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7 0 11-14 0 7 7 0 0114 0z" /> </svg></button> <div class="gh-navigation-members"><a href="https://blog-mozilla-ai.translate.goog/?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB#/portal/signin" data-portal="signin">Sign in</a> <a class="gh-button" href="https://blog-mozilla-ai.translate.goog/?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB#/portal/signup" data-portal="signup">Subscribe</a> </div> </div> </div> </header> <section class="gh-header is-highlight gh-outer"> <div class="gh-header-inner gh-inner"> <div class="gh-header-left"> <article class="gh-card post"><a class="gh-card-link" href="https://blog-mozilla-ai.translate.goog/taming-randomness-in-ml-models-with-hypothesis-testing-and-marimo/?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB"> <figure class="gh-card-image"><img srcset="https://blog-mozilla-ai.translate.goog/content/images/size/w160/format/webp/2024/10/photo-1661114544198-4b2c6dad0b58.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 160w,https://blog-mozilla-ai.translate.goog/content/images/size/w320/format/webp/2024/10/photo-1661114544198-4b2c6dad0b58.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 320w,https://blog-mozilla-ai.translate.goog/content/images/size/w600/format/webp/2024/10/photo-1661114544198-4b2c6dad0b58.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 600w,https://blog-mozilla-ai.translate.goog/content/images/size/w960/format/webp/2024/10/photo-1661114544198-4b2c6dad0b58.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 960w,https://blog-mozilla-ai.translate.goog/content/images/size/w1200/format/webp/2024/10/photo-1661114544198-4b2c6dad0b58.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 1200w,https://blog-mozilla-ai.translate.goog/content/images/size/w2000/format/webp/2024/10/photo-1661114544198-4b2c6dad0b58.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 2000w" sizes="(max-width: 767px) calc(100vw - max(8vmin, 40px)), 640px" src="/content/images/size/w600/2024/10/photo-1661114544198-4b2c6dad0b58.jpeg" alt="Taming randomness in ML models with hypothesis testing and marimo"> </figure> <div class="gh-card-wrapper"> <h3 class="gh-card-title is-title">Taming randomness in ML models with hypothesis testing and marimo</h3> <p class="gh-card-excerpt is-body">The behavior of ML models is often affected by randomness at different levels, from the initialization of model parameters to the dataset split into training and evaluation. Thus, predictions made by a model (including the answers an LLM gives to your questions) are potentially different every time you run it.</p> <footer class="gh-card-meta"><!-- --> <span class="gh-card-author">By Davide Eynard</span> <time class="gh-card-date" datetime="2024-10-16">Oct 16, 2024</time> <!-- --> </footer> </div></a> </article> </div> <div class="gh-header-middle"> <article class="gh-card post featured"><a class="gh-card-link" href="https://blog-mozilla-ai.translate.goog/introducing-lumigator-2/?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB"> <figure class="gh-card-image"><img srcset="https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1528904125624-f485d66786ef?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDExM3x8aWxsdW1pbmF0ZXxlbnwwfHx8fDE3Mjc3NjkyMjl8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D160 160w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1528904125624-f485d66786ef?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDExM3x8aWxsdW1pbmF0ZXxlbnwwfHx8fDE3Mjc3NjkyMjl8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D320 320w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1528904125624-f485d66786ef?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDExM3x8aWxsdW1pbmF0ZXxlbnwwfHx8fDE3Mjc3NjkyMjl8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D600 600w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1528904125624-f485d66786ef?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDExM3x8aWxsdW1pbmF0ZXxlbnwwfHx8fDE3Mjc3NjkyMjl8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D960 960w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1528904125624-f485d66786ef?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDExM3x8aWxsdW1pbmF0ZXxlbnwwfHx8fDE3Mjc3NjkyMjl8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D1200 1200w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1528904125624-f485d66786ef?