Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

The biggest challenge in robotics isn’t building better robots—it’s getting better data. Anastasis Germanidis, co-founder and CEO of Runway, on how world models could break the cycle.

TIME

18,529,066 subscribers

11,114,716 views • 5 months ago •via X (Twitter)

News & Politics Science & Technology

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

🎙️ Jan Liphardt, CEO and co-founder of OpenMind, joins the show to chat about the rapidly evolving world of humanoid robotics, why OpenMind is building an open source operating system for robots, and why they're putting Asimov’s Laws on the blockchain.

🎙️ Jan Liphardt, CEO and co-founder of OpenMind, joins the show to chat about the rapidly evolving world of humanoid robotics, why OpenMind is building an open source operating system for robots, and why they're putting Asimov’s Laws on the blockchain.

Stack Overflow

10,752 views • 5 months ago

It's easy for robots to nail a demo. It's much harder to get them to work reliably in the real world. The bottleneck is data. At Axis Robotics we're building a compounding data engine that combines simulation, ego-centric data and DAgger correction data at scale. Watch our CEO ChrisF(✱,✱) break down the data bottleneck, why messy data can still train good models, and what it takes to get robots out of the lab with blocmates. ⬇️

It's easy for robots to nail a demo. It's much harder to get them to work reliably in the real world. The bottleneck is data. At Axis Robotics we're building a compounding data engine that combines simulation, ego-centric data and DAgger correction data at scale. Watch our CEO ChrisF(✱,✱) break down the data bottleneck, why messy data can still train good models, and what it takes to get robots out of the lab with blocmates. ⬇️

Axis Robotics

22,634 views • 15 days ago

The future of robotics isn't about flashy demos—it's about building robots that can react safely and reliably in the real world, says AMD's Salil Raje. From AMD's AdvancingAI event.

The future of robotics isn't about flashy demos—it's about building robots that can react safely and reliably in the real world, says AMD's Salil Raje. From AMD's AdvancingAI event.

TIME

30,031 views • 29 days ago

World Labs CEO Dr. Fei-Fei Li & SceniX Co-Founder Yunzhu Li on the data bottleneck in robotics and how world models help: "The lack of data in training, the lack of data in evaluation, this is very, very different from language models, where data is abundant on the internet." "And we know that in order for robotics to work, we have to somehow unlock the power of scaling law. But where does that come from?" "It's a profound problem that everybody's battling with in robotics." "We see a lot of unlock in being able to do this whole process through the modeling of the environments." "Being able to create these digital worlds... that's just going to unlock so much more potential for being able to replace all the costly and the unsafe data in the real environments with the data generated from the worlds for robots to be able to do scalable learning and evaluations." Fei-Fei Li Yunzhu Li martin_casado

World Labs CEO Dr. Fei-Fei Li & SceniX Co-Founder Yunzhu Li on the data bottleneck in robotics and how world models help: "The lack of data in training, the lack of data in evaluation, this is very, very different from language models, where data is abundant on the internet." "And we know that in order for robotics to work, we have to somehow unlock the power of scaling law. But where does that come from?" "It's a profound problem that everybody's battling with in robotics." "We see a lot of unlock in being able to do this whole process through the modeling of the environments." "Being able to create these digital worlds... that's just going to unlock so much more potential for being able to replace all the costly and the unsafe data in the real environments with the data generated from the worlds for robots to be able to do scalable learning and evaluations." Fei-Fei Li Yunzhu Li martin_casado

a16z

75,232 views • 28 days ago

Chip design takes years. At RAISE Summit, Ricursive says AI can dramatically speed up the process—and that better chips will in turn enable better AI models, creating a recursive cycle of improvement.

Chip design takes years. At RAISE Summit, Ricursive says AI can dramatically speed up the process—and that better chips will in turn enable better AI models, creating a recursive cycle of improvement.

TIME

4,917,612 views • 1 month ago

the micro1 robotics lab: real world data for intelligent models that co-exist in the physical world. we’re in-the-wild across 75 countries in 6,000+ unique environments collecting data. diverse movements, objects, and settings. the future of AI is as human as you can imagine. join us to start training robots today (link in comments).

the micro1 robotics lab: real world data for intelligent models that co-exist in the physical world. we’re in-the-wild across 75 countries in 6,000+ unique environments collecting data. diverse movements, objects, and settings. the future of AI is as human as you can imagine. join us to start training robots today (link in comments).

