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class="sc-ace17a57-0 sc-5f7d928-0 iMdtXa kritbo image-wrapper" width="fit-content" height="fit-content"><img alt="" loading="lazy" width="16" height="16" decoding="async" data-nimg="1" style="color:transparent;object-fit:contain" src="https://www.datocms-assets.com/96965/1728060023-speech-to-speech.svg"/></div></div><div class="sc-ace17a57-0 guuHrd"><span font-weight="medium" display="flex" tabindex="-1" class="sc-b323b31-0 sc-3618c394-13 hHDluE dVEgqo">Voice Agent API</span><span font-size="textXs" class="sc-b323b31-0 sc-3618c394-14 lnJhVG cFsKfJ">For real-time AI Agents</span></div></div></a></div><div width="max-content" class="sc-ace17a57-0 sc-3618c394-5 dMJoKC bGaVbc"><a rel="" target="" text-decoration="none" class="sc-e69ac761-0 cCnzAI sc-3618c394-10 jycipe" href="/product/text-to-speech"><div class="sc-ace17a57-0 gCajMv"><div class="sc-ace17a57-0 sc-3618c394-4 ftcNci bpvjgx"><div class="sc-ace17a57-0 sc-5f7d928-0 iMdtXa kritbo image-wrapper" width="fit-content" height="fit-content"><img alt="" loading="lazy" width="16" height="16" decoding="async" data-nimg="1" style="color:transparent;object-fit:contain" src="https://www.datocms-assets.com/96965/1728060055-text-to-speech.svg"/></div></div><div class="sc-ace17a57-0 guuHrd"><span font-weight="medium" display="flex" tabindex="-1" class="sc-b323b31-0 sc-3618c394-13 hHDluE dVEgqo">Text to Speech API</span><span font-size="textXs" class="sc-b323b31-0 sc-3618c394-14 lnJhVG cFsKfJ">Responsive, natural-sounding voices</span></div></div></a></div><div width="max-content" class="sc-ace17a57-0 sc-3618c394-5 dMJoKC bGaVbc"><a rel="" target="" text-decoration="none" class="sc-e69ac761-0 cCnzAI sc-3618c394-10 jycipe" href="/product/speech-to-text"><div class="sc-ace17a57-0 gCajMv"><div class="sc-ace17a57-0 sc-3618c394-4 ftcNci bpvjgx"><div class="sc-ace17a57-0 sc-5f7d928-0 iMdtXa kritbo image-wrapper" width="fit-content" height="fit-content"><img alt="" loading="lazy" width="16" height="16" decoding="async" data-nimg="1" style="color:transparent;object-fit:contain" src="https://www.datocms-assets.com/96965/1728060077-speech-to-text.svg"/></div></div><div class="sc-ace17a57-0 guuHrd"><span font-weight="medium" display="flex" tabindex="-1" class="sc-b323b31-0 sc-3618c394-13 hHDluE dVEgqo">Speech to Text API</span><span font-size="textXs" class="sc-b323b31-0 sc-3618c394-14 lnJhVG cFsKfJ">Unmatched accuracy, speed & cost</span></div></div></a></div><div width="max-content" class="sc-ace17a57-0 sc-3618c394-5 dMJoKC bGaVbc"><a rel="" target="" text-decoration="none" class="sc-e69ac761-0 cCnzAI sc-3618c394-10 jycipe" href="/product/audio-intelligence"><div class="sc-ace17a57-0 gCajMv"><div class="sc-ace17a57-0 sc-3618c394-4 ftcNci bpvjgx"><div class="sc-ace17a57-0 sc-5f7d928-0 iMdtXa kritbo image-wrapper" width="fit-content" height="fit-content"><img alt="" loading="lazy" width="16" height="16" decoding="async" data-nimg="1" style="color:transparent;object-fit:contain" src="https://www.datocms-assets.com/96965/1728060103-brain-ai.svg"/></div></div><div class="sc-ace17a57-0 guuHrd"><span font-weight="medium" display="flex" tabindex="-1" class="sc-b323b31-0 sc-3618c394-13 hHDluE dVEgqo">Audio Intelligence API</span><span font-size="textXs" class="sc-b323b31-0 sc-3618c394-14 lnJhVG cFsKfJ">Powered by AI Language models</span></div></div></a></div></div></div></div></div></div><div width="calc(100%)" class="sc-ace17a57-0 sc-3618c394-6 hiDOHk juEUpi"><div width="100%" class="sc-ace17a57-0 lePzZD"><span display="block" height="36px" class="sc-b323b31-0 ilnsGr">Announcements</span><style data-emotion="css 1y3y2u2">.css-1y3y2u2{font-family:var(--font-inter, sans-serif);font-size:1.0446428571428572rem;line-height:1.75rem;font-weight:700;text-transform:uppercase;min-width:64px;padding:4px 5px;border-radius:4px;-webkit-transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms 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MuiButton-colorSecondary MuiButton-root MuiButton-text MuiButton-textSecondary MuiButton-sizeSmall MuiButton-textSizeSmall MuiButton-colorSecondary sc-d74559df-0 fqnlbI sc-6e03a9e4-0 iumJHL sc-3618c394-0 gxydGy css-6n9fb7" tabindex="0" type="button" __typename="ComponentCallToActionRecord" id="Xho9X9_YQj2HBRVr87BG0g" href="/learn?type=Article&page=1&category=Announcements"><span class="sc-b323b31-0 fcPowg button-label" display="inline-flex"><span>View more</span></span><style data-emotion="css kcxyz4">.css-kcxyz4{display:inherit;margin-right:-2px;margin-left:8px;}.css-kcxyz4>*:nth-of-type(1){font-size:18px;}</style><span class="MuiButton-icon MuiButton-endIcon MuiButton-iconSizeSmall css-kcxyz4"><div width="fit-content" class="sc-ace17a57-0 ddioGD"><span display="inline-flex" class="sc-b323b31-0 bZmEHx"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 448 512" height="16" width="16" xmlns="http://www.w3.org/2000/svg"><path d="M438.6 278.6c12.5-12.5 12.5-32.8 0-45.3l-160-160c-12.5-12.5-32.8-12.5-45.3 0s-12.5 32.8 0 45.3L338.8 224 32 224c-17.7 0-32 14.3-32 32s14.3 32 32 32l306.7 0L233.4 393.4c-12.5 12.5-12.5 32.8 0 45.3s32.8 12.5 45.3 0l160-160z"></path></svg></span></div></span></a></div><div class="sc-ace17a57-0 gzWdaa"><a rel="" target="" display="-webkit-box" height="100%" width="100%" class="sc-e69ac761-0 ecplwP sc-2850a57f-3 cPKdIq" href="/learn/introducing-nova-3-speech-to-text-api"><div width="100%" height="100%" id="e1wy33mNTlGk8-WqDH28_Q" class="sc-ace17a57-0 sc-2850a57f-1 fJWxEy ggobuO"><div width="100%" height="150px" class="sc-6293d692-0 eWcIvK"><div class="sc-ace17a57-0 sc-5f7d928-0 fvbMGK image-wrapper" width="100%" height="100%"><img alt="Introducing Nova-3: Setting a New Standard for AI-Driven Speech-to-Text" loading="lazy" width="590" height="259" decoding="async" data-nimg="1" class="sc-2850a57f-2 dSsmQU" style="color:transparent;object-fit:cover" srcSet="/_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1740086862-2502-nova-3-blog-header.jpg%3Fauto%3Dformat%26w%3D590&w=640&q=75 1x, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1740086862-2502-nova-3-blog-header.jpg%3Fauto%3Dformat%26w%3D590&w=1200&q=75 2x" src="/_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1740086862-2502-nova-3-blog-header.jpg%3Fauto%3Dformat%26w%3D590&w=1200&q=75"/></div></div><div class="sc-ace17a57-0 biWqHE"><span font-weight="semiBold" class="sc-b323b31-0 iNRMrC"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 320 512" color="#ffffff" class="sc-2850a57f-0 Tcnof" style="color:#ffffff" height="12" width="12" xmlns="http://www.w3.org/2000/svg"><path d="M285.476 272.971L91.132 467.314c-9.373 9.373-24.569 9.373-33.941 0l-22.667-22.667c-9.357-9.357-9.375-24.522-.04-33.901L188.505 256 34.484 101.255c-9.335-9.379-9.317-24.544.04-33.901l22.667-22.667c9.373-9.373 24.569-9.373 33.941 0L285.475 239.03c9.373 9.372 9.373 24.568.001 33.941z"></path></svg>Introducing Nova-3: Setting a New Standard for AI-Driven Speech-to-Text</span><span class="sc-b323b31-0 jUNaqu">Published on 02/12/25</span></div></div></a></div></div></div></div></li><li height="fit-content" width="100%" tabindex="0" class="sc-6293d692-0 hEIHLV"><div width="100%" class="sc-ace17a57-0 gbwWMz"><div height="fit-content" width="100%" class="sc-ace17a57-0 caCSrG"><span font-size="textXl" font-weight="medium" display="block" cursor="pointer" width="100%" class="sc-b323b31-0 kzoxAi">Solutions</span><div transform="rotateX(0deg)" class="sc-ace17a57-0 fxtsZN"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 448 512" color="#A9A9AD" style="color:#A9A9AD" height="12" width="12" xmlns="http://www.w3.org/2000/svg"><path d="M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z"></path></svg></div></div></div><div pointer-events="none" class="sc-6293d692-0 sc-610ba7e0-0 fqJJID gkvAJG"><div class="sc-ace17a57-0 iIvmda"><div class="sc-ace17a57-0 fXUJvn"><div class="sc-ace17a57-0 jbARwL"><div class="sc-ace17a57-0 exshrD"><div class="sc-ace17a57-0 gYFcFc"><span display="block" width="auto" class="sc-b323b31-0 gIJLbd">Use Cases</span></div><div class="sc-ace17a57-0 eTCxuy"><div class="sc-ace17a57-0 ldsYPN"><div width="max-content" class="sc-ace17a57-0 sc-3618c394-5 dMJoKC kjWGMU"><a rel="" target="" text-decoration="none" class="sc-e69ac761-0 cCnzAI sc-3618c394-10 jycipe" href="/solutions/contact-centers"><div class="sc-ace17a57-0 ljypZA"><div class="sc-ace17a57-0 sc-3618c394-4 iNSltq iIhisP"><div class="sc-ace17a57-0 sc-5f7d928-0 iMdtXa kritbo image-wrapper" width="fit-content" height="fit-content"><img alt="" loading="lazy" width="16" height="16" decoding="async" data-nimg="1" style="color:transparent;object-fit:contain" src="https://www.datocms-assets.com/96965/1728060222-customer-service.svg"/></div></div><div class="sc-ace17a57-0 guuHrd"><span font-weight="medium" display="flex" tabindex="-1" class="sc-b323b31-0 sc-3618c394-13 hHDluE dRVqCB">Contact Centers</span></div></div></a></div><div width="max-content" class="sc-ace17a57-0 sc-3618c394-5 dMJoKC kjWGMU"><a rel="" target="" text-decoration="none" class="sc-e69ac761-0 cCnzAI sc-3618c394-10 jycipe" href="/solutions/medical-transcription"><div class="sc-ace17a57-0 ljypZA"><div class="sc-ace17a57-0 sc-3618c394-4 iNSltq iIhisP"><div class="sc-ace17a57-0 sc-5f7d928-0 iMdtXa kritbo image-wrapper" width="fit-content" height="fit-content"><img alt="" loading="lazy" width="16" height="16" decoding="async" data-nimg="1" style="color:transparent;object-fit:contain" src="https://www.datocms-assets.com/96965/1728060247-medical.svg"/></div></div><div class="sc-ace17a57-0 guuHrd"><span font-weight="medium" display="flex" tabindex="-1" class="sc-b323b31-0 sc-3618c394-13 hHDluE dRVqCB">Medical Transcription</span></div></div></a></div><div width="max-content" class="sc-ace17a57-0 sc-3618c394-5 dMJoKC kjWGMU"><a rel="" target="" text-decoration="none" class="sc-e69ac761-0 cCnzAI sc-3618c394-10 jycipe" href="/deepgram-for-voicebots-and-chatbots"><div class="sc-ace17a57-0 ljypZA"><div class="sc-ace17a57-0 sc-3618c394-4 iNSltq iIhisP"><div class="sc-ace17a57-0 sc-5f7d928-0 iMdtXa kritbo image-wrapper" width="fit-content" height="fit-content"><img alt="" loading="lazy" width="16" height="16" decoding="async" data-nimg="1" style="color:transparent;object-fit:contain" src="https://www.datocms-assets.com/96965/1728060265-conversational-ai.svg"/></div></div><div class="sc-ace17a57-0 guuHrd"><span font-weight="medium" display="flex" tabindex="-1" class="sc-b323b31-0 sc-3618c394-13 hHDluE dRVqCB">Conversational AI</span></div></div></a></div><div width="max-content" class="sc-ace17a57-0 sc-3618c394-5 dMJoKC kjWGMU"><a rel="" target="" text-decoration="none" class="sc-e69ac761-0 cCnzAI sc-3618c394-10 jycipe" href="/solutions/speech-analytics"><div class="sc-ace17a57-0 ljypZA"><div class="sc-ace17a57-0 sc-3618c394-4 iNSltq iIhisP"><div class="sc-ace17a57-0 sc-5f7d928-0 iMdtXa kritbo image-wrapper" width="fit-content" height="fit-content"><img alt="" loading="lazy" width="16" height="16" decoding="async" data-nimg="1" style="color:transparent;object-fit:contain" src="https://www.datocms-assets.com/96965/1728060282-speech-analytics.svg"/></div></div><div class="sc-ace17a57-0 guuHrd"><span font-weight="medium" display="flex" tabindex="-1" class="sc-b323b31-0 sc-3618c394-13 hHDluE dRVqCB">Speech Analytics</span></div></div></a></div><div width="max-content" class="sc-ace17a57-0 sc-3618c394-5 dMJoKC kjWGMU"><a rel="" target="" text-decoration="none" class="sc-e69ac761-0 cCnzAI sc-3618c394-10 jycipe" href="/solutions/media-transcription"><div class="sc-ace17a57-0 ljypZA"><div class="sc-ace17a57-0 sc-3618c394-4 iNSltq iIhisP"><div class="sc-ace17a57-0 sc-5f7d928-0 iMdtXa kritbo image-wrapper" width="fit-content" height="fit-content"><img alt="" loading="lazy" width="16" height="16" decoding="async" data-nimg="1" style="color:transparent;object-fit:contain" src="https://www.datocms-assets.com/96965/1728060298-media.svg"/></div></div><div class="sc-ace17a57-0 guuHrd"><span font-weight="medium" display="flex" tabindex="-1" class="sc-b323b31-0 sc-3618c394-13 hHDluE dRVqCB">Media Transcription</span></div></div></a></div></div></div></div><div class="sc-ace17a57-0 bcBFEg"><a rel="" target="" class="sc-e69ac761-0 bkHGsI sc-3618c394-11 cTfqJK" href="/customers"><div class="sc-ace17a57-0 ldePaW"><div width="28px" height="28px" class="sc-6293d692-0 sc-3618c394-1 ipShUF kXFUqt"><div class="sc-ace17a57-0 sc-5f7d928-0 fvbMGK image-wrapper" width="100%" height="100%"><img alt="Customers" loading="lazy" width="16" height="16" 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fxtsZN"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 448 512" color="#A9A9AD" style="color:#A9A9AD" height="12" width="12" xmlns="http://www.w3.org/2000/svg"><path d="M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z"></path></svg></div></div></div><div pointer-events="none" class="sc-6293d692-0 sc-610ba7e0-0 fqJJID gkvAJG"><div class="sc-ace17a57-0 iIvmda"><div class="sc-ace17a57-0 fXUJvn"><div class="sc-ace17a57-0 jbARwL"><div class="sc-ace17a57-0 exshrD"><div class="sc-ace17a57-0 gYFcFc"><span display="block" width="auto" class="sc-b323b31-0 gIJLbd">Resources</span></div><div class="sc-ace17a57-0 eTCxuy"><div class="sc-ace17a57-0 ldsYPN"><div width="max-content" class="sc-ace17a57-0 sc-3618c394-5 dMJoKC kjWGMU"><a rel="" 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alt="Transcription Tool" loading="lazy" width="16" height="16" decoding="async" data-nimg="1" class="sc-3618c394-8 jzJMzZ" style="color:transparent;object-fit:cover" src="https://www.datocms-assets.com/96965/1728060712-transcription.svg"/></div></div><span font-size="textSm" class="sc-b323b31-0 sc-3618c394-15 fmcyDO gpxdfo">Transcription Tool</span></div></a></div></div></div></div></div></li><li height="fit-content" width="100%" tabindex="0" class="sc-6293d692-0 hEIHLV"><div width="100%" class="sc-ace17a57-0 gbwWMz"><div height="fit-content" width="100%" class="sc-ace17a57-0 caCSrG"><span font-size="textXl" font-weight="medium" display="block" cursor="pointer" width="100%" class="sc-b323b31-0 kzoxAi">Developers</span><div transform="rotateX(0deg)" class="sc-ace17a57-0 fxtsZN"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 448 512" color="#A9A9AD" style="color:#A9A9AD" height="12" width="12" xmlns="http://www.w3.org/2000/svg"><path d="M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z"></path></svg></div></div></div><div pointer-events="none" class="sc-6293d692-0 sc-610ba7e0-0 fqJJID gkvAJG"><div class="sc-ace17a57-0 iIvmda"><div class="sc-ace17a57-0 fXUJvn"><div class="sc-ace17a57-0 jbARwL"><div class="sc-ace17a57-0 exshrD"><div class="sc-ace17a57-0 eTCxuy"><div class="sc-ace17a57-0 ldsYPN"><div width="max-content" class="sc-ace17a57-0 sc-3618c394-5 dMJoKC kjWGMU"><a href="https://developers.deepgram.com/documentation/" rel="noreferrer noopener" target="_blank" text-decoration="none" class="sc-e69ac761-0 cCnzAI sc-3618c394-10 jycipe"><div class="sc-ace17a57-0 ljypZA"><div class="sc-ace17a57-0 sc-3618c394-4 iNSltq iIhisP"><div class="sc-ace17a57-0 sc-5f7d928-0 iMdtXa kritbo image-wrapper" 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src="https://www.datocms-assets.com/96965/1728060860-tutorials.svg"/></div></div><div class="sc-ace17a57-0 guuHrd"><span font-weight="medium" display="flex" tabindex="-1" class="sc-b323b31-0 sc-3618c394-13 hHDluE dRVqCB">Tutorials</span></div></div></a></div><div width="max-content" class="sc-ace17a57-0 sc-3618c394-5 dMJoKC kjWGMU"><a href="https://status.deepgram.com/" rel="noreferrer noopener" target="_blank" text-decoration="none" class="sc-e69ac761-0 cCnzAI sc-3618c394-10 jycipe"><div class="sc-ace17a57-0 ljypZA"><div class="sc-ace17a57-0 sc-3618c394-4 iNSltq iIhisP"><div class="sc-ace17a57-0 sc-5f7d928-0 iMdtXa kritbo image-wrapper" width="fit-content" height="fit-content"><img alt="" loading="lazy" width="16" height="16" decoding="async" data-nimg="1" style="color:transparent;object-fit:contain" src="https://www.datocms-assets.com/96965/1728060872-status.svg"/></div></div><div class="sc-ace17a57-0 guuHrd"><span font-weight="medium" display="flex" tabindex="-1" class="sc-b323b31-0 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0ms;color:#9c27b0;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#ffffff;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-es23wo:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(156, 39, 176, 0.04);}@media (hover: none){.css-es23wo:hover{background-color:transparent;}}.css-es23wo.