Gemini 2.0 and the evolution of agentic AI with Oriol Vinyals
In this episode, Hannah is joined by Oriol Vinyals, VP of Drastic Research and Gemini co-lead. They discuss the evolution of agents from single-task models to more general-purpose models capable of broader applications, like Gemini. Vinyals guides Hannah through the two-step process behind multi modal models: pre-training (imitation learning) and post-training (reinforcement learning). They discuss the complexities of scaling and the importance of innovation in architecture and training processes. They close on a quick whirlwind tour of some of the new agentic capabilities recently released by Google DeepMind.
Note: To see the full demos, unedited versions, and other videos related to Gemini 2.0 head to our Gemini playlist: https://www.youtube.com/playlist?list=PLqYmG7hTraZD8qyQmEfXrJMpGsQKk-LCY
Additional learning:
https://deepmind.google/
https://www.youtube.com/watch?v=lH74gNeryhQ&
https://youtu.be/64pndvbbokA?si=O9Ep7fD5eF5YUNYe
Thanks to everyone who made this possible, including but not limited to:
Presenter: Professor Hannah Fry
Series Producer: Dan Hardoon
Editor: Rami Tzabar, TellTale Studios
Commissioner & Producer: Emma Yousif
Music composition: Eleni Shaw
Camera Director and Video Editor: Bernardo Resende
Audio Engineer: Perry Rogantin
Video Studio Production: Nicholas Duke
Video Editor: Bilal Merhi
Video Production Design: James Barton
Visual Identity and Design: Eleanor Tomlinson
Commissioned by Google DeepMind

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Artificial intelligence could be one of humanity's most useful inventions. DeepMind aims to build advanced AI to expand our knowledge and find new answers. By solving this one thing, we believe we could help people solve thousands of problems. We’re a te...