Ali Ansari

208,233 views • 5 months ago

.Over the Reality 🌐 Co-Founder & COO Diego DT 🦇🔊 X 🏴 on: → why Web3 + DePIN beats Web2 in spatial data collection → How transparent incentives unlock higher quality real-world data for robots and AI

.Over the Reality 🌐 Co-Founder & COO Diego DT 🦇🔊 X 🏴 on: → why Web3 + DePIN beats Web2 in spatial data collection → How transparent incentives unlock higher quality real-world data for robots and AI

peaq

15,735 views • 1 year ago

The internet was the training set for intelligence Nobody has built the equivalent for the physical world Previously, Lucas Ngoo co-founded Carousell, scaled it $1B+ Now at CortexAI he's collecting the data robotics labs need to train foundation models Cameras, VR headsets, glasses on factory workers, retail workers, everyday people. Recording real-world manipulation work Not building the robot. Not training the model. Collecting what goes in 2026: scale data 2027+: start rolling robots out Initially 90% teleoperation, 10% autonomy While humans step in, the system keeps learning That's the flywheel toward full autonomy 🎙️ Lucas Ngoo, Co-Founder & CEO, CortexAI on Fondo.com Start (full ep in comments)

The internet was the training set for intelligence Nobody has built the equivalent for the physical world Previously, Lucas Ngoo co-founded Carousell, scaled it $1B+ Now at CortexAI he's collecting the data robotics labs need to train foundation models Cameras, VR headsets, glasses on factory workers, retail workers, everyday people. Recording real-world manipulation work Not building the robot. Not training the model. Collecting what goes in 2026: scale data 2027+: start rolling robots out Initially 90% teleoperation, 10% autonomy While humans step in, the system keeps learning That's the flywheel toward full autonomy 🎙️ Lucas Ngoo, Co-Founder & CEO, CortexAI on Fondo.com Start (full ep in comments)

David J Phillips

110,268 views • 5 months ago

Robotics could reshape the global economy—and the balance of geopolitical power. At RAISE Summit, leaders discuss why the race to build and manufacture robots is accelerating.

Robotics could reshape the global economy—and the balance of geopolitical power. At RAISE Summit, leaders discuss why the race to build and manufacture robots is accelerating.

TIME

25,819 views • 1 month ago

Meet Gemini Robotics: our latest AI models designed for a new generation of helpful robots. 🤖 Based on Gemini 2.0, they bring capabilities such as better reasoning, interactivity, dexterity and generalization into the physical world. 🧵

Meet Gemini Robotics: our latest AI models designed for a new generation of helpful robots. 🤖 Based on Gemini 2.0, they bring capabilities such as better reasoning, interactivity, dexterity and generalization into the physical world. 🧵

Google DeepMind

643,002 views • 1 year ago

Language models understand words. World models could help AI understand the world itself. TIME's Tharin Pillay spoke with Oliver Cameron, CEO of Odyssey, at AMD's Advancing AI event:

Language models understand words. World models could help AI understand the world itself. TIME's Tharin Pillay spoke with Oliver Cameron, CEO of Odyssey, at AMD's Advancing AI event:

TIME

49,444 views • 1 month ago

Karol Hausman is the co-founder and CEO of Physical Intelligence, a robotics company building a general-purpose “AI brain for the physical world.” The company has raised more than $1 billion in funding to develop foundation models that allow robots to operate across many machines, environments, and tasks rather than being programmed for a single purpose. In our conversation, we explore: • The moment a lecture from Sergey Levine convinced him to abandon his PhD research direction and pivot fully to deep learning • The case for building a general “AI brain” for the physical world rather than a single specialized robot • The role of real-world data in training robots, the limits of simulation, and how deployment could create a powerful data flywheel • The unique challenges of physical intelligence and why robots must operate with far higher reliability than language models Thank you to the partners who make this possible - Brex: The intelligent finance platform: - Granola: The app that might actually make you love meetings: Timestamps (00:00) Intro (04:05) Karol’s early fascination with robots (18:21) Karol’s entry point to robotics and PhD program (25:49) Combining robotics with LLMs: The Taylor Swift demo (30:48) The 1970s SHRDLU AI experiment (39:40) How research shapes what Physical Intelligence builds (49:07) The return of reinforcement learning in robotics (1:00:00) NVIDIA’s simulation engines (1:07:31) Compensating for missing senses

