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<button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2412.04486">arXiv:2412.04486</a> <span> [<a href="https://arxiv.org/pdf/2412.04486">pdf</a>, <a href="https://arxiv.org/format/2412.04486">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> The Global AI Vibrancy Tool </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Fattorini%2C+L">Loredana Fattorini</a>, <a href="/search/cs?searchtype=author&query=Maslej%2C+N">Nestor Maslej</a>, <a href="/search/cs?searchtype=author&query=Perrault%2C+R">Raymond Perrault</a>, <a href="/search/cs?searchtype=author&query=Parli%2C+V">Vanessa Parli</a>, <a href="/search/cs?searchtype=author&query=Etchemendy%2C+J">John Etchemendy</a>, <a href="/search/cs?searchtype=author&query=Shoham%2C+Y">Yoav Shoham</a>, <a href="/search/cs?searchtype=author&query=Ligett%2C+K">Katrina Ligett</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2412.04486v1-abstract-short" style="display: inline;"> This paper presents the latest version of the Global AI Vibrancy Tool (GVT), an interactive suite of visualizations designed to facilitate the comparison of AI vibrancy across 36 countries, using 42 indicators organized into 8 pillars. The tool offers customizable features that allow users to conduct in-depth country-level comparisons and longitudinal analyses of AI-related metrics, all based on p… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2412.04486v1-abstract-full').style.display = 'inline'; document.getElementById('2412.04486v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2412.04486v1-abstract-full" style="display: none;"> This paper presents the latest version of the Global AI Vibrancy Tool (GVT), an interactive suite of visualizations designed to facilitate the comparison of AI vibrancy across 36 countries, using 42 indicators organized into 8 pillars. The tool offers customizable features that allow users to conduct in-depth country-level comparisons and longitudinal analyses of AI-related metrics, all based on publicly available data. By providing a transparent assessment of national progress in AI, it serves the diverse needs of policymakers, industry leaders, researchers, and the general public. Using weights for indicators and pillars developed by AI Index's panel of experts and combined into an index, the Global AI Vibrancy Ranking for 2023 places the United States first by a significant margin, followed by China and the United Kingdom. The ranking also highlights the rise of smaller nations such as Singapore when evaluated on both absolute and per capita bases. The tool offers three sub-indices for evaluating Global AI Vibrancy along different dimensions: the Innovation Index, the Economic Competitiveness Index, and the Policy, Governance, and Public Engagement Index. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2412.04486v1-abstract-full').style.display = 'none'; document.getElementById('2412.04486v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2405.19522">arXiv:2405.19522</a> <span> [<a href="https://arxiv.org/pdf/2405.19522">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> Artificial Intelligence Index Report 2024 </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Maslej%2C+N">Nestor Maslej</a>, <a href="/search/cs?searchtype=author&query=Fattorini%2C+L">Loredana Fattorini</a>, <a href="/search/cs?searchtype=author&query=Perrault%2C+R">Raymond Perrault</a>, <a href="/search/cs?searchtype=author&query=Parli%2C+V">Vanessa Parli</a>, <a href="/search/cs?searchtype=author&query=Reuel%2C+A">Anka Reuel</a>, <a href="/search/cs?searchtype=author&query=Brynjolfsson%2C+E">Erik Brynjolfsson</a>, <a href="/search/cs?searchtype=author&query=Etchemendy%2C+J">John Etchemendy</a>, <a href="/search/cs?searchtype=author&query=Ligett%2C+K">Katrina Ligett</a>, <a href="/search/cs?searchtype=author&query=Lyons%2C+T">Terah Lyons</a>, <a href="/search/cs?searchtype=author&query=Manyika%2C+J">James Manyika</a>, <a href="/search/cs?searchtype=author&query=Niebles%2C+J+C">Juan Carlos Niebles</a>, <a href="/search/cs?searchtype=author&query=Shoham%2C+Y">Yoav Shoham</a>, <a href="/search/cs?searchtype=author&query=Wald%2C+R">Russell Wald</a>, <a href="/search/cs?searchtype=author&query=Clark%2C+J">Jack Clark</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2405.19522v1-abstract-short" style="display: inline;"> The 2024 Index is our most comprehensive to date and arrives at an important moment when AI's influence on society has never been more pronounced. This year, we have broadened our scope to more extensively cover essential trends such as technical advancements in AI, public perceptions of the technology, and the geopolitical dynamics surrounding its development. Featuring more original data than ev… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.19522v1-abstract-full').style.display = 'inline'; document.getElementById('2405.19522v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2405.19522v1-abstract-full" style="display: none;"> The 2024 Index is our most comprehensive to date and arrives at an important moment when AI's influence on society has never been more pronounced. This year, we have broadened our scope