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-es23wo::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms 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1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#9c27b0;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#ffffff;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-1vy4m6x::-moz-focus-inner{border-style:none;}.css-1vy4m6x.Mui-disabled{pointer-events:none;cursor:default;}@media print{.css-1vy4m6x{-webkit-print-color-adjust:exact;color-adjust:exact;}}.css-1vy4m6x:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(156, 39, 176, 0.04);}@media (hover: none){.css-1vy4m6x:hover{background-color:transparent;}}.css-1vy4m6x.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-1vy4m6x::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-1vy4m6x:hover{color:#79AFFA;background-color:transparent;}.css-1vy4m6x:focus-visible{color:#ffffff;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-1vy4m6x.Mui-disabled{color:#ffffff;opacity:0.2;}</style><a class="MuiButtonBase-root MuiButton-root MuiButton-text MuiButton-textSecondary MuiButton-sizeMedium MuiButton-textSizeMedium MuiButton-colorSecondary MuiButton-root MuiButton-text MuiButton-textSecondary MuiButton-sizeMedium MuiButton-textSizeMedium MuiButton-colorSecondary sc-d74559df-0 cIekQB sc-84b76e46-0 sc-f5e67a3c-0 jroYld css-1vy4m6x" tabindex="0" type="button" href="https://console.deepgram.com/" target="_self" id="108492178" __typename="ComponentCallToActionRecord"><span class="sc-b323b31-0 btXZGI button-label" display="inline-flex"><span>Log In</span></span></a><style data-emotion="css 134mfhg">.css-134mfhg{font-family:var(--font-inter, sans-serif);font-size:0.875rem;line-height:1.75rem;font-weight:700;text-transform:uppercase;min-width:64px;padding:6px 16px;border-radius:4px;-webkit-transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;box-shadow:0px 3px 1px -2px rgba(0,0,0,0.2),0px 2px 2px 0px rgba(0,0,0,0.14),0px 1px 5px 0px rgba(0,0,0,0.12);min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;background:#0B0B0C;color:#ffffff;border:1px solid #ffffff;}.css-134mfhg:hover{-webkit-text-decoration:none;text-decoration:none;box-shadow:0px 2px 4px -1px rgba(0,0,0,0.2),0px 4px 5px 0px rgba(0,0,0,0.14),0px 1px 10px 0px rgba(0,0,0,0.12);}.css-134mfhg:active{box-shadow:0px 5px 5px -3px rgba(0,0,0,0.2),0px 8px 10px 1px rgba(0,0,0,0.14),0px 3px 14px 2px rgba(0,0,0,0.12);}.css-134mfhg.Mui-focusVisible{box-shadow:0px 3px 5px -1px rgba(0,0,0,0.2),0px 6px 10px 0px rgba(0,0,0,0.14),0px 1px 18px 0px 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16px;border-radius:4px;-webkit-transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;box-shadow:0px 3px 1px -2px rgba(0,0,0,0.2),0px 2px 2px 0px rgba(0,0,0,0.14),0px 1px 5px 0px rgba(0,0,0,0.12);min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;background:#0B0B0C;color:#ffffff;border:1px solid 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sc-84b76e46-0 etnILU sc-f5e67a3c-0 jroYeL css-aaf570" tabindex="0" type="button" id="T-CCS94ZQ2CRFyuYD-Kv-Q" __typename="ComponentCallToActionRecord" href="/contact-us"><span class="sc-b323b31-0 fcPowg button-label" display="inline-flex"><span>Get a Demo</span></span></a><style data-emotion="css 40xoaf">.css-40xoaf{font-family:var(--font-inter, sans-serif);font-size:0.875rem;line-height:1.75rem;font-weight:700;text-transform:uppercase;min-width:64px;padding:6px 16px;border-radius:4px;-webkit-transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:rgba(0, 0, 0, 0.87);background-color:#00E062;box-shadow:0px 3px 1px 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data-emotion="css ubnyan">.css-ubnyan{display:-webkit-inline-box;display:-webkit-inline-flex;display:-ms-inline-flexbox;display:inline-flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;position:relative;box-sizing:border-box;-webkit-tap-highlight-color:transparent;background-color:transparent;outline:0;border:0;margin:0;border-radius:0;padding:0;cursor:pointer;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;vertical-align:middle;-moz-appearance:none;-webkit-appearance:none;-webkit-text-decoration:none;text-decoration:none;color:inherit;font-family:var(--font-inter, sans-serif);font-size:0.875rem;line-height:1.75rem;font-weight:700;text-transform:uppercase;min-width:64px;padding:6px 16px;border-radius:4px;-webkit-transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:rgba(0, 0, 0, 0.87);background-color:#00E062;box-shadow:0px 3px 1px -2px rgba(0,0,0,0.2),0px 2px 2px 0px rgba(0,0,0,0.14),0px 1px 5px 0px rgba(0,0,0,0.12);min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;background-color:#ffffff;color:#0B0B0C;border:1px solid #ffffff;}.css-ubnyan::-moz-focus-inner{border-style:none;}.css-ubnyan.Mui-disabled{pointer-events:none;cursor:default;}@media print{.css-ubnyan{-webkit-print-color-adjust:exact;color-adjust:exact;}}.css-ubnyan:hover{-webkit-text-decoration:none;text-decoration:none;background-color:#00BB49;box-shadow:0px 2px 4px -1px rgba(0,0,0,0.2),0px 4px 5px 0px rgba(0,0,0,0.14),0px 1px 10px 0px rgba(0,0,0,0.12);}@media (hover: none){.css-ubnyan:hover{background-color:#00E062;}}.css-ubnyan:active{box-shadow:0px 5px 5px -3px rgba(0,0,0,0.2),0px 8px 10px 1px rgba(0,0,0,0.14),0px 3px 14px 2px rgba(0,0,0,0.12);}.css-ubnyan.Mui-focusVisible{box-shadow:0px 3px 5px -1px rgba(0,0,0,0.2),0px 6px 10px 0px rgba(0,0,0,0.14),0px 1px 18px 0px rgba(0,0,0,0.12);}.css-ubnyan.Mui-disabled{color:rgba(0, 0, 0, 0.26);box-shadow:none;background-color:rgba(0, 0, 0, 0.12);}.css-ubnyan::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-ubnyan::before{background:linear-gradient(to right, #008fc1, #00f099, #008fc1, #00f099);-webkit-background-size:300% 100%;background-size:300% 100%;}.css-ubnyan:hover{color:#0B0B0C;box-shadow:0px 1px 2px rgba(38, 44, 52, 0.05);background:#ffffff;}.css-ubnyan:hover::before{opacity:1;-webkit-background-position:100% 0;background-position:100% 0;}.css-ubnyan:focus{background:#ffffff;box-shadow:0px 1px 2px rgba(16, 24, 40, 0.05),0px 0px 0px 2px #687EF7;border-color:#ffffff;}.css-ubnyan.Mui-disabled{background:#2C2C33;color:#A9A9AD;}</style><a class="MuiButtonBase-root MuiButton-root MuiButton-contained MuiButton-containedPrimary MuiButton-sizeMedium MuiButton-containedSizeMedium MuiButton-colorPrimary MuiButton-root MuiButton-contained MuiButton-containedPrimary MuiButton-sizeMedium MuiButton-containedSizeMedium MuiButton-colorPrimary sc-d74559df-0 cIekQB sc-84b76e46-0 etnILU sc-f5e67a3c-0 jroYeL css-ubnyan" tabindex="0" type="button" href="https://console.deepgram.com/signup" target="_self" id="108492199" __typename="ComponentCallToActionRecord"><span class="sc-b323b31-0 btXZGI button-label" display="inline-flex"><span>Sign Up</span></span></a></div></ul></div></div></div><div display="none" id="nav-overlay" height="0" class="sc-ace17a57-0 jUgQHG"></div></div></nav></div></header><section id="" width="100%" class="sc-ace17a57-0 sc-b22001da-2 iLVWKa eAcnIZ"><div width="100%" class="sc-6293d692-0 chAbBM"><div class="sc-ace17a57-0 doHfou"><a rel="" target="" href="/ai-glossary" class="sc-e69ac761-0 fobbYG"><h2 font-size="displayLg" font-family="primaryFont" class="sc-4555ca6a-0 htUWGk">AI Glossary</h2></a></div></div></section><section id="" width="100%" class="sc-ace17a57-0 sc-b22001da-2 hMGZHr dJJSTR"><div width="100%" class="sc-6293d692-0 chAbBM"><div height="100%" width="100%" class="sc-6293d692-0 gKLLRj"><div height="100%" width="100%" class="sc-662dedcb-0 qCkfD"><div class="sc-6293d692-0 csGpzP"><div class="sc-ace17a57-0 hhtFqm glossary-content-wrapper"><div class="sc-ace17a57-0 btkfVN"><div class="sc-ace17a57-0 sc-a48d0877-0 dJCIVv zIKHU"><h1 font-size="displaySm" letter-spacing="neg2" font-weight="semiBold" font-family="primaryFont" class="sc-b323b31-0 JYZsj">Model Interpretability</h1><div class="sc-ace17a57-0 fJkbQy"><p font-family="bodyFont" class="sc-5159831f-0 GBftN">This article delves deep into the essence of model interpretability, shining a light on its crucial role across various sectors, from healthcare to finance.</p></div></div></div><div class="sc-ace17a57-0 sc-4e888a2-0 hfDdWp cifBqP"><p class="sc-5159831f-0">With a staggering 91% of data professionals emphasizing the importance of interpretability for business stakeholders, it's clear that understanding the "why" behind model predictions isn't just a preference—it's a necessity. </p><p class="sc-5159831f-0">This article delves deep into the essence of model interpretability, shining a light on its crucial role across various sectors, from healthcare to finance. You'll discover how interpretability acts as the linchpin in balancing model complexity with transparency, ensuring fairness, and adhering to regulatory demands. But more importantly, how does it foster trust among end-users? Let's embark on this exploration together, unearthing the significance of making the complex understandable. </p><h2 id="what-is-model-interpretability" class="sc-4555ca6a-0 sc-42818e5a-3 kIEulY ipqlKg">What is Model Interpretability</h2><p class="sc-5159831f-0">Interpretability in machine learning signifies the extent to which a human can understand and trust the decisions made by a model. It embodies the crucial bridge linking sophisticated computational models with their practical applications, where trust and transparency reign supreme. Consider the following facets of model interpretability:</p><ul class="sc-ace17a57-0 sc-42818e5a-1 dslPBO dZzOHq"><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Healthcare and Life Sciences:</span> Interpretability holds paramount importance in healthcare and life sciences. Here, decisions can quite literally mean the difference between life and death. Understanding the rationale behind a model's prediction ensures that healthcare professionals can trust these tools, leading to better patient outcomes. To learn more about healthcare and life sciences, click <a href="https://deepgram.com/learn/the-future-of-healthcare-enhancing-patient-experience-with-voice-enabled-ai-copil">here</a>.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Complexity vs. Interpretability:</span> A delicate balance exists between a model's complexity and its interpretability. As algorithms become more intricate, comprehending their decision-making processes becomes more challenging. This tug-of-war necessitates a careful approach to design models that are both powerful and understandable.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Ensuring Fairness and Compliance:</span> The role of interpretability extends to debugging models, enhancing their performance, and ensuring they make unbiased decisions. This aspect is especially crucial in sectors like finance and healthcare, where explainability isn't just ethical—it's legally mandated.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Fostering Model Trust:</span> At the heart of interpretability lies the concept of 'model trust.' When end-users understand how a model arrives at its predictions, their confidence in these tools skyrockets. This trust is foundational, especially in applications where users rely on model predictions for critical decision-making.</p></li></li></ul><p class="sc-5159831f-0">In essence, model interpretability weaves the thread of trust through the fabric of machine learning applications. It ensures that as we venture further into the age of AI, our reliance on these models is built on a solid foundation of understanding and transparency.</p><h2 id="types-of-model-interpretability-methods" class="sc-4555ca6a-0 sc-42818e5a-3 kIEulY ipqlKg">Types of Model Interpretability Methods</h2><p class="sc-5159831f-0"><div width="100%" class="sc-ace17a57-0 ldWHw component-img-wrapper" id="IMVv3CVZR7at3ZHNX-hR9w"><div class="sc-ace17a57-0 sc-5f7d928-0 iLvNR kritbo image-wrapper" width="fit-content" height="fit-content" display="flex"><img alt="" title="" loading="lazy" width="1996" height="304" decoding="async" data-nimg="1" class="sc-3ec8aa52-0 jTMTOn desktop-image" style="color:transparent;object-fit:contain;background-size:contain;background-position:50% 50%;background-repeat:no-repeat;background-image:url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 1996 304'%3E%3Cfilter id='b' color-interpolation-filters='sRGB'%3E%3CfeGaussianBlur stdDeviation='20'/%3E%3CfeColorMatrix values='1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 100 -1' result='s'/%3E%3CfeFlood x='0' y='0' width='100%25' height='100%25'/%3E%3CfeComposite operator='out' in='s'/%3E%3CfeComposite in2='SourceGraphic'/%3E%3CfeGaussianBlur stdDeviation='20'/%3E%3C/filter%3E%3Cimage width='100%25' height='100%25' x='0' y='0' preserveAspectRatio='none' style='filter: url(%23b);' href='/deepgram.jpg'/%3E%3C/svg%3E")" sizes="(min-width: 992px) 810px, 100vw" srcSet="/_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1712769285-screen-shot-2024-04-10-at-10-14-30-am.png&w=640&q=75 640w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1712769285-screen-shot-2024-04-10-at-10-14-30-am.png&w=750&q=75 750w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1712769285-screen-shot-2024-04-10-at-10-14-30-am.png&w=828&q=75 828w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1712769285-screen-shot-2024-04-10-at-10-14-30-am.png&w=1080&q=75 1080w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1712769285-screen-shot-2024-04-10-at-10-14-30-am.png&w=1200&q=75 1200w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1712769285-screen-shot-2024-04-10-at-10-14-30-am.png&w=1920&q=75 1920w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1712769285-screen-shot-2024-04-10-at-10-14-30-am.png&w=2048&q=75 2048w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1712769285-screen-shot-2024-04-10-at-10-14-30-am.png&w=3840&q=75 3840w" src="/_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1712769285-screen-shot-2024-04-10-at-10-14-30-am.png&w=3840&q=75"/></div><div font-size="textSm" font-style="italic" class="sc-6293d692-0 jgEMAk"></div></div></p><p class="sc-5159831f-0">In the quest for transparency within machine learning models, various interpretability methods have emerged. A significant survey by Two Sigma categorizes these methods into three primary types: application-grounded, human-grounded, and functionally grounded evaluation. Each of these methods offers a unique perspective on model interpretability, catering to different needs and scenarios.</p><h3 id="applicationgrounded-evaluation" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">Application-Grounded Evaluation</h3><p class="sc-5159831f-0">Application-grounded evaluation stands out for its emphasis on practical application. This method involves:</p><ul class="sc-ace17a57-0 sc-42818e5a-1 dslPBO dZzOHq"><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Direct involvement of a human in the loop:</span> It necessitates that a person directly interacts with the model within a real-life scenario, ensuring that the interpretability methods are grounded in practical use.