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDExM3x8aWxsdW1pbmF0ZXxlbnwwfHx8fDE3Mjc3NjkyMjl8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D2000 2000w" sizes="320px" src="https://images.unsplash.com/photo-1528904125624-f485d66786ef?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3wxMTc3M3wwfDF8c2VhcmNofDExM3x8aWxsdW1pbmF0ZXxlbnwwfHx8fDE3Mjc3NjkyMjl8MA&ixlib=rb-4.0.3&q=80&w=600" alt="Introducing Lumigator 🐊"> </figure> <div class="gh-card-wrapper"> <h3 class="gh-card-title is-title">Introducing Lumigator 🐊</h3> <p class="gh-card-excerpt is-body">An MVP for Simplifying AI Model Selection In today’s fast-moving AI landscape, choosing the right large language model (LLM) for your project can feel like navigating a maze. With hundreds of models, each offering different capabilities, the process can be overwhelming. That’s why Mozilla.ai is developing Lumigator,</p> <footer class="gh-card-meta"><!-- --> <span class="gh-card-author">By Juliana Rodrigues Araújo</span> <time class="gh-card-date" datetime="2024-10-01">Oct 1, 2024</time> <!-- --> </footer> </div></a> </article> <article class="gh-card post"><a class="gh-card-link" href="https://blog-mozilla-ai.translate.goog/the-importance-of-ground-truth-data-in-ai-applications-an-overview/?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB"> <figure class="gh-card-image"><img srcset="https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1458411328059-8244e9b9bdca?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDI2fHxncm91bmQlMjB0cnV0aHxlbnwwfHx8fDE3MjU5NTgyMTF8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D160 160w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1458411328059-8244e9b9bdca?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDI2fHxncm91bmQlMjB0cnV0aHxlbnwwfHx8fDE3MjU5NTgyMTF8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D320 320w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1458411328059-8244e9b9bdca?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDI2fHxncm91bmQlMjB0cnV0aHxlbnwwfHx8fDE3MjU5NTgyMTF8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D600 600w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1458411328059-8244e9b9bdca?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDI2fHxncm91bmQlMjB0cnV0aHxlbnwwfHx8fDE3MjU5NTgyMTF8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D960 960w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1458411328059-8244e9b9bdca?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDI2fHxncm91bmQlMjB0cnV0aHxlbnwwfHx8fDE3MjU5NTgyMTF8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D1200 1200w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1458411328059-8244e9b9bdca?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDI2fHxncm91bmQlMjB0cnV0aHxlbnwwfHx8fDE3MjU5NTgyMTF8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D2000 2000w" sizes="320px" src="https://images.unsplash.com/photo-1458411328059-8244e9b9bdca?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3wxMTc3M3wwfDF8c2VhcmNofDI2fHxncm91bmQlMjB0cnV0aHxlbnwwfHx8fDE3MjU5NTgyMTF8MA&ixlib=rb-4.0.3&q=80&w=600" alt="The Importance of Ground Truth Data in AI Applications: An Overview"> </figure> <div class="gh-card-wrapper"> <h3 class="gh-card-title is-title">The Importance of Ground Truth Data in AI Applications: An Overview</h3> <p class="gh-card-excerpt is-body">Introduction We are witnessing explosive growth in the development of artificial intelligence (AI) applications across various industries, from virtual agents to healthcare diagnostics and autonomous driving. This growth is powered by vast datasets and advanced algorithms that enable AI systems to learn and make decisions in real-world scenarios. However, the</p> <footer class="gh-card-meta"><!-- --> <span class="gh-card-author">By Sandra Antunes</span> <time class="gh-card-date" datetime="2024-09-10">Sep 10, 2024</time> <!-- --> </footer> </div></a> </article> <article class="gh-card post"><a class="gh-card-link" href="https://blog-mozilla-ai.translate.goog/towards-truly-multilingual-ai-breaking-english-dominance/?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB"> <figure class="gh-card-image"><img srcset="https://blog-mozilla-ai.translate.goog/content/images/size/w160/format/webp/2024/07/photo-1592776115343-3f2f637dba4d.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 160w,https://blog-mozilla-ai.translate.goog/content/images/size/w320/format/webp/2024/07/photo-1592776115343-3f2f637dba4d.