About the talk
Despite amazing progress in generative AI, even the largest and smartest large language models have serious limitations in their reasoning abilities, as shown by results on game-playing benchmarks.
On the other hand, simulation-based AI (SBAI) agents make intelligent decisions based on the statistics of simulations using a forward model of a problem domain, providing a complementary type of intelligence. SBAI algorithms have very attractive properties, including instant adaptation to new problems, tunable intelligence and some degree of explainability.
In this talk I’ll present recent results on combining SBAI with LLMs to develop capable game-playing agents, and argue that—right now—it’s an especially good time to be an AI engineer.