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Tailored to specific applications:</span> The evaluation focuses on how well the interpretability method aids in understanding model decisions within a particular domain, such as healthcare diagnostics or financial forecasting.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Strengths:</span> Provides direct feedback on the utility of interpretability methods in real-world applications, ensuring that the insights are actionable and relevant.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Weaknesses:</span> Time-consuming and resource-intensive, as it requires setting up specific application scenarios and direct human involvement.</p></li></li></ul><h3 id="humangrounded-evaluation" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">Human-Grounded Evaluation</h3><p class="sc-5159831f-0">Human-grounded evaluation takes a more general approach:</p><ul class="sc-ace17a57-0 sc-42818e5a-1 dslPBO dZzOHq"><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Simplified tasks to assess interpretability:</span> Instead of in-depth application scenarios, this method uses simplified tasks that evaluate whether model explanations make sense to average users.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Tools and techniques:</span> Popular tools like LIME (Local Interpretable Model-agnostic Explanations) and SHAP (SHapley Additive exPlanations) are often used in this evaluation type to provide insights into how model decisions are made.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Strengths:</span> More scalable than application-grounded evaluation, allowing for quicker, broader insights into model interpretability.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Weaknesses:</span> May not fully capture the complexity of real-world applications, potentially oversimplifying the interpretability needs of specific scenarios.</p></li></li></ul><h3 id="functionally-grounded-evaluation" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">Functionally Grounded Evaluation</h3><p class="sc-5159831f-0">Functionally grounded evaluation focuses on theoretical aspects:</p><ul class="sc-ace17a57-0 sc-42818e5a-1 dslPBO dZzOHq"><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Assessment based on predefined criteria:</span> This method evaluates interpretability based on whether a model or method meets certain predefined theoretical criteria, without the direct need for human judgment.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Objective and structured:</span> Offers a structured way to assess models based on clear, objective criteria.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Strengths:</span> Efficient and straightforward, providing a quick means to gauge basic interpretability without extensive human involvement.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Weaknesses:</span> Lacks the nuanced understanding that human judgment can provide, possibly overlooking practical interpretability challenges.</p></li></li></ul><h3 id="the-trend-towards-hybrid-approaches" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">The Trend Towards Hybrid Approaches</h3><p class="sc-5159831f-0">Interestingly, a growing trend points towards hybrid approaches that amalgamate elements from all three types of evaluations. This holistic strategy aims to harness the strengths of each method, achieving a more comprehensive understanding of model interpretability. By combining the practical insights of application-grounded evaluation, the scalability of human-grounded evaluation, and the objectivity of functionally grounded evaluation, these hybrid approaches represent the forefront of interpretability research.</p><p class="sc-5159831f-0">In sum, understanding the strengths and weaknesses of each interpretability method is crucial for selecting the appropriate approach for a given scenario. As the landscape of machine learning continues to evolve, so too will the strategies for making these models transparent and understandable to their end-users.</p><p class="sc-5159831f-0"><div width="100%" class="sc-ace17a57-0 ldWHw component-img-wrapper" id="Z5su9I_yQ16q7vzUlugSsg"><div class="sc-ace17a57-0 sc-5f7d928-0 iLvNR kritbo image-wrapper" width="fit-content" height="fit-content" display="flex"><img alt="" title="" loading="lazy" width="1472" height="950" decoding="async" data-nimg="1" class="sc-3ec8aa52-0 jTMTOn desktop-image" style="color:transparent;object-fit:contain;background-size:contain;background-position:50% 50%;background-repeat:no-repeat;background-image:url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 1472 950'%3E%3Cfilter id='b' color-interpolation-filters='sRGB'%3E%3CfeGaussianBlur stdDeviation='20'/%3E%3CfeColorMatrix values='1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 100 -1' result='s'/%3E%3CfeFlood x='0' y='0' width='100%25' height='100%25'/%3E%3CfeComposite operator='out' in='s'/%3E%3CfeComposite in2='SourceGraphic'/%3E%3CfeGaussianBlur stdDeviation='20'/%3E%3C/filter%3E%3Cimage width='100%25' height='100%25' x='0' y='0' preserveAspectRatio='none' style='filter: url(%23b);' href='/deepgram.jpg'/%3E%3C/svg%3E")" sizes="(min-width: 992px) 810px, 100vw" srcSet="/_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718528956-screen-shot-2024-06-16-at-2-09-13-am.png&w=640&q=75 640w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718528956-screen-shot-2024-06-16-at-2-09-13-am.png&w=750&q=75 750w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718528956-screen-shot-2024-06-16-at-2-09-13-am.png&w=828&q=75 828w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718528956-screen-shot-2024-06-16-at-2-09-13-am.png&w=1080&q=75 1080w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718528956-screen-shot-2024-06-16-at-2-09-13-am.png&w=1200&q=75 1200w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718528956-screen-shot-2024-06-16-at-2-09-13-am.png&w=1920&q=75 1920w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718528956-screen-shot-2024-06-16-at-2-09-13-am.png&w=2048&q=75 2048w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718528956-screen-shot-2024-06-16-at-2-09-13-am.png&w=3840&q=75 3840w" src="/_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718528956-screen-shot-2024-06-16-at-2-09-13-am.png&w=3840&q=75"/></div><div font-size="textSm" font-style="italic" class="sc-6293d692-0 jgEMAk"></div></div></p><h2 id="practical-application-of-model-interpretability" class="sc-4555ca6a-0 sc-42818e5a-3 kIEulY ipqlKg">Practical Application of Model Interpretability</h2><p class="sc-5159831f-0">Model interpretability extends far beyond a theoretical concept, embedding itself into the very fabric of industries that shape our daily lives. Healthcare, finance, and criminal justice represent sectors where the application of interpretability in machine learning models not only enhances operational efficiency but also reinforces ethical standards and compliance with regulatory mandates.</p><h3 id="healthcare-a-lifeline-for-diagnostic-precision" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">Healthcare: A Lifeline for Diagnostic Precision</h3><p class="sc-5159831f-0">In the realm of healthcare, the stakes couldn't be higher. Here, interpretability translates into the ability to uncover the rationale behind diagnostic and treatment recommendations made by AI systems. For instance, when a machine learning model identifies a novel pattern in patient data suggesting a predisposed genetic condition, clinicians need to understand the "why" behind this prediction to trust and act upon it. AWS documentation underscores the criticality of interpretability in healthcare, advocating for models that clinicians can interrogate for the evidence leading to their conclusions. Such transparency:</p><ul class="sc-ace17a57-0 sc-42818e5a-1 dslPBO dZzOHq"><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Facilitates trust</span> between clinicians and the AI tools they rely on.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Improves patient outcomes</span> by enabling more informed decision-making.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Ensures regulatory compliance</span>, meeting stringent standards for medical devices and software.</p></li></li></ul><h3 id="finance-decoding-the-logic-of-loan-approvals" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">Finance: Decoding the Logic of Loan Approvals</h3><p class="sc-5159831f-0">The finance sector, particularly in credit scoring models, relies heavily on interpretability. Understanding why a loan application gets approved or denied is crucial not just for regulatory compliance but also for maintaining fairness and transparency. According to AWS documentation, interpretability in financial models helps identify the factors influencing these decisions. This clarity allows financial institutions to:</p><ul class="sc-ace17a57-0 sc-42818e5a-1 dslPBO dZzOHq"><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Provide applicants with actionable feedback</span>, helping them improve their creditworthiness.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Detect and mitigate biases</span> in loan approval processes.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Ensure adherence to financial regulations</span> that mandate transparency in credit scoring.</p></li></li></ul><h3 id="criminal-justice-the-beacon-of-fairness" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">Criminal Justice: The Beacon of Fairness</h3><p class="sc-5159831f-0">In criminal justice, the deployment of predictive policing and risk assessment models has sparked a significant ethical debate. The crux of the matter lies in ensuring these models do not perpetuate biases or injustices. Implementing interpretability in these systems plays a pivotal role in:</p><ul class="sc-ace17a57-0 sc-42818e5a-1 dslPBO dZzOHq"><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Ensuring transparency</span> in how risk assessments are conducted.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Facilitating the auditability</span> of models to uncover any inherent biases.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Promoting fairness</span> by making the decision-making process visible and understandable to all stakeholders.</p></li></li></ul><h3 id="navigating-the-challenges" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">Navigating the Challenges</h3><p class="sc-5159831f-0">Despite the clear benefits, the road to achieving interpretability, especially in complex models like deep neural networks, is fraught with challenges. The intricate architecture of these models often makes it difficult to pinpoint the exact rationale behind specific decisions. However, advancements in interpretability methods and tools are gradually overcoming these hurdles, paving the way for more transparent AI applications.</p><h3 id="advocating-for-a-datacentric-approach" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">Advocating for a Data-Centric Approach</h3><p class="sc-5159831f-0">DCAI CSAIL MIT's introduction to Interpretable ML champions a data-centric approach to model development, emphasizing the importance of considering interpretability from the outset. This proactive stance ensures that models are not only accurate but also understandable. By prioritizing data quality and transparency in model design, developers can:</p><ul class="sc-ace17a57-0 sc-42818e5a-1 dslPBO dZzOHq"><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Avoid the pitfalls of biased or unexplainable models</span>.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Build trust with end-users</span> by providing clear insights into how predictions are made.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Foster innovation</span> in fields where interpretability is non-negotiable, such as healthcare and criminal justice.</p></li></li></ul><p class="sc-5159831f-0">The journey towards fully interpretable models is ongoing, with each step forward unlocking new possibilities for applying AI in ways that are both impactful and understandable. As this field evolves, so too will our ability to harness the power of AI for the greater good, ensuring that decisions that affect human lives are made with the utmost clarity and fairness.</p><p class="sc-5159831f-0"><div width="100%" class="sc-ace17a57-0 ldWHw component-img-wrapper" id="DLj1WuxXReqbXBdxGnJoCg"><div class="sc-ace17a57-0 sc-5f7d928-0 iLvNR kritbo image-wrapper" width="fit-content" height="fit-content" display="flex"><img alt="" title="" loading="lazy" width="1336" height="710" decoding="async" data-nimg="1" class="sc-3ec8aa52-0 jTMTOn desktop-image" style="color:transparent;object-fit:contain;background-size:contain;background-position:50% 50%;background-repeat:no-repeat;background-image:url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 1336 710'%3E%3Cfilter id='b' color-interpolation-filters='sRGB'%3E%3CfeGaussianBlur stdDeviation='20'/%3E%3CfeColorMatrix values='1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 100 -1' result='s'/%3E%3CfeFlood x='0' y='0' width='100%25' height='100%25'/%3E%3CfeComposite operator='out' in='s'/%3E%3CfeComposite in2='SourceGraphic'/%3E%3CfeGaussianBlur stdDeviation='20'/%3E%3C/filter%3E%3Cimage width='100%25' height='100%25' x='0' y='0' preserveAspectRatio='none' style='filter: url(%23b);' href='/deepgram.jpg'/%3E%3C/svg%3E")" sizes="(min-width: 992px) 810px, 100vw" srcSet="/_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718529084-screen-shot-2024-06-16-at-2-11-22-am.png&w=640&q=75 640w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718529084-screen-shot-2024-06-16-at-2-11-22-am.png&w=750&q=75 750w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718529084-screen-shot-2024-06-16-at-2-11-22-am.png&w=828&q=75 828w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718529084-screen-shot-2024-06-16-at-2-11-22-am.png&w=1080&q=75 1080w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718529084-screen-shot-2024-06-16-at-2-11-22-am.png&w=1200&q=75 1200w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718529084-screen-shot-2024-06-16-at-2-11-22-am.png&w=1920&q=75 1920w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718529084-screen-shot-2024-06-16-at-2-11-22-am.png&w=2048&q=75 2048w, /_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718529084-screen-shot-2024-06-16-at-2-11-22-am.png&w=3840&q=75 3840w" src="/_next/image?url=https%3A%2F%2Fwww.datocms-assets.com%2F96965%2F1718529084-screen-shot-2024-06-16-at-2-11-22-am.png&w=3840&q=75"/></div><div font-size="textSm" font-style="italic" class="sc-6293d692-0 jgEMAk"></div></div></p><h2 id="model-interpretability-vs-explainability" class="sc-4555ca6a-0 sc-42818e5a-3 kIEulY ipqlKg">Model Interpretability vs Explainability</h2><p class="sc-5159831f-0">In the ever-evolving landscape of machine learning and artificial intelligence, two terms frequently surface, sparking considerable debate among developers and stakeholders alike: model interpretability and explainability. While these concepts intertwine, understanding their distinctions is crucial in the development and deployment of AI models, especially in sensitive sectors like healthcare and finance where decisions have profound implications.