Chain of Thought

The Making of Gemini 2.0: DeepMind's Approach to AI Development and Deployment | Logan Kilpatrick


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Google’s strength in AI has often seemed to get lost in the midst of OpenAI announcements or DeepSeek fervor - yet Gemini 2.0 is more than good for many tasks; it’s the model to beat - and we have the research to back it up. 

This week, Logan Kilpatrick, senior product manager at Google DeepMind, joins us to discuss Gemini’s creation story, its emergence as the premiere model in the AI race, and why the launch of Gemini 2.0 is great news for developers.

During the conversation Conor and Logan explore the exciting world of multimodal AI, Gemini's strengths in agentic use cases, and its unique approach to function calling, compositional function calling, and the seamless integration of tools like search and code execution.

They also chat about Logan’s vision for a future where AI interacts with the world more naturally, offering a view of the potential of vision-first AI agents, and why Google's hardware advantage is enabling Gemini's impressive performance and long context capabilities. 

Follow along with the discussion using Galileo’s AI Agent Leaderboard:https://huggingface.co/spaces/galileo-ai/agent-leaderboard


Chapters:00:00 DeepMind's Role in Gemini's Development

03:49 Gemini 2.0 Updates and Developer Highlights

06:08 Agentic Use Cases and Function Calling

11:29 Multimodal Capabilities

16:15 Putting AI in Production

21:06 Gemini's Differentiation and Hardware

31:22 Future Vision for Gemini and G Suite Integration

35:23 Gemini for Developers

39:02 Conclusion and Farewell


Follow the hosts

Follow⁠⁠⁠Atin⁠⁠⁠

Follow⁠⁠⁠Conor⁠⁠

Follow⁠Vikram⁠

Follow⁠⁠⁠Yash⁠⁠⁠


Follow Logan

Twitter:@OfficialLoganK

LinkedIn:https://www.linkedin.com/in/logankilpatrick/


Show Notes

Try Gemini for yourself:gemini.google.com

Gemini for Developers:aistudio.google.com


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Chain of ThoughtBy Galileo