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 320w,https://blog-mozilla-ai.translate.goog/content/images/size/w600/format/webp/2024/07/photo-1592776115343-3f2f637dba4d.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 600w,https://blog-mozilla-ai.translate.goog/content/images/size/w960/format/webp/2024/07/photo-1592776115343-3f2f637dba4d.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 960w,https://blog-mozilla-ai.translate.goog/content/images/size/w1200/format/webp/2024/07/photo-1592776115343-3f2f637dba4d.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 1200w,https://blog-mozilla-ai.translate.goog/content/images/size/w2000/format/webp/2024/07/photo-1592776115343-3f2f637dba4d.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 2000w" sizes="320px" src="/content/images/size/w600/2024/07/photo-1592776115343-3f2f637dba4d.jpeg" alt="Towards Truly Multilingual AI: Breaking English Dominance"> </figure> <div class="gh-card-wrapper"> <h3 class="gh-card-title is-title">Towards Truly Multilingual AI: Breaking English Dominance</h3> <p class="gh-card-excerpt is-body">At the TAUS Massively Multilingual AI conference in Rome, I had the honor of moderating a panel on Multilingual AI provocatively titled “No English Please - How to move towards truly multilingual AI”. In this panel, we explored the pressing need for AI to transcend linguistic barriers and embrace global</p> <footer class="gh-card-meta"><!-- --> <span class="gh-card-author">By Julie Belião</span> <time class="gh-card-date" datetime="2024-07-18">Jul 18, 2024</time> <!-- --> </footer> </div></a> </article> </div> <div class="gh-header-right"> <div class="gh-featured-feed"> <article class="gh-card post"><a class="gh-card-link" href="https://blog-mozilla-ai.translate.goog/uncovering-genai-trends-using-local-language-models-to-explore-35-organizations/?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB"> <figure class="gh-card-image"><img srcset="https://blog-mozilla-ai.translate.goog/content/images/size/w160/format/webp/2024/06/photo-1536313398110-ea21a1fc9467.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 160w,https://blog-mozilla-ai.translate.goog/content/images/size/w320/format/webp/2024/06/photo-1536313398110-ea21a1fc9467.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 320w,https://blog-mozilla-ai.translate.goog/content/images/size/w600/format/webp/2024/06/photo-1536313398110-ea21a1fc9467.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 600w,https://blog-mozilla-ai.translate.goog/content/images/size/w960/format/webp/2024/06/photo-1536313398110-ea21a1fc9467.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 960w,https://blog-mozilla-ai.translate.goog/content/images/size/w1200/format/webp/2024/06/photo-1536313398110-ea21a1fc9467.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 1200w,https://blog-mozilla-ai.translate.goog/content/images/size/w2000/format/webp/2024/06/photo-1536313398110-ea21a1fc9467.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 2000w" sizes="80px" src="/content/images/size/w600/2024/06/photo-1536313398110-ea21a1fc9467.jpeg" alt="Uncovering GenAI Trends: Using Local Language Models to Explore 35 Organizations"> </figure> <div class="gh-card-wrapper"> <h3 class="gh-card-title is-title">Uncovering GenAI Trends: Using Local Language Models to Explore 35 Organizations</h3> <p class="gh-card-excerpt is-body">Over the past few months at Mozilla.ai, we’ve engaged with a number of organizations to learn how they are using language models in practice. We spoke with 35 organizations across various sectors, including finance, government, startups, and large enterprises. Our interviewees ranged from ML engineers to CTOs, capturing</p> <footer class="gh-card-meta"><!-- --> <span class="gh-card-author">By Stefan French</span> <time class="gh-card-date" datetime="2024-06-03">Jun 3, 2024</time> <!-- --> </footer> </div></a> </article> <article class="gh-card post"><a class="gh-card-link" href="https://blog-mozilla-ai.translate.goog/on-model-selection-for-text-summarization/?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB"> <figure class="gh-card-image"><img srcset="https://blog-mozilla-ai.translate.goog/content/images/size/w160/format/webp/2024/05/photo-1608556984704-fa578c96e6eb.