Democratizing & Accelerating the Future of AI With Kevin Scott

The speaker discusses the advancements in machine learning and AI over the past six months, including self-supervised models and pre-trained models, and their potential implications for various domains.

• Self-supervised models are becoming better at performing tasks and admitting a broader range of tasks as they scale up
• Pre-trained models can be used as software engineering objects to solve a variety of problems
• Self-supervised learning techniques are being applied to various domains, including vision and graphs
• The use of these models has potential implications for fields such as molecular dynamics and protein folding

Researchers at MSR have developed a self-supervised learning technique called graph formers, which can be used to solve molecular dynamics problems and protein folding. This is an exciting development in the field of AI and has potential implications for drug discovery and other areas of molecular biology.

Kevin Scott is executive vice president of Technology & Research, and the chief technology officer of Microsoft. He is an innovative leader and is passionate about creating technologies that benefit everyone. He joins Scale AI CEO Alexandr Wang in a fireside chat to discuss the recent advances in AI that he considers the most impactful, and how AI can be democratized for the benefit of everyone in society, enabling a new wave of technology innovation. Together they explore a vision of an AI-enabled society where AI is accessible to all - and walk through what that means for the way we live and work.