</p><h3 id="defining-the-terms" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">Defining the Terms</h3><ul class="sc-ace17a57-0 sc-42818e5a-1 dslPBO dZzOHq"><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Model Interpretability</span> delves into the inner workings of machine learning models, striving for a comprehensive understanding of how models reach their conclusions. It demands a granular level of detail, enabling developers and users to trace and understand the decision-making path of the model.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0"><span font-weight="bold" class="sc-b323b31-0 caUwZV">Model Explainability</span>, on the other hand, focuses on the outcomes, providing insights into the decisions made by the model without necessarily detailing the process. It answers the 'what' rather than the 'how', making it slightly more accessible but less detailed compared to interpretability.</p></li></li></ul><h3 id="the-importance-of-detail" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">The Importance of Detail</h3><p class="sc-5159831f-0">Interpretability requires a deeper dive into the model's mechanics, often necessitating a more sophisticated understanding of machine learning principles. This depth:</p><ul class="sc-ace17a57-0 sc-42818e5a-1 dslPBO dZzOHq"><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0">Ensures developers can troubleshoot and refine models with precision.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0">Facilitates regulatory compliance, particularly in sectors where understanding the decision process is mandatory.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0">Helps in identifying and mitigating biases within the model, promoting fairness.</p></li></li></ul><p class="sc-5159831f-0">Explainability, with its broader overview, allows stakeholders without technical expertise to grasp the model's decisions, fostering trust and acceptance.</p><h3 id="regulatory-compliance-and-healthcare" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">Regulatory Compliance and Healthcare</h3><p class="sc-5159831f-0">Choosing between interpretability and explainability becomes pivotal in contexts where regulatory compliance enters the fray. In healthcare, for instance, regulatory bodies demand clear explanations of diagnostic and treatment recommendations made by AI. Scenarios where interpretability takes precedence include:</p><ul class="sc-ace17a57-0 sc-42818e5a-1 dslPBO dZzOHq"><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0">Developing models for diagnosing complex diseases, where understanding the rationale behind each diagnosis is crucial.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0">Creating treatment recommendation systems, where the stakes of each decision are high, and the reasoning must be transparent.</p></li></li></ul><p class="sc-5159831f-0">Conversely, explainability may suffice in less critical applications, such as patient monitoring systems, where the focus is on tracking and reporting rather than diagnosing.</p><h3 id="balancing-act-accuracy-vs-understandability" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">Balancing Act: Accuracy vs. Understandability</h3><p class="sc-5159831f-0">A key challenge in AI development is balancing model accuracy with interpretability or explainability. Insights shared on LinkedIn highlight this dilemma, noting that as models, particularly deep learning models, become more accurate, they often lose transparency. Strategies to navigate this balance include:</p><ul class="sc-ace17a57-0 sc-42818e5a-1 dslPBO dZzOHq"><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0">Employing hybrid models that combine interpretable and complex models to achieve both accuracy and transparency.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0">Utilizing post-hoc interpretation techniques, such as LIME or SHAP, to shed light on complex model decisions.</p></li></li></ul><h3 id="the-future-of-model-interpretability-and-explainability" class="sc-4555ca6a-0 sc-42818e5a-3 cGaypB ipqlKg">The Future of Model Interpretability and Explainability</h3><p class="sc-5159831f-0">The quest for making complex models both interpretable and explainable is at the forefront of AI research. Emerging AI technologies and methodologies aim to:</p><ul class="sc-ace17a57-0 sc-42818e5a-1 dslPBO dZzOHq"><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0">Develop novel approaches that enhance the transparency of deep learning models without compromising their performance.</p></li></li><li class="sc-ace17a57-0 sc-42818e5a-0 PRHwk hegRkn"><li><p class="sc-5159831f-0">Create standards and frameworks for interpretability and explainability that align with regulatory requirements and ethical considerations.</p></li></li></ul><p class="sc-5159831f-0">As AI continues to evolve, the focus on making models not just powerful but also understandable and trustworthy will remain paramount. The future direction of research in this area is poised to revolutionize how we develop, deploy, and interact with AI systems, ensuring they serve humanity in the most transparent and ethical way possible.</p><p class="sc-5159831f-0"><div width="100%" class="sc-ace17a57-0 ldWHw component-img-wrapper" id="OcUPVLYOTdiOH90vXDPFbA"><div class="sc-ace17a57-0 sc-5f7d928-0 iLvNR kritbo image-wrapper" width="fit-content" height="fit-content" display="flex"><img alt="" title="" loading="lazy" width="1512" height="788" decoding="async" data-nimg="1" class="sc-3ec8aa52-0 jTMTOn desktop-image" style="color:transparent;object-fit:contain;background-size:contain;background-position:50% 50%;background-repeat:no-repeat;background-image:url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 1512 788'%3E%3Cfilter id='b' color-interpolation-filters='sRGB'%3E%3CfeGaussianBlur stdDeviation='20'/%3E%3CfeColorMatrix values='1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 100 -1' 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kmKRMV">Rectified Linear Unit (ReLU)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/reproducibility-machine-learning" class="sc-e69ac761-0 kmKRMV">Reproducibility in Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/restricted-boltzmann-machines" class="sc-e69ac761-0 kmKRMV">Restricted Boltzmann Machines</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/semi-supervised-learning" class="sc-e69ac761-0 kmKRMV">Semi-Supervised Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/supervised-learning" class="sc-e69ac761-0 kmKRMV">Supervised Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/support-vector-machines-svm" class="sc-e69ac761-0 kmKRMV">Support Vector Machines (SVM)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/topic-modeling" class="sc-e69ac761-0 kmKRMV">Topic Modeling</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/uncertainty-machine-learning" class="sc-e69ac761-0 kmKRMV">Uncertainty in Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/vanishing-and-exploding-gradients" class="sc-e69ac761-0 kmKRMV">Vanishing and Exploding Gradients</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-interpretability" class="sc-e69ac761-0 kmKRMV">AI Interpretability</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/data-labeling" class="sc-e69ac761-0 kmKRMV">Data Labeling</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/inference-engine" class="sc-e69ac761-0 kmKRMV">Inference Engine</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/probabilistic-models-in-machine-learning" class="sc-e69ac761-0 kmKRMV">Probabilistic Models in Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/f1-score-machine-learning" class="sc-e69ac761-0 kmKRMV">F1 Score in Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/expectation-maximization" class="sc-e69ac761-0 kmKRMV">Expectation Maximization</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/beam-search-algorithm" class="sc-e69ac761-0 kmKRMV">Beam Search Algorithm</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/embedding-layer" class="sc-e69ac761-0 kmKRMV">Embedding Layer</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/differential-privacy" class="sc-e69ac761-0 kmKRMV">Differential Privacy</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/data-poisoning" class="sc-e69ac761-0 kmKRMV">Data Poisoning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/causal-inference" class="sc-e69ac761-0 kmKRMV">Causal Inference</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/capsule-neural-network" class="sc-e69ac761-0 kmKRMV">Capsule Neural Network</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/attention-mechanisms" class="sc-e69ac761-0 kmKRMV">Attention Mechanisms</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/domain-adaptation" class="sc-e69ac761-0 kmKRMV">Domain Adaptation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/evolutionary-algorithms" class="sc-e69ac761-0 kmKRMV">Evolutionary Algorithms</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/contrastive-learning" class="sc-e69ac761-0 kmKRMV">Contrastive Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/explainable-ai" class="sc-e69ac761-0 kmKRMV">Explainable AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/affective-ai" class="sc-e69ac761-0 kmKRMV">Affective AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/semantic-networks" class="sc-e69ac761-0 kmKRMV">Semantic Networks</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/data-augmentation" class="sc-e69ac761-0 kmKRMV">Data Augmentation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/convolutional-neural-networks" class="sc-e69ac761-0 kmKRMV">Convolutional Neural Networks</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/cognitive-computing" class="sc-e69ac761-0 kmKRMV">Cognitive Computing</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/end-to-end-learning" class="sc-e69ac761-0 kmKRMV">End-to-end Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/prompt-tuning" class="sc-e69ac761-0 kmKRMV">Prompt Tuning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/double-descent" class="sc-e69ac761-0 kmKRMV">Double Descent</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/model-drift" class="sc-e69ac761-0 kmKRMV">Model Drift</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/neural-radiance-fields" class="sc-e69ac761-0 kmKRMV">Neural Radiance Fields</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/regularization" class="sc-e69ac761-0 kmKRMV">Regularization</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/natural-language-querying" class="sc-e69ac761-0 kmKRMV">Natural Language Querying (NLQ)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/foundation-models" class="sc-e69ac761-0 kmKRMV">Foundation Models</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/forward-propagation" class="sc-e69ac761-0 kmKRMV">Forward Propagation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/f2-score" class="sc-e69ac761-0 kmKRMV">F2 Score</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-ethics" class="sc-e69ac761-0 kmKRMV">AI Ethics</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/transfer-learning" class="sc-e69ac761-0 kmKRMV">Transfer Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-alignment" class="sc-e69ac761-0 kmKRMV">AI Alignment</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/whisper-v3" class="sc-e69ac761-0 kmKRMV">Whisper v3</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/whisper-v2" class="sc-e69ac761-0 kmKRMV">Whisper v2</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/semi-structured-data" class="sc-e69ac761-0 kmKRMV">Semi-structured data</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-hallucinations" class="sc-e69ac761-0 kmKRMV">AI Hallucinations</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/emergent-behavior" class="sc-e69ac761-0 kmKRMV">Emergent Behavior</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/matplotlib" class="sc-e69ac761-0 kmKRMV">Matplotlib</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/numpy" class="sc-e69ac761-0 kmKRMV">NumPy</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/scikit-learn" class="sc-e69ac761-0 kmKRMV">Scikit-learn</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/scipy" class="sc-e69ac761-0 kmKRMV">SciPy</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/keras" class="sc-e69ac761-0 kmKRMV">Keras</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/tensorflow" class="sc-e69ac761-0 kmKRMV">TensorFlow</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/seaborn-python-package" class="sc-e69ac761-0 kmKRMV">Seaborn Python Package</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/pytorch" class="sc-e69ac761-0 kmKRMV">PyTorch</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/natural-language-toolkit-nltk" class="sc-e69ac761-0 kmKRMV">Natural Language Toolkit (NLTK)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/pandas" class="sc-e69ac761-0 kmKRMV">Pandas</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ego-4d" class="sc-e69ac761-0 kmKRMV">Ego 4D</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/the-pile" class="sc-e69ac761-0 kmKRMV">The Pile</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/common-crawl-datasets" class="sc-e69ac761-0 kmKRMV">Common Crawl Datasets</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/squad" class="sc-e69ac761-0 kmKRMV">SQuAD</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/intelligent-document-processing" class="sc-e69ac761-0 kmKRMV">Intelligent Document Processing</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/hyperparameter-tuning" class="sc-e69ac761-0 kmKRMV">Hyperparameter Tuning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/Markov-decision-process" class="sc-e69ac761-0 kmKRMV">Markov Decision Process</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/graph-neural-networks" class="sc-e69ac761-0 kmKRMV">Graph Neural Networks</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/neural-architecture-search" class="sc-e69ac761-0 kmKRMV">Neural Architecture Search</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ablation" class="sc-e69ac761-0 kmKRMV">Ablation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/knowledge-distillation" class="sc-e69ac761-0 kmKRMV">Knowledge Distillation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/model-interpretability" class="sc-e69ac761-0 iUnKGS">Model Interpretability</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/out-of-distribution-detection" class="sc-e69ac761-0 kmKRMV">Out-of-Distribution Detection</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/recurrent-neural-networks" class="sc-e69ac761-0 kmKRMV">Recurrent Neural Networks</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/active-learning" class="sc-e69ac761-0 kmKRMV">Active Learning (Machine Learning)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/imbalanced-data" class="sc-e69ac761-0 kmKRMV">Imbalanced Data</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/loss-function" class="sc-e69ac761-0 kmKRMV">Loss Function</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/unsupervised-learning" class="sc-e69ac761-0 kmKRMV">Unsupervised Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-and-big-data" class="sc-e69ac761-0 kmKRMV">AI and Big Data</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/adagrad" class="sc-e69ac761-0 kmKRMV">AdaGrad</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/clustering-algorithms" class="sc-e69ac761-0 kmKRMV">Clustering Algorithms</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/parametric-neural-networks%C2%A0" class="sc-e69ac761-0 kmKRMV">Parametric Neural Networks </a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/acoustic-models" class="sc-e69ac761-0 kmKRMV">Acoustic