Gemini 3 & Robot Dogs: Inside Google DeepMind's AI Experiments | Paige Bailey

Google DeepMind is reshaping the AI landscape with an unprecedented wave of releases—from Gemini 3 to robotics and even data centers in space.

Paige Bailey, AI Developer Relations Lead at Google DeepMind, joins us to break down the full Google AI ecosystem. From her unique journey as a geophysicist-turned-AI-leader who helped ship GitHub Copilot, to now running developer experience for DeepMind's entire platform, Paige offers an insider's view of how Google is thinking about the future of AI.

The conversation covers the practical differences between Gemini 3 Pro and Flash, when to use the open-source Gemma models, and how tools like Anti-Gravity IDE, Jules, and Gemini CLI fit into developer workflows. Paige also demonstrates Space Math Academy—a gamified NASA curriculum she built using AI Studio, Colab, and Anti-Gravity—showing how modern AI tools enable rapid prototyping.

The discussion then ventures into AI's physical frontier: robotics powered by Gemini on Raspberry Pi, Google's robotics trusted tester program, and the ambitious Project Suncatcher exploring data centers in space.

00:00 Introduction

01:30 Paige's Background & Connection to Modular

02:29 Gemini Integration Across Google Products

03:04 Jules, Gemini CLI & Anti-Gravity IDE Overview

03:48 Gemini 3 Flash vs Pro: Live Demo & Pricing

06:10 Choosing the Right Gemini Model

09:42 Google's Hardware Advantage: TPUs & JAX

10:16 TensorFlow History & Evolution to JAX

11:45 NeurIPS 2025 & Google's Research Culture

14:40 Google Brain to DeepMind: The Merger Story

15:24 Palm II to Gemini: Scaling from 40 People

18:42 Gemma Open Source Models

20:46 Anti-Gravity IDE Deep Dive

23:53 MCP Protocol & Chrome DevTools Integration

26:57 Gemini CLI in Google Colab

28:00 Image Generation & AI Studio Traffic Spikes

28:46 Space Math Academy: Gamified NASA Curriculum

31:31 Vibe Coding: Building with AI Studio & Anti-Gravity

36:02 AI From Bits to Atoms: The Robotics Frontier

36:40 Stanford Puppers: Gemini on Raspberry Pi Robots

38:35 Google's Robotics Trusted Tester Program

40:59 AI in Scientific Research & Automation

42:25 Project Suncatcher: Data Centers in Space

45:00 Sustainable AI Infrastructure

47:14 Non-Dystopian Sci-Fi Futures

47:48 Closing Thoughts & Resources

- Connect with Paige on LinkedIn: https://www.linkedin.com/in/dynamicwebpaige/

- Follow Paige on X: https://x.com/DynamicWebPaige

- Paige's Website: https://webpaige.dev/

- Google DeepMind: https://deepmind.google/

- AI Studio: https://ai.google.dev

Connect with our host Conor Bronsdon:

- Substack – https://conorbronsdon.substack.com/

- LinkedIn https://www.linkedin.com/in/conorbronsdon/

Presented By: Galileo.ai

Download Galileo's Mastering Multi-Agent Systems for free here!: https://galileo.ai/mastering-multi-agent-systems

Topics Covered:

- Gemini 3 Pro vs Flash comparison (pricing, speed, capabilities)

- When to use Gemma open-source models

- Anti-Gravity IDE, Jules, and Gemini CLI workflows

- Google's TPU hardware advantage

- History of TensorFlow, JAX, and Google Brain

- Space Math Academy demo (gamified education)

- AI-powered robotics (Stanford Puppers on Raspberry Pi)

- Project Suncatcher (orbital data centers)