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 160w,https://blog-mozilla-ai.translate.goog/content/images/size/w320/format/webp/2024/05/photo-1608556984704-fa578c96e6eb.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 320w,https://blog-mozilla-ai.translate.goog/content/images/size/w600/format/webp/2024/05/photo-1608556984704-fa578c96e6eb.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 600w,https://blog-mozilla-ai.translate.goog/content/images/size/w960/format/webp/2024/05/photo-1608556984704-fa578c96e6eb.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 960w,https://blog-mozilla-ai.translate.goog/content/images/size/w1200/format/webp/2024/05/photo-1608556984704-fa578c96e6eb.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 1200w,https://blog-mozilla-ai.translate.goog/content/images/size/w2000/format/webp/2024/05/photo-1608556984704-fa578c96e6eb.jpeg?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB 2000w" sizes="80px" src="/content/images/size/w600/2024/05/photo-1608556984704-fa578c96e6eb.jpeg" alt="On model selection for text summarization"> </figure> <div class="gh-card-wrapper"> <h3 class="gh-card-title is-title">On model selection for text summarization</h3> <p class="gh-card-excerpt is-body">On our journey toward our product MVP, we are building a platform that will guide users through the process of machine learning model selection by performing evidence-based evaluation. We’re starting with text summarization as a first platform task for two main reasons: First, the product interviews we’ve conducted</p> <footer class="gh-card-meta"><!-- --> <span class="gh-card-author">By Imtihan Ahmed</span> <time class="gh-card-date" datetime="2024-05-15">May 15, 2024</time> <!-- --> </footer> </div></a> </article> <article class="gh-card post"><a class="gh-card-link" href="https://blog-mozilla-ai.translate.goog/local-llm-as-judge-evaluation-with-lm-buddy-prometheus-and-llamafile/?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB"> <figure class="gh-card-image"><img srcset="https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1619765618019-3e02fef0adf2?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDE2fHx0b29sa2l0fGVufDB8fHx8MTcxMzk4NDAyNnww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D160 160w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1619765618019-3e02fef0adf2?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDE2fHx0b29sa2l0fGVufDB8fHx8MTcxMzk4NDAyNnww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D320 320w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1619765618019-3e02fef0adf2?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDE2fHx0b29sa2l0fGVufDB8fHx8MTcxMzk4NDAyNnww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D600 600w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1619765618019-3e02fef0adf2?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDE2fHx0b29sa2l0fGVufDB8fHx8MTcxMzk4NDAyNnww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D960 960w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1619765618019-3e02fef0adf2?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDE2fHx0b29sa2l0fGVufDB8fHx8MTcxMzk4NDAyNnww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D1200 1200w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1619765618019-3e02fef0adf2?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDE2fHx0b29sa2l0fGVufDB8fHx8MTcxMzk4NDAyNnww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D2000 2000w" sizes="80px" src="https://images.unsplash.com/photo-1619765618019-3e02fef0adf2?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3wxMTc3M3wwfDF8c2VhcmNofDE2fHx0b29sa2l0fGVufDB8fHx8MTcxMzk4NDAyNnww&ixlib=rb-4.0.3&q=80&w=600" alt="Local LLM-as-judge evaluation with lm-buddy, Prometheus and llamafile"> </figure> <div class="gh-card-wrapper"> <h3 class="gh-card-title is-title">Local LLM-as-judge evaluation with lm-buddy, Prometheus and llamafile</h3> <p class="gh-card-excerpt is-body">In the bustling AI news cycle, where new models are unveiled at every turn, cost and evaluation don’t come up as frequently but are crucial to both developers and businesses in their use of AI systems. It is well known that LLMs are extremely costly to pre-train; but closed</p> <footer class="gh-card-meta"><!-- --> <span class="gh-card-author">By Davide Eynard</span> <time class="gh-card-date" datetime="2024-04-24">Apr 24, 2024</time> <!