Models</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/articulatory-synthesis" class="sc-e69ac761-0 kmKRMV">Articulatory Synthesis</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/concatenative-synthesis" class="sc-e69ac761-0 kmKRMV">Concatenative Synthesis</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/grapheme-to-phoneme-conversion-g2p" class="sc-e69ac761-0 kmKRMV">Grapheme-to-Phoneme Conversion (G2P)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/homograph-disambiguation" class="sc-e69ac761-0 kmKRMV">Homograph Disambiguation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/neural-text-to-speech-ntts" class="sc-e69ac761-0 kmKRMV">Neural Text-to-Speech (NTTS)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/voice-cloning" class="sc-e69ac761-0 kmKRMV">Voice Cloning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/autoregressive-model" class="sc-e69ac761-0 kmKRMV">Autoregressive Model</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/candidate-sampling" class="sc-e69ac761-0 kmKRMV">Candidate Sampling</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/machine-learning-algorithmic-trading" class="sc-e69ac761-0 kmKRMV">Machine Learning in Algorithmic Trading</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/computational-creativity" class="sc-e69ac761-0 kmKRMV">Computational Creativity</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/context-aware-computing" class="sc-e69ac761-0 kmKRMV">Context-Aware Computing</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-emotion-recognition" class="sc-e69ac761-0 kmKRMV">AI Emotion Recognition</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/knowledge-representation-and-reasoning" class="sc-e69ac761-0 kmKRMV">Knowledge Representation and Reasoning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/metacognitive-learning-models" class="sc-e69ac761-0 kmKRMV">Metacognitive Learning Models </a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/synthetic-data-for-ai-training" class="sc-e69ac761-0 kmKRMV">Synthetic Data for AI Training</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-speech-enhancement" class="sc-e69ac761-0 kmKRMV">AI Speech Enhancement</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/counterfactual-explanations-in-ai" class="sc-e69ac761-0 kmKRMV">Counterfactual Explanations in AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/eco-friendly-ai" class="sc-e69ac761-0 kmKRMV">Eco-friendly AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/feature-store-for-machine-learning" class="sc-e69ac761-0 kmKRMV">Feature Store for Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/generative-teaching-networks" class="sc-e69ac761-0 kmKRMV">Generative Teaching Networks</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/human-centered-ai" class="sc-e69ac761-0 kmKRMV">Human-centered AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/metaheuristic-algorithms" class="sc-e69ac761-0 kmKRMV">Metaheuristic Algorithms</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/statistical-relational-learning" class="sc-e69ac761-0 kmKRMV">Statistical Relational Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/cognitive-architectures" class="sc-e69ac761-0 kmKRMV">Cognitive Architectures</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/computational-phenotyping" class="sc-e69ac761-0 kmKRMV">Computational Phenotyping</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/continuous-learning-systems" class="sc-e69ac761-0 kmKRMV">Continuous Learning Systems</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/deepfake-detection" class="sc-e69ac761-0 kmKRMV">Deepfake Detection</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/one-shot-learning" class="sc-e69ac761-0 kmKRMV">One-Shot Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/quantum-machine-learning-algorithms" class="sc-e69ac761-0 kmKRMV">Quantum Machine Learning Algorithms</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/self-healing-ai" class="sc-e69ac761-0 kmKRMV">Self-healing AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/semantic-search-algorithms" class="sc-e69ac761-0 kmKRMV">Semantic Search Algorithms</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/artificial-super-intelligence" class="sc-e69ac761-0 kmKRMV">Artificial Super Intelligence</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-guardrails" class="sc-e69ac761-0 kmKRMV">AI Guardrails</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/limited-memory-ai" class="sc-e69ac761-0 kmKRMV">Limited Memory AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/chatbots" class="sc-e69ac761-0 kmKRMV">Chatbots</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/diffusion" class="sc-e69ac761-0 kmKRMV">Diffusion</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/hidden-layer" class="sc-e69ac761-0 kmKRMV">Hidden Layer</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/instruction-tuning" class="sc-e69ac761-0 kmKRMV">Instruction Tuning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/objective-function" class="sc-e69ac761-0 kmKRMV">Objective Function</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/pretraining" class="sc-e69ac761-0 kmKRMV">Pretraining</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/symbolic-ai" class="sc-e69ac761-0 kmKRMV">Symbolic AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/auto-classification" 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-q0kznr:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-q0kznr:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-q0kznr.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><style data-emotion="css ak4akz">.css-ak4akz{display:-webkit-inline-box;display:-webkit-inline-flex;display:-ms-inline-flexbox;display:inline-flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;position:relative;box-sizing:border-box;-webkit-tap-highlight-color:transparent;background-color:transparent;outline:0;border:0;margin:0;border-radius:0;padding:0;cursor:pointer;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;vertical-align:middle;-moz-appearance:none;-webkit-appearance:none;-webkit-text-decoration:none;text-decoration:none;color:inherit;font-family:var(--font-inter, sans-serif);font-size:0.875rem;line-height:1.75rem;font-weight:700;text-transform:uppercase;min-width:64px;padding:6px 8px;border-radius:4px;-webkit-transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media print{.css-ak4akz{-webkit-print-color-adjust:exact;color-adjust:exact;}}.css-ak4akz:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-ak4akz:hover{background-color:transparent;}}.css-ak4akz.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-ak4akz::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-ak4akz:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-ak4akz:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-ak4akz.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><button class="MuiButtonBase-root MuiButton-root MuiButton-text MuiButton-textPrimary MuiButton-sizeMedium MuiButton-textSizeMedium MuiButton-colorPrimary MuiButton-root MuiButton-text MuiButton-textPrimary MuiButton-sizeMedium MuiButton-textSizeMedium MuiButton-colorPrimary sc-d74559df-0 iotBFW css-ak4akz" tabindex="0" type="button" href="" target="_self"><span class="sc-b323b31-0 btXZGI button-label" display="inline-flex">B</span></button></li><li class="sc-ace17a57-0 goWpow"><style data-emotion="css q0kznr">.css-q0kznr{font-family:var(--font-inter, sans-serif);font-size:0.875rem;line-height:1.75rem;font-weight:700;text-transform:uppercase;min-width:64px;padding:6px 8px;border-radius:4px;-webkit-transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-q0kznr:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-q0kznr:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-q0kznr.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><style data-emotion="css ak4akz">.css-ak4akz{display:-webkit-inline-box;display:-webkit-inline-flex;display:-ms-inline-flexbox;display:inline-flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;position:relative;box-sizing:border-box;-webkit-tap-highlight-color:transparent;background-color:transparent;outline:0;border:0;margin:0;border-radius:0;padding:0;cursor:pointer;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;vertical-align:middle;-moz-appearance:none;-webkit-appearance:none;-webkit-text-decoration:none;text-decoration:none;color:inherit;font-family:var(--font-inter, sans-serif);font-size:0.875rem;line-height:1.75rem;font-weight:700;text-transform:uppercase;min-width:64px;padding:6px 8px;border-radius:4px;-webkit-transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media print{.css-ak4akz{-webkit-print-color-adjust:exact;color-adjust:exact;}}.css-ak4akz:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-ak4akz:hover{background-color:transparent;}}.css-ak4akz.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-ak4akz::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-ak4akz:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-ak4akz:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-ak4akz.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><button class="MuiButtonBase-root MuiButton-root MuiButton-text MuiButton-textPrimary MuiButton-sizeMedium MuiButton-textSizeMedium MuiButton-colorPrimary MuiButton-root MuiButton-text MuiButton-textPrimary MuiButton-sizeMedium MuiButton-textSizeMedium MuiButton-colorPrimary sc-d74559df-0 iotBFW css-ak4akz" tabindex="0" type="button" href="" target="_self"><span class="sc-b323b31-0 btXZGI button-label" display="inline-flex">C</span></button></li><li class="sc-ace17a57-0 goWpow"><style data-emotion="css q0kznr">.css-q0kznr{font-family:var(--font-inter, sans-serif);font-size:0.875rem;line-height:1.75rem;font-weight:700;text-transform:uppercase;min-width:64px;padding:6px 8px;border-radius:4px;-webkit-transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-q0kznr:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-q0kznr:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-q0kznr.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><style data-emotion="css ak4akz">.css-ak4akz{display:-webkit-inline-box;display:-webkit-inline-flex;display:-ms-inline-flexbox;display:inline-flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;position:relative;box-sizing:border-box;-webkit-tap-highlight-color:transparent;background-color:transparent;outline:0;border:0;margin:0;border-radius:0;padding:0;cursor:pointer;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;vertical-align:middle;-moz-appearance:none;-webkit-appearance:none;-webkit-text-decoration:none;text-decoration:none;color:inherit;font-family:var(--font-inter, sans-serif);font-size:0.875rem;line-height:1.75rem;font-weight:700;text-transform:uppercase;min-width:64px;padding:6px 8px;border-radius:4px;-webkit-transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media print{.css-ak4akz{-webkit-print-color-adjust:exact;color-adjust:exact;}}.css-ak4akz:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-ak4akz:hover{background-color:transparent;}}.css-ak4akz.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-ak4akz::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-ak4akz:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-ak4akz:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-ak4akz.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><button class="MuiButtonBase-root 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-q0kznr:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-q0kznr:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-q0kznr.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><style data-emotion="css 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media print{.css-ak4akz{-webkit-print-color-adjust:exact;color-adjust:exact;}}.css-ak4akz:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-ak4akz:hover{background-color:transparent;}}.css-ak4akz.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-ak4akz::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-ak4akz:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-ak4akz:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-ak4akz.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><button class="MuiButtonBase-root 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-q0kznr:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-q0kznr:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-q0kznr.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><style data-emotion="css 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media print{.css-ak4akz{-webkit-print-color-adjust:exact;color-adjust:exact;}}.css-ak4akz:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-ak4akz:hover{background-color:transparent;}}.css-ak4akz.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-ak4akz::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-ak4akz:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-ak4akz:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-ak4akz.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><button class="MuiButtonBase-root 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-q0kznr:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-q0kznr:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-q0kznr.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><style data-emotion="css 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media print{.css-ak4akz{-webkit-print-color-adjust:exact;color-adjust:exact;}}.css-ak4akz:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-ak4akz:hover{background-color:transparent;}}.css-ak4akz.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-ak4akz::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-ak4akz:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-ak4akz:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-ak4akz.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><button class="MuiButtonBase-root 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media print{.css-ak4akz{-webkit-print-color-adjust:exact;color-adjust:exact;}}.css-ak4akz:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-ak4akz:hover{background-color:transparent;}}.css-ak4akz.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-ak4akz::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-ak4akz:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-ak4akz:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-ak4akz.