to more extensively cover essential trends such as technical advancements in AI, public perceptions of the technology, and the geopolitical dynamics surrounding its development. Featuring more original data than ever before, this edition introduces new estimates on AI training costs, detailed analyses of the responsible AI landscape, and an entirely new chapter dedicated to AI's impact on science and medicine. The AI Index report tracks, collates, distills, and visualizes data related to artificial intelligence (AI). Our mission is to provide unbiased, rigorously vetted, broadly sourced data in order for policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI. The AI Index is recognized globally as one of the most credible and authoritative sources for data and insights on artificial intelligence. Previous editions have been cited in major newspapers, including the The New York Times, Bloomberg, and The Guardian, have amassed hundreds of academic citations, and been referenced by high-level policymakers in the United States, the United Kingdom, and the European Union, among other places. This year's edition surpasses all previous ones in size, scale, and scope, reflecting the growing significance that AI is coming to hold in all of our lives. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.19522v1-abstract-full').style.display = 'none'; document.getElementById('2405.19522v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 29 May, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2310.03715">arXiv:2310.03715</a> <span> [<a href="https://arxiv.org/pdf/2310.03715">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</span> </div> </div> <p class="title is-5 mathjax"> Artificial Intelligence Index Report 2023 </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Maslej%2C+N">Nestor Maslej</a>, <a href="/search/cs?searchtype=author&query=Fattorini%2C+L">Loredana Fattorini</a>, <a href="/search/cs?searchtype=author&query=Brynjolfsson%2C+E">Erik Brynjolfsson</a>, <a href="/search/cs?searchtype=author&query=Etchemendy%2C+J">John Etchemendy</a>, <a href="/search/cs?searchtype=author&query=Ligett%2C+K">Katrina Ligett</a>, <a href="/search/cs?searchtype=author&query=Lyons%2C+T">Terah Lyons</a>, <a href="/search/cs?searchtype=author&query=Manyika%2C+J">James Manyika</a>, <a href="/search/cs?searchtype=author&query=Ngo%2C+H">Helen Ngo</a>, <a href="/search/cs?searchtype=author&query=Niebles%2C+J+C">Juan Carlos Niebles</a>, <a href="/search/cs?searchtype=author&query=Parli%2C+V">Vanessa Parli</a>, <a href="/search/cs?searchtype=author&query=Shoham%2C+Y">Yoav Shoham</a>, <a href="/search/cs?searchtype=author&query=Wald%2C+R">Russell Wald</a>, <a href="/search/cs?searchtype=author&query=Clark%2C+J">Jack Clark</a>, <a href="/search/cs?searchtype=author&query=Perrault%2C+R">Raymond Perrault</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2310.03715v1-abstract-short" style="display: inline;"> Welcome to the sixth edition of the AI Index Report. This year, the report introduces more original data than any previous edition, including a new chapter on AI public opinion, a more thorough technical performance chapter, original analysis about large language and multimodal models, detailed trends in global AI legislation records, a study of the environmental impact of AI systems, and more. Th… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2310.03715v1-abstract-full').style.display = 'inline'; document.getElementById('2310.03715v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2310.03715v1-abstract-full" style="display: none;"> Welcome to the sixth edition of the AI Index Report. This year, the report introduces more original data than any previous edition, including a new chapter on AI public opinion, a more thorough technical performance chapter, original analysis about large language and multimodal models, detailed trends in global AI legislation records, a study of the environmental impact of AI systems, and more. The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence. Our mission is to provide unbiased, rigorously vetted, broadly sourced data in order for policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI. The report aims to be the world's most credible and authoritative source for data and insights about AI. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2310.03715v1-abstract-full').style.display = 'none'; document.getElementById('2310.03715v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 October, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2205.03468">arXiv:2205.03468</a> <span> [<a href="https://arxiv.org/pdf/2205.03468">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> The AI Index 2022 Annual Report </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Zhang%2C+D">Daniel Zhang</a>, <a href="/search/cs?searchtype=author&query=Maslej%2C+N">Nestor Maslej</a>, <a href="/search/cs?searchtype=author&query=Brynjolfsson%2C+E">Erik Brynjolfsson</a>, <a href="/search/cs?searchtype=author&query=Etchemendy%2C+J">John Etchemendy</a>, <a href="/search/cs?searchtype=author&query=Lyons%2C+T">Terah Lyons</a>, <a href="/search/cs?searchtype=author&query=Manyika%2C+J">James Manyika</a>, <a