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Genie 3 from Google DeepMind is the most mind-blowing technology I've ever seen since starting MLST. This is our exclusive in-person interview with Jack Parker-Holder and Shlomi Fruchter

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Machine Learning Street Talk

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29,719 次观看 • 11 个月前 •via X (Twitter)

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A conversation with the Project Genie team on the path to launching the most powerful world model to date, where they expect to see value from these models in the short term, what comes next, and more : ) Featuring: Jack Parker-Holder Shlomi Fruchter and diego rivas
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A conversation with the Project Genie team on the path to launching the most powerful world model to date, where they expect to see value from these models in the short term, what comes next, and more : ) Featuring: Jack Parker-Holder Shlomi Fruchter and diego rivas

Logan Kilpatrick

56,846 次观看 • 5 个月前

Today, we're joined by Jack Parker-Holder and Shlomi Fruchter, researchers at Google DeepMind, to discuss the recent release of Genie 3, a model capable of generating “playable” virtual worlds. We dig into the evolution of the Genie project and review the current model’s scaled-up capabilities, including creating real-time, interactive, and high-resolution environments. Jack and Shlomi share their perspectives on what defines a world model, the model's architecture, and key technical challenges and breakthroughs, including Genie 3’s visual memory and ability to handle “promptable world events.” Jack, Shlomi, and Sam share their favorite Genie 3 demos, and discuss its potential as a dynamic training environment for embodied AI agents. Finally, we will explore future directions for Genie research. 🗒️ For the full list of resources for this episode, visit the show notes page: 📖 CHAPTERS =============================== 00:00 - Introduction 7:11 - What is a world model? 14:49 - Milestones of Genie research 24:32 - Genie 3 27:46 - Challenges 30:07 - Genie 3 examples 33:48 - Model capabilities 35:49 - Key aspects of the model 39:40 - Consistency as an emergent property 42:11 - Promptable word events 47:24 - SIMA agent 50:56 - Limitations 56:08 - Future directions
1:00:31

Today, we're joined by Jack Parker-Holder and Shlomi Fruchter, researchers at Google DeepMind, to discuss the recent release of Genie 3, a model capable of generating “playable” virtual worlds. We dig into the evolution of the Genie project and review the current model’s scaled-up capabilities, including creating real-time, interactive, and high-resolution environments. Jack and Shlomi share their perspectives on what defines a world model, the model's architecture, and key technical challenges and breakthroughs, including Genie 3’s visual memory and ability to handle “promptable world events.” Jack, Shlomi, and Sam share their favorite Genie 3 demos, and discuss its potential as a dynamic training environment for embodied AI agents. Finally, we will explore future directions for Genie research. 🗒️ For the full list of resources for this episode, visit the show notes page: 📖 CHAPTERS =============================== 00:00 - Introduction 7:11 - What is a world model? 14:49 - Milestones of Genie research 24:32 - Genie 3 27:46 - Challenges 30:07 - Genie 3 examples 33:48 - Model capabilities 35:49 - Key aspects of the model 39:40 - Consistency as an emergent property 42:11 - Promptable word events 47:24 - SIMA agent 50:56 - Limitations 56:08 - Future directions

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12,043 次观看 • 11 个月前

Why make explorable, AI generated worlds? Shlomi Fruchter and Jack Parker-Holder explain how creating diverse and challenging virtual environments can help test and train AI agents safely. 🦺 Watch their conversation about Genie 3 with podcast host, Hannah Fry ↓ Timecodes: 00:00 Coming up 00:54 Intro 02:00 What is Genie 3? 03:00 Demos 06:50 Physics 11:00 Possible scenarios 15:07 Emergent properties 20:35 Veo and Genie 25:00 Hunter's lodge 28:02 Memory 34:52 SIMA and Genie 3 39:13 Searching for interestingness 52:00 AGI and the future 59:23 Hannah's thoughts
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Why make explorable, AI generated worlds? Shlomi Fruchter and Jack Parker-Holder explain how creating diverse and challenging virtual environments can help test and train AI agents safely. 🦺 Watch their conversation about Genie 3 with podcast host, Hannah Fry ↓ Timecodes: 00:00 Coming up 00:54 Intro 02:00 What is Genie 3? 03:00 Demos 06:50 Physics 11:00 Possible scenarios 15:07 Emergent properties 20:35 Veo and Genie 25:00 Hunter's lodge 28:02 Memory 34:52 SIMA and Genie 3 39:13 Searching for interestingness 52:00 AGI and the future 59:23 Hannah's thoughts

Google DeepMind

184,644 次观看 • 10 个月前

Google DeepMind's Jack Parker-Holder says Genie 3 is not an agent. It's an environment. A general-purpose simulator where AI can discover behaviors the way AlphaGo did: by playing, failing, and trying again. In robotics, this could enable agents to finally learn skills transferable outside the lab.
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Google DeepMind's Jack Parker-Holder says Genie 3 is not an agent. It's an environment. A general-purpose simulator where AI can discover behaviors the way AlphaGo did: by playing, failing, and trying again. In robotics, this could enable agents to finally learn skills transferable outside the lab.

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This is the most heartwarming and genuine reaction I've ever seen from the kiss scene
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This guy is at the same time the most serious and unserious person I've ever seen get arrested 😭
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It's happening... Google DeepMind is about to drop Genie 3 This AI can generate interactive 3D worlds with just text... And you can interact with objects in real time 🤯
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This is the most reasonable person I've ever seen on Nons Miraj show. Wow 😳
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Google AI product lead hint Genie 3 is coming you can generate 4D world and interact with 3D objects inside.. look at how they open the car door.. this will be mind blowing
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I tested Google’s world model Genie 3... Then DeepMind told me everything 00:00 - Intro & Authoring Workflow 00:27 - Genie 3 Playtesting & Demos 05:33 - Interview w/ Google DeepMind (Genie 3 co-lead Jack Parker-Holder and Sr. PM Diego Rivas) 06:54 - Wildest emergent behaviors observed 09:02 - The "inception" moment genie simulating itself 10:14 - Use cases for filmmaking, gaming & education 13:08 - Exerting control & promptable world events 15:28 - Solving for spatial memory and longer generation time 17:27 - The future of interactive, branching media feeds 18:57 - Open-endedness & community-driven evolution 20:04 - What's next for Genie 4? Hints! 21:30 - How Nano Banana Pro leveled up Genie 3
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