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><button class="MuiButtonBase-root 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;border-radius:4px;box-sizing:content-box;padding:1px;}.css-q0kznr:hover{color:#ffffff;-webkit-text-decoration:underline;text-decoration:underline;background-color:transparent;}.css-q0kznr:focus-visible{color:#ffffff;-webkit-text-decoration:none;text-decoration:none;border-radius:4px;outline:2px solid #687EF7;outline-offset:3px;}.css-q0kznr.Mui-disabled{color:#96A2FF;opacity:0.5;}</style><style data-emotion="css 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,box-shadow 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-ak4akz::-moz-focus-inner{border-style:none;}.css-ak4akz.Mui-disabled{pointer-events:none;cursor:default;}@media 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0ms,border-color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms,color 250ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;color:#00E062;min-width:0;text-transform:capitalize;font-weight:600;border-radius:4px;font-size:1rem;padding-left:2rem;padding-right:2rem;-webkit-transition:unset;transition:unset;white-space:nowrap;position:relative;font-size:1rem;line-height:2;padding-left:1.25rem;padding-right:1.25rem;color:#79AFFA;padding:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-q0kznr:hover{-webkit-text-decoration:none;text-decoration:none;background-color:rgba(0, 224, 98, 0.04);}@media (hover: none){.css-q0kznr:hover{background-color:transparent;}}.css-q0kznr.Mui-disabled{color:rgba(0, 0, 0, 0.26);}.css-q0kznr::before{content:"";position:absolute;width:100%;height:100%;top:-1px;left:-1px;z-index:0;opacity:0;-webkit-transition:opacity 100ms ease-in-out,background-position 400ms ease-in-out;transition:opacity 100ms ease-in-out,background-position 400ms 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href="/ai-glossary/ai-and-education" class="sc-e69ac761-0 dsCZKx">AI and Education</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-and-medicine" class="sc-e69ac761-0 dsCZKx">AI and Medicine</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-voice-transfer" class="sc-e69ac761-0 dsCZKx">AI Voice Transfer</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/approximate-dynamic-programming" class="sc-e69ac761-0 dsCZKx">Approximate Dynamic Programming</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/adversarial-machine-learning" class="sc-e69ac761-0 dsCZKx">Adversarial Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/alphago-zero" class="sc-e69ac761-0 dsCZKx">AlphaGo Zero</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-hardware" class="sc-e69ac761-0 dsCZKx">AI Hardware</a><a 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class="sc-e69ac761-0 dsCZKx">AI Lifecycle Management</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-literacy" class="sc-e69ac761-0 dsCZKx">AI Literacy</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-monitoring" class="sc-e69ac761-0 dsCZKx">AI Monitoring</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-oversight" class="sc-e69ac761-0 dsCZKx">AI Oversight</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-privacy" class="sc-e69ac761-0 dsCZKx">AI Privacy</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-prototyping" class="sc-e69ac761-0 dsCZKx">AI Prototyping</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-regulation" class="sc-e69ac761-0 dsCZKx">AI Regulation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-resilience" class="sc-e69ac761-0 dsCZKx">AI Resilience</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-interpretability" class="sc-e69ac761-0 dsCZKx">AI Interpretability</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/attention-mechanisms" class="sc-e69ac761-0 dsCZKx">Attention Mechanisms</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/affective-ai" class="sc-e69ac761-0 dsCZKx">Affective AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-ethics" class="sc-e69ac761-0 dsCZKx">AI Ethics</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-alignment" class="sc-e69ac761-0 dsCZKx">AI Alignment</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-hallucinations" class="sc-e69ac761-0 dsCZKx">AI Hallucinations</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ablation" class="sc-e69ac761-0 dsCZKx">Ablation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/active-learning" class="sc-e69ac761-0 dsCZKx">Active Learning (Machine Learning)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-and-big-data" class="sc-e69ac761-0 dsCZKx">AI and Big Data</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/adagrad" class="sc-e69ac761-0 dsCZKx">AdaGrad</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/acoustic-models" class="sc-e69ac761-0 dsCZKx">Acoustic Models</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/articulatory-synthesis" class="sc-e69ac761-0 dsCZKx">Articulatory Synthesis</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/autoregressive-model" class="sc-e69ac761-0 dsCZKx">Autoregressive Model</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-emotion-recognition" class="sc-e69ac761-0 dsCZKx">AI Emotion Recognition</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-speech-enhancement" class="sc-e69ac761-0 dsCZKx">AI Speech Enhancement</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/artificial-super-intelligence" class="sc-e69ac761-0 dsCZKx">Artificial Super Intelligence</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-guardrails" class="sc-e69ac761-0 dsCZKx">AI Guardrails</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/auto-classification" class="sc-e69ac761-0 dsCZKx">Auto Classification</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/association-rule-learning" class="sc-e69ac761-0 dsCZKx">Association Rule Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/autoencoder" class="sc-e69ac761-0 dsCZKx">Autoencoder</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/accuracy" class="sc-e69ac761-0 dsCZKx">Accuracy in Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-detection" class="sc-e69ac761-0 dsCZKx">AI Detection</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-robustness" class="sc-e69ac761-0 dsCZKx">AI Robustness</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-safety" class="sc-e69ac761-0 dsCZKx">AI Safety</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-scalability" class="sc-e69ac761-0 dsCZKx">AI Scalability</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-simulation" class="sc-e69ac761-0 dsCZKx">AI Simulation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-standards" class="sc-e69ac761-0 dsCZKx">AI Standards</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-steering" class="sc-e69ac761-0 dsCZKx">AI Steering</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ai-transparency" class="sc-e69ac761-0 dsCZKx">AI Transparency</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/augmented-intelligence" class="sc-e69ac761-0 dsCZKx">Augmented Intelligence</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/applications" class="sc-e69ac761-0 dsCZKx">Applications</a></li><li data-letter="B" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">B</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/benchmarking" class="sc-e69ac761-0 dsCZKx">Benchmarking</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/batch-gradient-descent" class="sc-e69ac761-0 dsCZKx">Batch Gradient Descent</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/backpropagation" class="sc-e69ac761-0 dsCZKx">Backpropagation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/bayesian-machine-learning" class="sc-e69ac761-0 dsCZKx">Bayesian Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/bert" class="sc-e69ac761-0 dsCZKx">BERT</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/binary-classification-ai" class="sc-e69ac761-0 dsCZKx">Binary Classification AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/beam-search-algorithm" class="sc-e69ac761-0 dsCZKx">Beam Search Algorithm</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/bias-variance-tradeoff" class="sc-e69ac761-0 dsCZKx">Bias-Variance Tradeoff</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/boosting" class="sc-e69ac761-0 dsCZKx">Boosting in Machine Learning</a></li><li data-letter="C" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">C</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/chess-bots" class="sc-e69ac761-0 dsCZKx">Chess bots</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/chatgpt" class="sc-e69ac761-0 dsCZKx">ChatGPT</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/cure-algorithm" class="sc-e69ac761-0 dsCZKx">CURE Algorithm</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/curse-of-dimensionality" class="sc-e69ac761-0 dsCZKx">Curse of Dimensionality</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/classification" class="sc-e69ac761-0 dsCZKx">Classification</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/cognitive-map" class="sc-e69ac761-0 dsCZKx">Cognitive Map</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/central-processing-unit-cpu" class="sc-e69ac761-0 dsCZKx">Central Processing Unit (CPU)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/conditional-variational-autoencoders" class="sc-e69ac761-0 dsCZKx">Conditional Variational Autoencoders</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/conversational-ai" class="sc-e69ac761-0 dsCZKx">Conversational AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/causal-inference" class="sc-e69ac761-0 dsCZKx">Causal Inference</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/capsule-neural-network" class="sc-e69ac761-0 dsCZKx">Capsule Neural Network</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/contrastive-learning" class="sc-e69ac761-0 dsCZKx">Contrastive Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/convolutional-neural-networks" class="sc-e69ac761-0 dsCZKx">Convolutional Neural Networks</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/cognitive-computing" class="sc-e69ac761-0 dsCZKx">Cognitive Computing</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/common-crawl-datasets" class="sc-e69ac761-0 dsCZKx">Common Crawl Datasets</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/clustering-algorithms" class="sc-e69ac761-0 dsCZKx">Clustering Algorithms</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/concatenative-synthesis" class="sc-e69ac761-0 dsCZKx">Concatenative Synthesis</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/candidate-sampling" class="sc-e69ac761-0 dsCZKx">Candidate Sampling</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/computational-creativity" class="sc-e69ac761-0 dsCZKx">Computational Creativity</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/context-aware-computing" class="sc-e69ac761-0 dsCZKx">Context-Aware Computing</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/counterfactual-explanations-in-ai" class="sc-e69ac761-0 dsCZKx">Counterfactual Explanations in AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/cognitive-architectures" class="sc-e69ac761-0 dsCZKx">Cognitive Architectures</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/computational-phenotyping" class="sc-e69ac761-0 dsCZKx">Computational Phenotyping</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/continuous-learning-systems" class="sc-e69ac761-0 dsCZKx">Continuous Learning Systems</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/chatbots" class="sc-e69ac761-0 dsCZKx">Chatbots</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/composite-ai" class="sc-e69ac761-0 dsCZKx">Composite AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/computational-lingustics" class="sc-e69ac761-0 dsCZKx">Computational Linguistics</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/computational-semantics" class="sc-e69ac761-0 dsCZKx">Computational Semantics</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/collaborative-filtering" class="sc-e69ac761-0 dsCZKx">Collaborative Filtering</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/corpus" class="sc-e69ac761-0 dsCZKx">Corpus in NLP</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/confirmation-bias" class="sc-e69ac761-0 dsCZKx">Confirmation Bias in Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/confidence-intervals" class="sc-e69ac761-0 dsCZKx">Confidence Intervals in Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/cross-validation" class="sc-e69ac761-0 dsCZKx">Cross Validation in Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/clustering" class="sc-e69ac761-0 dsCZKx">Clustering in Machine Learning</a></li><li data-letter="D" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">D</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/dall-e" class="sc-e69ac761-0 dsCZKx">Dall-E</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/distilbert" class="sc-e69ac761-0 dsCZKx">DistilBERT</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/dimensionality-reduction" class="sc-e69ac761-0 dsCZKx">Dimensionality Reduction</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/deep-reinforcement-learning" class="sc-e69ac761-0 dsCZKx">Deep Reinforcement Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/diffusion-model" class="sc-e69ac761-0 dsCZKx">Diffusion Models</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/deep-learning" class="sc-e69ac761-0 dsCZKx">Deep Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/datasets" class="sc-e69ac761-0 dsCZKx">Datasets</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/data-labeling" class="sc-e69ac761-0 dsCZKx">Data Labeling</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/differential-privacy" class="sc-e69ac761-0 dsCZKx">Differential Privacy</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/data-poisoning" class="sc-e69ac761-0 dsCZKx">Data Poisoning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/domain-adaptation" class="sc-e69ac761-0 dsCZKx">Domain Adaptation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/data-augmentation" class="sc-e69ac761-0 dsCZKx">Data Augmentation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/double-descent" class="sc-e69ac761-0 dsCZKx">Double Descent</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/deepfake-detection" class="sc-e69ac761-0 dsCZKx">Deepfake Detection</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/diffusion" class="sc-e69ac761-0 dsCZKx">Diffusion</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/data-drift" class="sc-e69ac761-0 dsCZKx">Data Drift</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/data-scarcity" class="sc-e69ac761-0 dsCZKx">Data Scarcity</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/decision-tree" class="sc-e69ac761-0 dsCZKx">Decision Tree</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/decision-intelligence" class="sc-e69ac761-0 dsCZKx">Decision Intelligence</a></li><li data-letter="E" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">E</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/expectation-maximization" class="sc-e69ac761-0 dsCZKx">Expectation Maximization</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/embedding-layer" class="sc-e69ac761-0 dsCZKx">Embedding Layer</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/evolutionary-algorithms" class="sc-e69ac761-0 dsCZKx">Evolutionary Algorithms</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/explainable-ai" class="sc-e69ac761-0 dsCZKx">Explainable AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/end-to-end-learning" class="sc-e69ac761-0 dsCZKx">End-to-end Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/emergent-behavior" class="sc-e69ac761-0 dsCZKx">Emergent Behavior</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ego-4d" class="sc-e69ac761-0 dsCZKx">Ego 4D</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/eco-friendly-ai" class="sc-e69ac761-0 dsCZKx">Eco-friendly AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ensemble-learning" class="sc-e69ac761-0 dsCZKx">Ensemble Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/entropy" class="sc-e69ac761-0 dsCZKx">Entropy in Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/epoch" class="sc-e69ac761-0 dsCZKx">Epoch in Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ethical-ai" class="sc-e69ac761-0 dsCZKx">Ethical AI</a></li><li data-letter="F" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">F</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/flajolet-martin-algorithm" class="sc-e69ac761-0 dsCZKx">Flajolet-Martin Algorithm</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/feedforward-neural-network" class="sc-e69ac761-0 dsCZKx">Feedforward Neural Network</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/fine-tuning-deep-learning" class="sc-e69ac761-0 dsCZKx">Fine