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A eureka moment is a two-step process: discovering something new and surprising, and establishing that it is correct. Drawing on her work at Axiom, Carina will discuss the transition from solving mathematical benchmarks to contributing to research, and from proving individual theorems to formalizing mathematical theories in Lean.

A eureka moment is a two-step process: discovering something new and surprising, and establishing that it is correct. Drawing on her work at Axiom, Carina will discuss the transition from solving mathematical benchmarks to contributing to research, and from proving individual theorems to formalizing mathematical theories in Lean.
Scientific progress is a key driver of economic growth and prosperity. There is great excitement- but also concerns- about the impacts of AI on science, but so far little data. We provide early insights on this from three data sources: a sample of 15 million Gemini interactions, an inventory of over 2,600 specialized AI models across disciplines, and a survey of over 600 scientists.

Scientific progress is a key driver of economic growth and prosperity. There is great excitement- but also concerns- about the impacts of AI on science, but so far little data. We provide early insights on this from three data sources: a sample of 15 million Gemini interactions, an inventory of over 2,600 specialized AI models across disciplines, and a survey of over 600 scientists.
The rapid acceleration of AI comes with a profound wave of anxiety. Across every sector of society, people are facing unsettling questions about their worth and their place in a shifting world.

The rapid acceleration of AI comes with a profound wave of anxiety. Across every sector of society, people are facing unsettling questions about their worth and their place in a shifting world.
Much of the discourse around AI frames it as an alien and inscrutable intelligence. But in fact our success at creating "real" AI with general capabilities in the 2020s has come not only by taking many pages from computational neuroscience, but by performing large-scale modeling on human language-- the "DNA" of our collective intelligence. Intelligence does not equate with or arise from optimal performance at any particular task; neither does it arise in isolation, or against the background of a static game-like environment. Rather, it arises through the social modeling of interactions with other intelligent entities.
This talk will explore the deep (and largely positive) implications of reframing intelligence in terms of social modeling, intersubjectivity, and symbiosis. These include new perspectives on life and evolution, the relationship between humans and technology, and even the nature of free will and consciousness.