href="/search/cs?searchtype=author&query=Ngo%2C+H">Helen Ngo</a>, <a href="/search/cs?searchtype=author&query=Niebles%2C+J+C">Juan Carlos Niebles</a>, <a href="/search/cs?searchtype=author&query=Sellitto%2C+M">Michael Sellitto</a>, <a href="/search/cs?searchtype=author&query=Sakhaee%2C+E">Ellie Sakhaee</a>, <a href="/search/cs?searchtype=author&query=Shoham%2C+Y">Yoav Shoham</a>, <a href="/search/cs?searchtype=author&query=Clark%2C+J">Jack Clark</a>, <a href="/search/cs?searchtype=author&query=Perrault%2C+R">Raymond Perrault</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2205.03468v1-abstract-short" style="display: inline;"> Welcome to the fifth edition of the AI Index Report! The latest edition includes data from a broad set of academic, private, and nonprofit organizations as well as more self-collected data and original analysis than any previous editions, including an expanded technical performance chapter, a new survey of robotics researchers around the world, data on global AI legislation records in 25 countries… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2205.03468v1-abstract-full').style.display = 'inline'; document.getElementById('2205.03468v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2205.03468v1-abstract-full" style="display: none;"> Welcome to the fifth edition of the AI Index Report! The latest edition includes data from a broad set of academic, private, and nonprofit organizations as well as more self-collected data and original analysis than any previous editions, including an expanded technical performance chapter, a new survey of robotics researchers around the world, data on global AI legislation records in 25 countries, and a new chapter with an in-depth analysis of technical AI ethics metrics. The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence. Its mission is to provide unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI. The report aims to be the world's most credible and authoritative source for data and insights about AI. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2205.03468v1-abstract-full').style.display = 'none'; document.getElementById('2205.03468v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 2 May, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2108.07258">arXiv:2108.07258</a> <span> [<a href="https://arxiv.org/pdf/2108.07258">pdf</a>, <a href="https://arxiv.org/format/2108.07258">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</span> </div> </div> <p class="title is-5 mathjax"> On the Opportunities and Risks of Foundation Models </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Bommasani%2C+R">Rishi Bommasani</a>, <a href="/search/cs?searchtype=author&query=Hudson%2C+D+A">Drew A. Hudson</a>, <a href="/search/cs?searchtype=author&query=Adeli%2C+E">Ehsan Adeli</a>, <a href="/search/cs?searchtype=author&query=Altman%2C+R">Russ Altman</a>, <a href="/search/cs?searchtype=author&query=Arora%2C+S">Simran Arora</a>, <a href="/search/cs?searchtype=author&query=von+Arx%2C+S">Sydney von Arx</a>, <a href="/search/cs?searchtype=author&query=Bernstein%2C+M+S">Michael S. Bernstein</a>, <a href="/search/cs?searchtype=author&query=Bohg%2C+J">Jeannette Bohg</a>, <a href="/search/cs?searchtype=author&query=Bosselut%2C+A">Antoine Bosselut</a>, <a href="/search/cs?searchtype=author&query=Brunskill%2C+E">Emma Brunskill</a>, <a href="/search/cs?searchtype=author&query=Brynjolfsson%2C+E">Erik Brynjolfsson</a>, <a href="/search/cs?searchtype=author&query=Buch%2C+S">Shyamal Buch</a>, <a href="/search/cs?searchtype=author&query=Card%2C+D">Dallas Card</a>, <a href="/search/cs?searchtype=author&query=Castellon%2C+R">Rodrigo Castellon</a>, <a href="/search/cs?searchtype=author&query=Chatterji%2C+N">Niladri Chatterji</a>, <a href="/search/cs?searchtype=author&query=Chen%2C+A">Annie Chen</a>, <a href="/search/cs?searchtype=author&query=Creel%2C+K">Kathleen Creel</a>, <a href="/search/cs?searchtype=author&query=Davis%2C+J+Q">Jared Quincy Davis</a>, <a href="/search/cs?searchtype=author&query=Demszky%2C+D">Dora Demszky</a>, <a href="/search/cs?searchtype=author&query=Donahue%2C+C">Chris Donahue</a>, <a href="/search/cs?searchtype=author&query=Doumbouya%2C+M">Moussa Doumbouya</a>, <a href="/search/cs?searchtype=author&query=Durmus%2C+E">Esin Durmus</a>, <a href="/search/cs?searchtype=author&query=Ermon%2C+S">Stefano Ermon</a>, <a href="/search/cs?searchtype=author&query=Etchemendy%2C+J">John Etchemendy</a>, <a href="/search/cs?searchtype=author&query=Ethayarajh%2C+K">Kawin Ethayarajh</a> , et al. (89 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2108.07258v3-abstract-short" style="display: inline;"> AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks. We call these models foundation models to underscore their critically central yet incomplete character. This report provides a thorough account of the opportunities and risks of foundation models, ranging from their cap… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2108.07258v3-abstract-full').style.display = 'inline'; document.getElementById('2108.07258v3-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2108.07258v3-abstract-full" style="display: none;"> AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks. We