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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.
This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.

This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.
As AI moves beyond language into systems that can perceive, understand, and act in the physical world, a new frontier is emerging: world models—AI systems that build and maintain working representations of real environments to predict how they change in response to action.

As AI moves beyond language into systems that can perceive, understand, and act in the physical world, a new frontier is emerging: world models—AI systems that build and maintain working representations of real environments to predict how they change in response to action.
The question of whether machines can really understand. Lovelace and Searle thought not. Turing thought yes. (Ok that’s not totally accurate, but let’s not ruin a good story.) With the advent of LLMs the question has resurfaced in force, again with some strong skeptics such as Bender et al. In this seminar, Yoav Shoham shares his views, based mostly on work at AI21 Labs. Spoilers: (1) He’s with Turing. (2) LLMs, as currently built, are necessary but not sufficient. (3) The question is more interesting than the answer.