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The past decade’s series of dramatic AI successes has brought us closer to realizing the dream of the autonomous agent—an artificial system that can learn about its world, make decisions, and set and achieve goals, all with minimal human intervention.
AI is advancing rapidly at the cognitive tasks that make up knowledge work, raising fears among firms, policymakers, and, not least, workers of a “China shock” for white-collar jobs. Neil Thompson will present new research on whether those fears are warranted.
AI is advancing rapidly at the cognitive tasks that make up knowledge work, raising fears among firms, policymakers, and, not least, workers of a “China shock” for white-collar jobs. Neil Thompson will present new research on whether those fears are warranted.
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.
A Center for Neural Data Science Seminar Series
A Center for Neural Data Science Seminar Series
Nature has given us an incredible motif for the autonomous agent. Humans are born with core motivations that drive behavior, and as they gain experience, they develop increasingly sophisticated representations of their worlds, which in turn facilitate increasingly complex behaviors.
How should we attempt to realize this motif for intelligence to create autonomous agents? In this seminar, the speakers will cover a number of efforts aimed at assembling pieces of it—starting with their own research into intrinsic motivation and adaptive “world model” representations, including work inspired by biology and, in particular, human development. They will also describe some of the opportunities language models provide for us to make increasingly autonomous systems.