call these models foundation models to underscore their critically central yet incomplete character. This report provides a thorough account of the opportunities and risks of foundation models, ranging from their capabilities (e.g., language, vision, robotics, reasoning, human interaction) and technical principles(e.g., model architectures, training procedures, data, systems, security, evaluation, theory) to their applications (e.g., law, healthcare, education) and societal impact (e.g., inequity, misuse, economic and environmental impact, legal and ethical considerations). Though foundation models are based on standard deep learning and transfer learning, their scale results in new emergent capabilities,and their effectiveness across so many tasks incentivizes homogenization. Homogenization provides powerful leverage but demands caution, as the defects of the foundation model are inherited by all the adapted models downstream. Despite the impending widespread deployment of foundation models, we currently lack a clear understanding of how they work, when they fail, and what they are even capable of due to their emergent properties. To tackle these questions, we believe much of the critical research on foundation models will require deep interdisciplinary collaboration commensurate with their fundamentally sociotechnical nature. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2108.07258v3-abstract-full').style.display = 'none'; document.getElementById('2108.07258v3-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 July, 2022; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 16 August, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Authored by the Center for Research on Foundation Models (CRFM) at the Stanford Institute for Human-Centered Artificial Intelligence (HAI). Report page with citation guidelines: https://crfm.stanford.edu/report.html</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2103.06312">arXiv:2103.06312</a> <span> [<a href="https://arxiv.org/pdf/2103.06312">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="General Literature">cs.GL</span> </div> </div> <p class="title is-5 mathjax"> The AI Index 2021 Annual Report </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Zhang%2C+D">Daniel Zhang</a>, <a href="/search/cs?searchtype=author&query=Mishra%2C+S">Saurabh Mishra</a>, <a href="/search/cs?searchtype=author&query=Brynjolfsson%2C+E">Erik Brynjolfsson</a>, <a href="/search/cs?searchtype=author&query=Etchemendy%2C+J">John Etchemendy</a>, <a href="/search/cs?searchtype=author&query=Ganguli%2C+D">Deep Ganguli</a>, <a href="/search/cs?searchtype=author&query=Grosz%2C+B">Barbara Grosz</a>, <a href="/search/cs?searchtype=author&query=Lyons%2C+T">Terah Lyons</a>, <a href="/search/cs?searchtype=author&query=Manyika%2C+J">James Manyika</a>, <a href="/search/cs?searchtype=author&query=Niebles%2C+J+C">Juan Carlos Niebles</a>, <a href="/search/cs?searchtype=author&query=Sellitto%2C+M">Michael Sellitto</a>, <a href="/search/cs?searchtype=author&query=Shoham%2C+Y">Yoav Shoham</a>, <a href="/search/cs?searchtype=author&query=Clark%2C+J">Jack Clark</a>, <a href="/search/cs?searchtype=author&query=Perrault%2C+R">Raymond Perrault</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2103.06312v1-abstract-short" style="display: inline;"> Welcome to the fourth edition of the AI Index Report. This year we significantly expanded the amount of data available in the report, worked with a broader set of external organizations to calibrate our data, and deepened our connections with the Stanford Institute for Human-Centered Artificial Intelligence (HAI). The AI Index Report tracks, collates, distills, and visualizes data related to artif… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2103.06312v1-abstract-full').style.display = 'inline'; document.getElementById('2103.06312v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2103.06312v1-abstract-full" style="display: none;"> Welcome to the fourth edition of the AI Index Report. This year we significantly expanded the amount of data available in the report, worked with a broader set of external organizations to calibrate our data, and deepened our connections with the Stanford Institute for Human-Centered Artificial Intelligence (HAI). The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence. Its mission is to provide unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, executives, journalists, and the general public to develop intuitions about the complex field of AI. The report aims to be the most credible and authoritative source for data and insights about AI in the world. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2103.06312v1-abstract-full').style.display = 'none'; document.getElementById('2103.06312v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 8 March, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2021. </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a>  </span> </div> </div> </main> <footer> <div class="columns is-desktop" role="navigation" aria-label="Secondary">  <div class="column"> <div class="columns"> <div class="column"> <ul class="nav-spaced"> <li><a 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