Tuning in Deep Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/fundamentals" class="sc-e69ac761-0 dsCZKx">Fundamentals</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/f1-score-machine-learning" class="sc-e69ac761-0 dsCZKx">F1 Score in Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/foundation-models" class="sc-e69ac761-0 dsCZKx">Foundation Models</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/forward-propagation" class="sc-e69ac761-0 dsCZKx">Forward Propagation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/f2-score" class="sc-e69ac761-0 dsCZKx">F2 Score</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/feature-store-for-machine-learning" class="sc-e69ac761-0 dsCZKx">Feature Store for Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/few-shot-learning" class="sc-e69ac761-0 dsCZKx">Few Shot Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/federated-learning" class="sc-e69ac761-0 dsCZKx">Federated Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/feature-learning" class="sc-e69ac761-0 dsCZKx">Feature Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/feature-selection" class="sc-e69ac761-0 dsCZKx">Feature Selection</a></li><li data-letter="G" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">G</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/gradient-clipping" class="sc-e69ac761-0 dsCZKx">Gradient Clipping</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/generative-adversarial-networks" class="sc-e69ac761-0 dsCZKx">Generative Adversarial Networks (GANs)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/gaussian-processes" class="sc-e69ac761-0 dsCZKx">Gaussian Processes</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/gated-recurrent-unit" class="sc-e69ac761-0 dsCZKx">Gated Recurrent Unit</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/grounding" class="sc-e69ac761-0 dsCZKx">Grounding</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/gradient-boosting-machines" class="sc-e69ac761-0 dsCZKx">Gradient Boosting Machines (GBMs)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/graphics-processing-unit-gpu" class="sc-e69ac761-0 dsCZKx">Graphics Processing Unit (GPU)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/google-bard" class="sc-e69ac761-0 dsCZKx">Google's Bard</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/gradient-scaling" class="sc-e69ac761-0 dsCZKx">Gradient Scaling</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/generative-ai" class="sc-e69ac761-0 dsCZKx">Generative AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/graph-neural-networks" class="sc-e69ac761-0 dsCZKx">Graph Neural Networks</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/grapheme-to-phoneme-conversion-g2p" class="sc-e69ac761-0 dsCZKx">Grapheme-to-Phoneme Conversion (G2P)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/generative-teaching-networks" class="sc-e69ac761-0 dsCZKx">Generative Teaching Networks</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/genetic-algorithms" class="sc-e69ac761-0 dsCZKx">Genetic Algorithms in AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/ground-truth" class="sc-e69ac761-0 dsCZKx">Ground Truth in Machine Learning</a></li><li data-letter="H" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">H</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/hyperparameters" class="sc-e69ac761-0 dsCZKx">Hyperparameters</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/hidden-markov-models" class="sc-e69ac761-0 dsCZKx">Hidden Markov Models (HMMs)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/hooke-jeeves-algorithm" class="sc-e69ac761-0 dsCZKx">Hooke-Jeeves Algorithm</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/hyperparameter-tuning" class="sc-e69ac761-0 dsCZKx">Hyperparameter Tuning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/homograph-disambiguation" class="sc-e69ac761-0 dsCZKx">Homograph Disambiguation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/human-centered-ai" class="sc-e69ac761-0 dsCZKx">Human-centered AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/hidden-layer" class="sc-e69ac761-0 dsCZKx">Hidden Layer</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/human-in-the-loop-ai" class="sc-e69ac761-0 dsCZKx">Human-in-the-Loop AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/hybrid-ai" class="sc-e69ac761-0 dsCZKx">Hybrid AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/human-augmentation-with-ai" class="sc-e69ac761-0 dsCZKx">Human Augmentation with AI</a></li><li data-letter="I" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">I</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/inference-engine" class="sc-e69ac761-0 dsCZKx">Inference Engine</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/intelligent-document-processing" class="sc-e69ac761-0 dsCZKx">Intelligent Document Processing</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/imbalanced-data" class="sc-e69ac761-0 dsCZKx">Imbalanced Data</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/instruction-tuning" class="sc-e69ac761-0 dsCZKx">Instruction Tuning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/incremental-learning" class="sc-e69ac761-0 dsCZKx">Incremental Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/information-retrieval" class="sc-e69ac761-0 dsCZKx">Information Retrieval</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/image-recognition" class="sc-e69ac761-0 dsCZKx">Image Recognition</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/imagenet" class="sc-e69ac761-0 dsCZKx">ImageNet</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/inductive-bias" class="sc-e69ac761-0 dsCZKx">Inductive Bias</a></li><li data-letter="K" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">K</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/k-shingles" class="sc-e69ac761-0 dsCZKx">k-Shingles</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/keyphrase-extraction" class="sc-e69ac761-0 dsCZKx">Keyphrase Extraction</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/keras" class="sc-e69ac761-0 dsCZKx">Keras</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/knowledge-distillation" class="sc-e69ac761-0 dsCZKx">Knowledge Distillation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/knowledge-representation-and-reasoning" class="sc-e69ac761-0 dsCZKx">Knowledge Representation and Reasoning</a></li><li data-letter="L" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">L</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/llama-2" class="sc-e69ac761-0 dsCZKx">Llama 2</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/llm-collection" class="sc-e69ac761-0 dsCZKx">LLM Collection</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/latent-dirichlet-allocation" class="sc-e69ac761-0 dsCZKx">Latent Dirichlet Allocation (LDA)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/large-language-model" class="sc-e69ac761-0 dsCZKx">Large Language Model (LLM)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/loss-function" class="sc-e69ac761-0 dsCZKx">Loss Function</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/limited-memory-ai" class="sc-e69ac761-0 dsCZKx">Limited Memory AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/learning-rate" class="sc-e69ac761-0 dsCZKx">Learning Rate</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/learning-to-rank" class="sc-e69ac761-0 dsCZKx">Learning To Rank</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/logits" class="sc-e69ac761-0 dsCZKx">Logits</a></li><li data-letter="M" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 fvIpti">M</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/midjourney-image-generation" class="sc-e69ac761-0 dsCZKx">Midjourney (Image Generation)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/mistral" class="sc-e69ac761-0 dsCZKx">Mistral</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/mixture-of-experts" class="sc-e69ac761-0 dsCZKx">Mixture of Experts</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/multimodal-ai" class="sc-e69ac761-0 dsCZKx">Multimodal AI</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/multimodal-learning" class="sc-e69ac761-0 dsCZKx">Multimodal Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/machine-learning" class="sc-e69ac761-0 dsCZKx">Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/multimodal-aI-models-and-modalities" class="sc-e69ac761-0 dsCZKx">Multimodal AI Models and Modalities</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/mamba" class="sc-e69ac761-0 dsCZKx">Mamba</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/models" class="sc-e69ac761-0 dsCZKx">Models</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/machine-learning-bias" class="sc-e69ac761-0 dsCZKx">Machine Learning Bias</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/machine-learning-life-cycle-management" class="sc-e69ac761-0 dsCZKx">Machine Learning Life Cycle Management</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/machine-translation" class="sc-e69ac761-0 dsCZKx">Machine Translation</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/mlops" class="sc-e69ac761-0 dsCZKx">MLOps</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/monte-carlo-learning" class="sc-e69ac761-0 dsCZKx">Monte Carlo Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/multi-task-learning" class="sc-e69ac761-0 dsCZKx">Multi-task Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/machine-learning-neuron" class="sc-e69ac761-0 dsCZKx">Machine Learning Neuron</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/machine-learning-preprocessing" class="sc-e69ac761-0 dsCZKx">Machine Learning Preprocessing</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/model-drift" class="sc-e69ac761-0 dsCZKx">Model Drift</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/matplotlib" class="sc-e69ac761-0 dsCZKx">Matplotlib</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/Markov-decision-process" class="sc-e69ac761-0 dsCZKx">Markov Decision Process</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/model-interpretability" class="sc-e69ac761-0 ezFGlW">Model Interpretability</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/machine-learning-algorithmic-trading" class="sc-e69ac761-0 dsCZKx">Machine Learning in Algorithmic Trading</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/metacognitive-learning-models" class="sc-e69ac761-0 dsCZKx">Metacognitive Learning Models </a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/metaheuristic-algorithms" class="sc-e69ac761-0 dsCZKx">Metaheuristic Algorithms</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/multitask-prompt-tuning" class="sc-e69ac761-0 dsCZKx">Multitask Prompt Tuning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/multi-agent-systems" class="sc-e69ac761-0 dsCZKx">Multi-Agent Systems</a></li><li data-letter="N" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">N</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/natural-language-processing" class="sc-e69ac761-0 dsCZKx">Natural Language Processing (NLP)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/natural-language-generation" class="sc-e69ac761-0 dsCZKx">Natural Language Generation (NLG)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/natural-language-understanding" class="sc-e69ac761-0 dsCZKx">Natural Language Understanding (NLU)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/neuralink" class="sc-e69ac761-0 dsCZKx">Neuralink</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/naive-bayes-classifier" class="sc-e69ac761-0 dsCZKx">Naive Bayes Classifier</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/neural-radiance-fields" class="sc-e69ac761-0 dsCZKx">Neural Radiance Fields</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/natural-language-querying" class="sc-e69ac761-0 dsCZKx">Natural Language Querying (NLQ)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/numpy" class="sc-e69ac761-0 dsCZKx">NumPy</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/natural-language-toolkit-nltk" class="sc-e69ac761-0 dsCZKx">Natural Language Toolkit (NLTK)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/neural-architecture-search" class="sc-e69ac761-0 dsCZKx">Neural Architecture Search</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/neural-text-to-speech-ntts" class="sc-e69ac761-0 dsCZKx">Neural Text-to-Speech (NTTS)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/named-entity-recognition" class="sc-e69ac761-0 dsCZKx">Named Entity Recognition</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/neural-style-transfer" class="sc-e69ac761-0 dsCZKx">Neural Style Transfer</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/neuroevolution" class="sc-e69ac761-0 dsCZKx">Neuroevolution</a></li><li data-letter="O" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">O</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/online-gradient-descent" class="sc-e69ac761-0 dsCZKx">Online Gradient Descent</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/overfitting-underfitting" class="sc-e69ac761-0 dsCZKx">Overfitting and Underfitting</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/openai-whisper" class="sc-e69ac761-0 dsCZKx">OpenAI Whisper</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/openai-sora" class="sc-e69ac761-0 dsCZKx">OpenAI Sora</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/out-of-distribution-detection" class="sc-e69ac761-0 dsCZKx">Out-of-Distribution Detection</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/one-shot-learning" class="sc-e69ac761-0 dsCZKx">One-Shot Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/objective-function" class="sc-e69ac761-0 dsCZKx">Objective Function</a></li><li data-letter="P" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">P</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/prompt-engineering" class="sc-e69ac761-0 dsCZKx">Prompt Engineering</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/prompt-chaining" class="sc-e69ac761-0 dsCZKx">Prompt Chaining</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/perceptron" class="sc-e69ac761-0 dsCZKx">Perceptron</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/precision-and-recall" class="sc-e69ac761-0 dsCZKx">Precision and Recall</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/packages-glossary" class="sc-e69ac761-0 dsCZKx">Packages</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/pooling-machine-learning" class="sc-e69ac761-0 dsCZKx">Pooling (Machine Learning)</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/principal-component-analysis" class="sc-e69ac761-0 dsCZKx">Principal Component Analysis</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/probabilistic-models-in-machine-learning" class="sc-e69ac761-0 dsCZKx">Probabilistic Models in Machine Learning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/prompt-tuning" class="sc-e69ac761-0 dsCZKx">Prompt Tuning</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/pytorch" class="sc-e69ac761-0 dsCZKx">PyTorch</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/pandas" class="sc-e69ac761-0 dsCZKx">Pandas</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/parametric-neural-networks%C2%A0" class="sc-e69ac761-0 dsCZKx">Parametric Neural Networks </a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/pretraining" class="sc-e69ac761-0 dsCZKx">Pretraining</a><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/part-of-speech-tagging" class="sc-e69ac761-0 dsCZKx">Part-of-Speech Tagging</a></li><li data-letter="Q" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" font-weight="medium" class="sc-b323b31-0 jgUCVJ">Q</span></div><a rel="" target="" font-size="textLg" font-weight="medium" href="/ai-glossary/quantum-machine-learning-algorithms" class="sc-e69ac761-0 dsCZKx">Quantum Machine Learning Algorithms</a></li><li data-letter="R" class="sc-ace17a57-0 eTCxuy"><div width="100%" class="sc-6293d692-0 jWSoNY"><span font-size="textLg" 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Deepgram</span></div></div></div></footer></div></div><script id="__NEXT_DATA__" type="application/json">{"props":{"pageProps":{"slug":["model-interpretability"],"pageData":{"templateGlossary":{"__typename":"TemplateGlossaryRecord","id":"OJR0The7S7-G2DBMKqiBcA","seo":null,"slug":"model-interpretability","title":"Model Interpretability","categoryPage":false,"excerpt":{"__typename":"TemplateGlossaryModelExcerptField","value":{"schema":"dast","document":{"type":"root","children":[{"type":"paragraph","children":[{"type":"span","value":"This article delves deep into the essence of model interpretability, shining a light on its crucial role across various sectors, from healthcare to finance."