-- --> </footer> </div></a> </article> <article class="gh-card post"><a class="gh-card-link" href="https://blog-mozilla-ai.translate.goog/open-source-in-the-age-of-llms/?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB"> <figure class="gh-card-image"><img srcset="https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1529061498291-c978a148ee6e?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDV8fHBhdGNoJTIwb2YlMjBmbG93ZXJzfGVufDB8fHx8MTcxMjY4ODQwMHww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D160 160w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1529061498291-c978a148ee6e?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDV8fHBhdGNoJTIwb2YlMjBmbG93ZXJzfGVufDB8fHx8MTcxMjY4ODQwMHww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D320 320w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1529061498291-c978a148ee6e?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDV8fHBhdGNoJTIwb2YlMjBmbG93ZXJzfGVufDB8fHx8MTcxMjY4ODQwMHww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D600 600w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1529061498291-c978a148ee6e?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDV8fHBhdGNoJTIwb2YlMjBmbG93ZXJzfGVufDB8fHx8MTcxMjY4ODQwMHww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D960 960w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1529061498291-c978a148ee6e?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDV8fHBhdGNoJTIwb2YlMjBmbG93ZXJzfGVufDB8fHx8MTcxMjY4ODQwMHww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D1200 1200w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1529061498291-c978a148ee6e?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDV8fHBhdGNoJTIwb2YlMjBmbG93ZXJzfGVufDB8fHx8MTcxMjY4ODQwMHww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D2000 2000w" sizes="80px" src="https://images.unsplash.com/photo-1529061498291-c978a148ee6e?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3wxMTc3M3wwfDF8c2VhcmNofDV8fHBhdGNoJTIwb2YlMjBmbG93ZXJzfGVufDB8fHx8MTcxMjY4ODQwMHww&ixlib=rb-4.0.3&q=80&w=600" alt="Wildflowers with mountains in the background"> </figure> <div class="gh-card-wrapper"> <h3 class="gh-card-title is-title">Open Source in the Age of LLMs</h3> <p class="gh-card-excerpt is-body">Like our parent company, Mozilla.ai’s founding story is rooted in open-source principles and community collaboration. Since our start last year, our key focus has been exploring state-of-the-art methods for evaluating and fine-tuning large-language models (LLMs), including continued open-source LLM evaluation experiments and establishing our GPU cluster’s infrastructure.</p> <footer class="gh-card-meta"><!-- --> <span class="gh-card-author">By Vicki Boykis</span> <time class="gh-card-date" datetime="2024-04-10">Apr 10, 2024</time> <!-- --> </footer> </div></a> </article> <article class="gh-card post"><a class="gh-card-link" href="https://blog-mozilla-ai.translate.goog/the-cost-of-cutting-edge-scaling-compute-and-limiting-access/?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB"> <figure class="gh-card-image"><img srcset="https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1649829879702-a0afdbec8d2f?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDEwfHxjb3N0JTIwbWF0ZXJpYWxzfGVufDB8fHx8MTcxMDg4NTkyNHww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D160 160w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1649829879702-a0afdbec8d2f?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDEwfHxjb3N0JTIwbWF0ZXJpYWxzfGVufDB8fHx8MTcxMDg4NTkyNHww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D320 320w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1649829879702-a0afdbec8d2f?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDEwfHxjb3N0JTIwbWF0ZXJpYWxzfGVufDB8fHx8MTcxMDg4NTkyNHww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D600 600w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1649829879702-a0afdbec8d2f?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDEwfHxjb3N0JTIwbWF0ZXJpYWxzfGVufDB8fHx8MTcxMDg4NTkyNHww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D960 960w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1649829879702-a0afdbec8d2f?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDEwfHxjb3N0JTIwbWF0ZXJpYWxzfGVufDB8fHx8MTcxMDg4NTkyNHww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D1200 1200w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1649829879702-a0afdbec8d2f?