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What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.
What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.
AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery. Experts will separate hype from reality, spotlighting where AI is already enabling genuine breakthroughs and where its limits and risks remain.
AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery. Experts will separate hype from reality, spotlighting where AI is already enabling genuine breakthroughs and where its limits and risks remain.
While Large Language Models (LLMs) show promise in many domains, relying on them for direct policy generation in games often results in illegal moves and poor strategic play.
While Large Language Models (LLMs) show promise in many domains, relying on them for direct policy generation in games often results in illegal moves and poor strategic play.
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This Symposium hosted by the U.S. Department of Commerce and National Institute of Standards and Technology, Stanford Institute for Human-Centered Artificial Intelligence (HAI), and the FinRegLab, will bring together leaders from government, industry, civil society, and academia to explore potential opportunities and challenges posed by artificial intelligence and machine learning deployment across different economic sectors, with a particular focus on financial services and healthcare.
The event is designed to address how these technologies relate to ensuring inclusive economic growth, supporting financial inclusion, and mitigating risks such as bias and unfairness. It will feature presenters and panelists on the cutting edge of researching fairness and explainability in AI, as well as those working to develop policies and frameworks to evaluate and assess the goals of improving the trustworthiness, inclusiveness, and equity of AI deployment.
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