}]}]}}},"body":{"__typename":"TemplateGlossaryModelBodyField","blocks":[],"links":[{"__typename":"ComponentImageRecord","id":"IMVv3CVZR7at3ZHNX-hR9w","caption":"An example of interpretable embeddings comes in this early form of word vectorization, in which every entry corresponds to the probability that two words will appear in the same document. To learn more, click [here](https://deepgram.com/learn/word-vectorization-how-llms-learned-to-write-like-humans#blog-detail-hero).","imageDesktop":{"__typename":"FileField","id":"GNGv-1xTQR6OXttyBmDwmg","title":null,"filename":"screen-shot-2024-04-10-at-10-14-30-am.png","size":158331,"alt":null,"url":"https://www.datocms-assets.com/96965/1712769285-screen-shot-2024-04-10-at-10-14-30-am.png","width":1996,"height":304},"imageMobile":null,"link":""},{"__typename":"ComponentImageRecord","id":"Z5su9I_yQ16q7vzUlugSsg","caption":"Ever wanted to learn how to build an LLM Chatbot from scratch? Check out [this article](https://deepgram.com/learn/building-an-end-to-end-llm-chatbot) to learn how!","imageDesktop":{"__typename":"FileField","id":"aAdLHPi7SYKaLLoWjBaYpg","title":null,"filename":"screen-shot-2024-06-16-at-2-09-13-am.png","size":1528630,"alt":null,"url":"https://www.datocms-assets.com/96965/1718528956-screen-shot-2024-06-16-at-2-09-13-am.png","width":1472,"height":950},"imageMobile":null,"link":""},{"__typename":"ComponentImageRecord","id":"DLj1WuxXReqbXBdxGnJoCg","caption":"The Massive Multitask Language Understanding (MMLU) benchmark is like the SAT for AI models. It's one of the best methods we have to measure the quality of new AI models. Learn more about it in [this article](https://deepgram.com/learn/mmlu-llm-benchmark-guide)!","imageDesktop":{"__typename":"FileField","id":"Apw80VNSRm6FNLrmp6QN6w","title":null,"filename":"screen-shot-2024-06-16-at-2-11-22-am.png","size":1195249,"alt":null,"url":"https://www.datocms-assets.com/96965/1718529084-screen-shot-2024-06-16-at-2-11-22-am.png","width":1336,"height":710},"imageMobile":null,"link":""},{"__typename":"ComponentImageRecord","id":"OcUPVLYOTdiOH90vXDPFbA","caption":"Mixture of Experts (MoE) is a method that presents an efficient approach to dramatically increasing a model’s capabilities without introducing a proportional amount of computational overhead. To learn more, check out [this guide](https://deepgram.com/learn/mixture-of-experts-ml-model-guide)!","imageDesktop":{"__typename":"FileField","id":"cnmz5FWiQv2S--QFhqNL-g","title":null,"filename":"screen-shot-2024-06-16-at-2-06-22-am.png","size":2233720,"alt":null,"url":"https://www.datocms-assets.com/96965/1718528786-screen-shot-2024-06-16-at-2-06-22-am.png","width":1512,"height":788},"imageMobile":null,"link":""}],"value":{"schema":"dast","document":{"type":"root","children":[{"type":"paragraph","children":[{"type":"span","value":"With a staggering 91% of data professionals emphasizing the importance of interpretability for business stakeholders, it's clear that understanding the \"why\" behind model predictions isn't just a preference—it's a necessity. "}]},{"type":"paragraph","children":[{"type":"span","value":"This article delves deep into the essence of model interpretability, shining a light on its crucial role across various sectors, from healthcare to finance. You'll discover how interpretability acts as the linchpin in balancing model complexity with transparency, ensuring fairness, and adhering to regulatory demands. But more importantly, how does it foster trust among end-users? Let's embark on this exploration together, unearthing the significance of making the complex understandable. "}]},{"type":"heading","level":2,"children":[{"type":"span","value":"What is Model Interpretability"}]},{"type":"paragraph","children":[{"type":"span","value":"Interpretability in machine learning signifies the extent to which a human can understand and trust the decisions made by a model. It embodies the crucial bridge linking sophisticated computational models with their practical applications, where trust and transparency reign supreme. Consider the following facets of model interpretability:"}]},{"type":"list","style":"bulleted","children":[{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Healthcare and Life Sciences:"},{"type":"span","value":" Interpretability holds paramount importance in healthcare and life sciences. Here, decisions can quite literally mean the difference between life and death. Understanding the rationale behind a model's prediction ensures that healthcare professionals can trust these tools, leading to better patient outcomes. To learn more about healthcare and life sciences, click "},{"url":"https://deepgram.com/learn/the-future-of-healthcare-enhancing-patient-experience-with-voice-enabled-ai-copil","type":"link","children":[{"type":"span","value":"here"}]},{"type":"span","value":"."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Complexity vs. Interpretability:"},{"type":"span","value":" A delicate balance exists between a model's complexity and its interpretability. As algorithms become more intricate, comprehending their decision-making processes becomes more challenging. This tug-of-war necessitates a careful approach to design models that are both powerful and understandable."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Ensuring Fairness and Compliance:"},{"type":"span","value":" The role of interpretability extends to debugging models, enhancing their performance, and ensuring they make unbiased decisions. This aspect is especially crucial in sectors like finance and healthcare, where explainability isn't just ethical—it's legally mandated."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Fostering Model Trust:"},{"type":"span","value":" At the heart of interpretability lies the concept of 'model trust.' When end-users understand how a model arrives at its predictions, their confidence in these tools skyrockets. This trust is foundational, especially in applications where users rely on model predictions for critical decision-making."}]}]}]},{"type":"paragraph","children":[{"type":"span","value":"In essence, model interpretability weaves the thread of trust through the fabric of machine learning applications. It ensures that as we venture further into the age of AI, our reliance on these models is built on a solid foundation of understanding and transparency."}]},{"type":"heading","level":2,"children":[{"type":"span","value":"Types of Model Interpretability Methods"}]},{"type":"paragraph","children":[{"item":"IMVv3CVZR7at3ZHNX-hR9w","type":"inlineItem"}]},{"type":"paragraph","children":[{"type":"span","value":"In the quest for transparency within machine learning models, various interpretability methods have emerged. A significant survey by Two Sigma categorizes these methods into three primary types: application-grounded, human-grounded, and functionally grounded evaluation. Each of these methods offers a unique perspective on model interpretability, catering to different needs and scenarios."}]},{"type":"heading","level":3,"children":[{"type":"span","value":"Application-Grounded Evaluation"}]},{"type":"paragraph","children":[{"type":"span","value":"Application-grounded evaluation stands out for its emphasis on practical application. This method involves:"}]},{"type":"list","style":"bulleted","children":[{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Direct involvement of a human in the loop:"},{"type":"span","value":" It necessitates that a person directly interacts with the model within a real-life scenario, ensuring that the interpretability methods are grounded in practical use."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Tailored to specific applications:"},{"type":"span","value":" The evaluation focuses on how well the interpretability method aids in understanding model decisions within a particular domain, such as healthcare diagnostics or financial forecasting."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Strengths:"},{"type":"span","value":" Provides direct feedback on the utility of interpretability methods in real-world applications, ensuring that the insights are actionable and relevant."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Weaknesses:"},{"type":"span","value":" Time-consuming and resource-intensive, as it requires setting up specific application scenarios and direct human involvement."}]}]}]},{"type":"heading","level":3,"children":[{"type":"span","value":"Human-Grounded Evaluation"}]},{"type":"paragraph","children":[{"type":"span","value":"Human-grounded evaluation takes a more general approach:"}]},{"type":"list","style":"bulleted","children":[{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Simplified tasks to assess interpretability:"},{"type":"span","value":" Instead of in-depth application scenarios, this method uses simplified tasks that evaluate whether model explanations make sense to average users."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Tools and techniques:"},{"type":"span","value":" Popular tools like LIME (Local Interpretable Model-agnostic Explanations) and SHAP (SHapley Additive exPlanations) are often used in this evaluation type to provide insights into how model decisions are made."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Strengths:"},{"type":"span","value":" More scalable than application-grounded evaluation, allowing for quicker, broader insights into model interpretability."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Weaknesses:"},{"type":"span","value":" May not fully capture the complexity of real-world applications, potentially oversimplifying the interpretability needs of specific scenarios."}]}]}]},{"type":"heading","level":3,"children":[{"type":"span","value":"Functionally Grounded Evaluation"}]},{"type":"paragraph","children":[{"type":"span","value":"Functionally grounded evaluation focuses on theoretical aspects:"}]},{"type":"list","style":"bulleted","children":[{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Assessment based on predefined criteria:"},{"type":"span","value":" This method evaluates interpretability based on whether a model or method meets certain predefined theoretical criteria, without the direct need for human judgment."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Objective and structured:"},{"type":"span","value":" Offers a structured way to assess models based on clear, objective criteria."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Strengths:"},{"type":"span","value":" Efficient and straightforward, providing a quick means to gauge basic interpretability without extensive human involvement."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Weaknesses:"},{"type":"span","value":" Lacks the nuanced understanding that human judgment can provide, possibly overlooking practical interpretability challenges."}]}]}]},{"type":"heading","level":3,"children":[{"type":"span","value":"The Trend Towards Hybrid Approaches"}]},{"type":"paragraph","children":[{"type":"span","value":"Interestingly, a growing trend points towards hybrid approaches that amalgamate elements from all three types of evaluations. This holistic strategy aims to harness the strengths of each method, achieving a more comprehensive understanding of model interpretability. By combining the practical insights of application-grounded evaluation, the scalability of human-grounded evaluation, and the objectivity of functionally grounded evaluation, these hybrid approaches represent the forefront of interpretability research."}]},{"type":"paragraph","children":[{"type":"span","value":"In sum, understanding the strengths and weaknesses of each interpretability method is crucial for selecting the appropriate approach for a given scenario. As the landscape of machine learning continues to evolve, so too will the strategies for making these models transparent and understandable to their end-users."}]},{"type":"paragraph","children":[{"item":"Z5su9I_yQ16q7vzUlugSsg","type":"inlineItem"}]},{"type":"heading","level":2,"children":[{"type":"span","value":"Practical Application of Model Interpretability"}]},{"type":"paragraph","children":[{"type":"span","value":"Model interpretability extends far beyond a theoretical concept, embedding itself into the very fabric of industries that shape our daily lives. Healthcare, finance, and criminal justice represent sectors where the application of interpretability in machine learning models not only enhances operational efficiency but also reinforces ethical standards and compliance with regulatory mandates."}]},{"type":"heading","level":3,"children":[{"type":"span","value":"Healthcare: A Lifeline for Diagnostic Precision"}]},{"type":"paragraph","children":[{"type":"span","value":"In the realm of healthcare, the stakes couldn't be higher. Here, interpretability translates into the ability to uncover the rationale behind diagnostic and treatment recommendations made by AI systems. For instance, when a machine learning model identifies a novel pattern in patient data suggesting a predisposed genetic condition, clinicians need to understand the \"why\" behind this prediction to trust and act upon it. AWS documentation underscores the criticality of interpretability in healthcare, advocating for models that clinicians can interrogate for the evidence leading to their conclusions. Such transparency:"}]},{"type":"list","style":"bulleted","children":[{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Facilitates trust"},{"type":"span","value":" between clinicians and the AI tools they rely on."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Improves patient outcomes"},{"type":"span","value":" by enabling more informed decision-making."}]}]},{"type":"listItem","children":[{"type":"paragraph","children":[{"type":"span","marks":["strong"],"value":"Ensures regulatory compliance"},{"type":"span","value":", meeting stringent standards for medical devices and software."}]}]}]},{"type":"heading","level":3,"children":[{"type":"span","value":"Finance: Decoding the Logic of Loan Approvals"}]},{"type":"paragraph","children":[{"type":"span","value":"The finance sector, particularly in credit scoring models, relies heavily on interpretability. Understanding why a loan application gets approved or denied is crucial not just for regulatory compliance but also for maintaining fairness and transparency. According to AWS documentation, interpretability in financial models helps identify the factors influencing these decisions. 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