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Turn the Lens with Jeff Frick

Turn the Lens with Jeff Frick

Auteur(s): Jeff Frick
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 Turn the Lens is about exploring the people, topics, and pieces of media that help shape my perspective on the world. The concept behind 'turn the lens' is to look beyond the foreground, beyond the obvious, to see things in a different context, to see things that you might have missed before. Let's get past our own bias and point of view to try and look from a broader point of view, to expand our learning beyond the obvious.© Menlo Creek Media, 2020 All rights reserved. Économie
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  • Pete Florence: Generalist, Scaling Laws, Train One Improve All | Turn the Lens Ep46

    Pete Florence: Generalist, Scaling Laws, Train One Improve All | Turn the Lens Ep46
    Jan 24 2026
    What if training a robot to do ONE thing automatically made it better at EVERYTHING? Pete Florence, Co-founder & CEO of Generalist and former Google DeepMind Senior Research Scientist, joins Jeff Frick at Humanoids Summit 2025 to reveal a breakthrough that fundamentally changes how we think about robot intelligence. The big discovery? Robotics has finally found its scaling laws—just like large language models. At 7 billion parameters, models cross an "intelligence threshold" where more data predictably equals more intelligence. No more hitting walls. No more plateaus. Just continuous improvement. But the real magic is cross-task generalization: when you train on one skill, the robot gets better at all skills. It's not just learning faster—it's learning universally. Pete explains why Generalist is betting on generalist robots (yes, the double meaning is intentional) when specialists have dominated for decades, how smaller models experience "ossification" and literally stop learning, and why reaching a "data-rich regime" of 270,000+ hours of real-world interaction data changed everything. He also introduces fascinating concepts like "physical hallucinations" (when robots confidently do the wrong thing) and why teaching robots epistemic humility—the ability to say "I don't know"—might be more critical than any task-specific training. From his award-winning work on Dense Object Nets at MIT to pioneering RT-2 and PaLM-E at Google DeepMind, Pete has been at the cutting edge of embodied AI. Now with GEN-0, he's proving that foundation models can work in the physical world—with all the scaling properties that made LLMs so powerful. Key Topics: The 7B parameter intelligence threshold breakthroughWhy training one task improves all tasks (cross-skill learning)GEN-0: First embodied foundation model with proven scaling lawsGeneralist vs specialist: Why Pete's betting against conventional wisdomOssification: When models give up and stop learningPhysical hallucinations in robotics270,000+ hours of real-world data and why it mattersThe data-rich regime that enables scalingTeaching robots to know their limitsComparing robotics timelines to autonomous vehicles Guest Bio: Pete Florence is Co-founder & CEO of Generalist, an embodied AI company building foundation models for physical robots. Previously a Senior Research Scientist at Google DeepMind, Pete led groundbreaking research on RT-2 (vision-language-action models) and PaLM-E (embodied multimodal language models). He earned his PhD in Computer Science from MIT under Russ Tedrake, winning multiple Best Paper awards including CoRL 2018 for Dense Object Nets and the IEEE RA-L Best Paper Award 2020. His work has been cited over 20,000 times and featured in the New York Times, WIRED, and CNN. About the Event: Recorded at Humanoids Summit 2025 (December 11-12) at the Computer History Museum in Mountain View, California. The Summit brought together 2,000+ attendees from 400+ companies and 40 countries, featuring leaders from Google DeepMind, Boston Dynamics, Physical Intelligence, and dozens of humanoid robotics startups. Links: Pete Florence: https://www.peteflorence.comGeneralist AI: https://generalistai.comGEN-0 Blog: https://generalistai.com/blog/nov-04-2025-GEN-0RT-2 Research: https://robotics-transformer2.github.ioHumanoids Summit: https://humanoidssummit.com Host: Jeff Frick, Turn the Lens / Work 20XX Episode: 46 Series: Humanoids Summit 2025 Interviews Listen to our full series from Humanoids Summit, including interviews with Carolina Parada (Google DeepMind), Jeff Burnstein (A3), and other robotics leaders.
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    24 min
  • Stop the Slop: Five AI Fundamentals, Smarter Prompts, Real Results | Turn the Lens Ep45

    Stop the Slop: Five AI Fundamentals, Smarter Prompts, Real Results | Turn the Lens Ep45
    Jan 22 2026

    Five game-changing AI tips from my training with Kyle "KMo" Moschetto. Discover the RGCOA framework for prompt engineering, why paying for ChatGPT, Claude, and Gemini is essential for serious work, and how understanding tokens, context windows, and temperature settings can dramatically improve your results. Practical, tested insights you can apply immediately to get more from generative AI tools.

    Stop the Slop: Five AI Fundamentals, Smarter Prompts, Real Results | Turn the Lens with Jeff Frick Ep 45

    YouTube

    https://www.youtube.com/watch?v=oOMin0E1BoA&list=PLZURvMqWbYjk4hbmcR46tNDdXQlrVZgEn

    Transcript and Show Notes

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    6 min
  • Carolina Parada: Embodied AI, Gemini Robotics, Delightful Surprise | Turn the Lens Ep44

    Carolina Parada: Embodied AI, Gemini Robotics, Delightful Surprise | Turn the Lens Ep44
    Jan 19 2026

    Carolina Parada and the team have delivered Gemini Robotics, Google DeepMind's vision-language-action (VLA) foundation model. Gemini Robotics provides the general-purpose 'understanding' enabling robots to go from pixel to action.

    How do you teach a machine to understand the physical world well enough to move through it, manipulate it, and help people in it, when every case is a corner case, never experienced in training?

    Embodied AI. AI with arms and legs and the ability to interact with the real world. Gemini Robotics is designed to generalize across platforms, so it works for robots that walk, roll, fly, and swim, with any end-effector, be it a hand, gripper, pincher, or suction cup. Gemini Robotics is designed to generalize across tasks and skills to respond to just about any request that the robot receives.

    I sat down with Carolina to explore Google DeepMind's approach to embodied AI at the Humanoids Summit 2025, hosted and organized by ALM Ventures at the Computer History Museum in Mountain View, California.

    Carolina has been working on teaching machines to recognize and respond to the environment in more human-centric ways, starting with speech and voice, then computer vision, and now robotics.

    At the heart of her work is Gemini Robotics, a foundation model that takes the multimodal reasoning capabilities of Gemini and extends them into the physical world. It's a VLA, vision-language-action, model. Going beyond "how many cars are in this image?" to "dunk the ball" when playing with a basketball toy. Embodiment-agnostic, it can adapt to control any robot: manipulators, mobile platforms, and the quickly developing humanoids.

    Data, Constitutional AI, teleoperation, video training, good candidates for the top concepts covered. But what impressed me more was her description of bringing new people in to experience the robots, inevitably asking the robots to do things they've never heard before, or interacting in Japanese or another language, only to have the robot respond appropriately, creating 'delight, surprise, and joy.'

    That is a robot future I can get excited about.

    Please join me in welcoming Carolina Parada to Turn the Lens, in collaboration with Humanoids Summit and ALM Ventures.

    This interview is a collaboration between Turn the Lens and Humanoids Summit, and was conducted at the Humanoids Summit SV, Computer History Museum, Mountain View, California, December 12, 2025. Humanoids Summit is organized and hosted by ALM Ventures

    Carolina Parada: Embodied AI, Gemini Robotics, Delightful Surprise | Turn the Lens with Jeff Frick Ep 44

    Learn more about Humanoids Summit at
    http://www.humanoidssummit.com

    YouTube
    https://youtu.be/BUH1CysZX6A

    Trancripit and Show Notes

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    20 min
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