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Gemini 2.0 and the evolution of agentic AI with Oriol Vinyals
Manage episode 455162396 series 2532352
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 all of the full length demos, including unedited versions, and other videos related to Gemini 2.0 head to YouTube.
Future reading/watching:
- Gemini 2.0
- Decoding Google Gemini with Jeff Dean
- Gaming, Goats & General Intelligence with Frederic Besse
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
—
Subscribe to our YouTube channel
Find us on X
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Please like and subscribe on your preferred podcast platform. Want to share feedback? Or have a suggestion for a guest that we should have on next? Leave us a comment on YouTube and stay tuned for future episodes.
31 episoder
Manage episode 455162396 series 2532352
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 all of the full length demos, including unedited versions, and other videos related to Gemini 2.0 head to YouTube.
Future reading/watching:
- Gemini 2.0
- Decoding Google Gemini with Jeff Dean
- Gaming, Goats & General Intelligence with Frederic Besse
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
—
Subscribe to our YouTube channel
Find us on X
Follow us on Instagram
Add us on Linkedin
Please like and subscribe on your preferred podcast platform. Want to share feedback? Or have a suggestion for a guest that we should have on next? Leave us a comment on YouTube and stay tuned for future episodes.
31 episoder
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