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-leaderboardChapters:00:00 DeepMind's Role in Gemini's Development03:49 Gemini 2.0 Updates and Developer Highlights06:08 Agentic Use Cases and Function Calling11:29 Multimodal Capabilities16:15 Putting AI in Production21:06 Gemini's Differentiation and Hardware31:22 Future Vision for Gemini and G Suite Integration35:23 Gemini for Developers39:02 Conclusion and FarewellFollow the hostsFollowAtinFollowConorFollowVikramFollowYashFollow LoganTwitter:@OfficialLoganKLinkedIn:https://www.linkedin.com/in/logankilpatrick/Show NotesTry Gemini for yourself:gemini.google.comGemini for Developers:aistudio.google.comCheck out GalileoTry Galileo
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
Check out Galileo
AI is reshaping infrastructure, strategy, and entire industries. Host Conor Bronsdon talks to the engineers, founders, and researchers building breakthrough AI systems about what it actually takes to ship AI in production, where the opportunities lie, and how leaders should think about the strategic bets ahead.
Chain of Thought translates technical depth into actionable insights for builders and decision-makers. New episodes bi-weekly.
Conor Bronsdon is an angel investor in AI and dev tools, Head of Technical Ecosystem at Modular, and previously led growth at AI startups Galileo and LinearB.