Astonishing Cicero Negotiates and Builds Trust With Humans Using Natural Language

Data Science

Meta AI’s CICERO algorithm — which negotiates and build trust with humans to perform in the top decile at the game of Diplomacy — is (in our view) the most astounding A.I. feat yet. Hear all about it from Alexander Holden Miller.

As published in the prestigious academic journal Science in November, CICERO is capable of using natural-language conversation to coordinate with humans, develop strategic alliances, and ultimately win in Diplomacy, an extremely complex board game.

Excelling in a game with incomplete information and vastly more possible states of play than games previously conquered by A.I. like chess and go would be a wild feat in and of itself, but CICERO’s generative capacity to converse and negotiate in real-time with six other human players in order to strategize victoriously is the truly mind-boggling capability.

To detail for you how the game of Diplomacy works, why Meta chose to tackle this game with A.I., and how they developed a model that competes in the top decile of human Diplomacy players without any other players even catching a whiff that CICERO could possibly be a machine, our Chief Data Scientist, Jon Krohn’s guest in today’s episode is Alexander Holden Miller, a co-author of the CICERO paper.

• Has been working in Meta AI’s Fundamental AI Research group, FAIR, for nearly eight years.
• Currently serves as a Senior Research Engineering Manager within FAIR.
• Has supported researchers working in most ML sub-domains but has been especially involved in conversational A.I. research and more recently reinforcement learning and planning.
• Holds a degree in Computer Science from Cornell University.


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