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDEwfHxjb3N0JTIwbWF0ZXJpYWxzfGVufDB8fHx8MTcxMDg4NTkyNHww%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D2000 2000w" sizes="80px" src="https://images.unsplash.com/photo-1649829879702-a0afdbec8d2f?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3wxMTc3M3wwfDF8c2VhcmNofDEwfHxjb3N0JTIwbWF0ZXJpYWxzfGVufDB8fHx8MTcxMDg4NTkyNHww&ixlib=rb-4.0.3&q=80&w=600" alt="Weathered cemen"> </figure> <div class="gh-card-wrapper"> <h3 class="gh-card-title is-title">The cost of cutting-edge: Scaling compute and limiting access</h3> <p class="gh-card-excerpt is-body">In a year marked by extraordinary advancements in artificial intelligence, largely driven by the evolution of large language models (LLMs), one factor stands out as a universal accelerator: the exponential growth in computational power. Over the last few years, researchers have continuously pushed the boundaries of what a ‘large’ language</p> <footer class="gh-card-meta"><!-- --> <span class="gh-card-author">By Stefan French</span> <time class="gh-card-date" datetime="2024-03-20">Mar 20, 2024</time> <!-- --> </footer> </div></a> </article> <article class="gh-card post"><a class="gh-card-link" href="https://blog-mozilla-ai.translate.goog/exploring-llm-evaluation-at-scale-with-the-neurips-large-language-model-efficiency-challenge/?_x_tr_sl=pl&_x_tr_tl=cs&_x_tr_hl=en-GB"> <figure class="gh-card-image"><img srcset="https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1562447141-5ab151b2638f?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDI3fHxldmFsdWF0aW9uJTIwcGFsZXR0ZXxlbnwwfHx8fDE3MDgzNTI4MTR8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D160 160w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1562447141-5ab151b2638f?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDI3fHxldmFsdWF0aW9uJTIwcGFsZXR0ZXxlbnwwfHx8fDE3MDgzNTI4MTR8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D320 320w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1562447141-5ab151b2638f?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDI3fHxldmFsdWF0aW9uJTIwcGFsZXR0ZXxlbnwwfHx8fDE3MDgzNTI4MTR8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D600 600w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1562447141-5ab151b2638f?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDI3fHxldmFsdWF0aW9uJTIwcGFsZXR0ZXxlbnwwfHx8fDE3MDgzNTI4MTR8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D960 960w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1562447141-5ab151b2638f?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDI3fHxldmFsdWF0aW9uJTIwcGFsZXR0ZXxlbnwwfHx8fDE3MDgzNTI4MTR8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D1200 1200w,https://translate.google.com/website?sl=pl&tl=cs&hl=en-GB&u=https://images.unsplash.com/photo-1562447141-5ab151b2638f?crop%3Dentropy%26cs%3Dtinysrgb%26fit%3Dmax%26fm%3Dwebp%26ixid%3DM3wxMTc3M3wwfDF8c2VhcmNofDI3fHxldmFsdWF0aW9uJTIwcGFsZXR0ZXxlbnwwfHx8fDE3MDgzNTI4MTR8MA%26ixlib%3Drb-4.0.3%26q%3D80%26w%3D2000 2000w" sizes="80px" src="https://images.unsplash.com/photo-1562447141-5ab151b2638f?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3wxMTc3M3wwfDF8c2VhcmNofDI3fHxldmFsdWF0aW9uJTIwcGFsZXR0ZXxlbnwwfHx8fDE3MDgzNTI4MTR8MA&ixlib=rb-4.0.3&q=80&w=600" alt="LLM evaluation at scale with the NeurIPS Large Language Model Efficiency Challenge"> </figure> <div class="gh-card-wrapper"> <h3 class="gh-card-title is-title">LLM evaluation at scale with the NeurIPS Large Language Model Efficiency Challenge</h3> <p class="gh-card-excerpt is-body">After a year of breakneck innovation and hype in the AI space, we have now moved sufficiently beyond the peak of the hype cycle to start asking a critical question: are LLMs good enough yet to solve all of the business and societal challenges we are setting them up for?</p> <footer class="gh-card-meta"><!-- --> <span class="gh-card-author">By Vicki Boykis</span> <time class="gh-card-date" datetime="2024-02-21">Feb 21, 2024</time> <!-- --> </footer> </div></a> </article> </div> </div> </div> </section> <section class="gh-cta gh-outer"> <div class="gh-cta-inner gh-inner"> <div class="gh-cta-content"> <h2 class="gh-cta-title is-title">Mozilla.ai</h2> <p class="gh-cta-description is-body">Subscribe to receive updates</p> </div> <form class="gh-form" data-members-form><input class="gh-form-input" id="cta-email" name="email" 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