Karol Hausman is the co-founder and CEO of Physical Intelligence, a robotics company building a general-purpose “AI brain for the physical world.” The company has raised more than $1 billion in funding to develop foundation models that allow robots to operate across many machines, environments, and tasks rather than being programmed for a single purpose. In our conversation, we explore: • The moment a lecture from Sergey Levine convinced him to abandon his PhD research direction and pivot fully to deep learning • The case for building a general “AI brain” for the physical world rather than a single specialized robot • The role of real-world data in training robots, the limits of simulation, and how deployment could create a powerful data flywheel • The unique challenges of physical intelligence and why robots must operate with far higher reliability than language models Thank you to the partners who make this possible - Brex: The intelligent finance platform: - Granola: The app that might actually make you love meetings: Timestamps (00:00) Intro (04:05) Karol’s early fascination with robots (18:21) Karol’s entry point to robotics and PhD program (25:49) Combining robotics with LLMs: The Taylor Swift demo (30:48) The 1970s SHRDLU AI experiment (39:40) How research shapes what Physical Intelligence builds (49:07) The return of reinforcement learning in robotics (1:00:00) NVIDIA’s simulation engines (1:07:31) Compensating for missing senses

Mario Gabriele 🦊

27,871 views • 5 months ago

My first visit to Orangewood, and Co-Founder and CEO Abhinav Das. 00:00 Intro to Orangewood and Founders in Garage. 00:27 Building industrial robot arms you can talk to. 01:01 A look at the robotics technology. 01:24 Demoing the software and training the models. 01:53 The origin story: from a basement to a business. 02:34 The future of humanoid robots and small-scale manufacturing.

My first visit to Orangewood, and Co-Founder and CEO Abhinav Das. 00:00 Intro to Orangewood and Founders in Garage. 00:27 Building industrial robot arms you can talk to. 01:01 A look at the robotics technology. 01:24 Demoing the software and training the models. 01:53 The origin story: from a basement to a business. 02:34 The future of humanoid robots and small-scale manufacturing.

Ilir Aliu

16,804 views • 4 months ago

"AI is unlocking our ability to make general purpose software for robots," says Agility CTO Pras Velagapudi at Nvidia's GTC conference. More on how artificial intelligence is transforming the world of robotics:

"AI is unlocking our ability to make general purpose software for robots," says Agility CTO Pras Velagapudi at Nvidia's GTC conference. More on how artificial intelligence is transforming the world of robotics:

TIME

6,137,587 views • 5 months ago

Former Google CEO Eric Schmidt on the US - China AI race: The U.S. is chasing AGI. China is shipping day-to-day AI apps, and robotics. If Chinese open-source models get good enough, much of the world could end up building on them.

Former Google CEO Eric Schmidt on the US - China AI race: The U.S. is chasing AGI. China is shipping day-to-day AI apps, and robotics. If Chinese open-source models get good enough, much of the world could end up building on them.

The AI Investor

23,224 views • 6 months ago

Introducing 𝐃𝐫𝐞𝐚𝐦𝐆𝐞𝐧! We got humanoid robots to perform totally new 𝑣𝑒𝑟𝑏𝑠 in new environments through video world models. We believe video world models will solve the data problem in robotics. Bringing the paradigm of scaling human hours to GPU hours. Quick 🧵

Introducing 𝐃𝐫𝐞𝐚𝐦𝐆𝐞𝐧! We got humanoid robots to perform totally new 𝑣𝑒𝑟𝑏𝑠 in new environments through video world models. We believe video world models will solve the data problem in robotics. Bringing the paradigm of scaling human hours to GPU hours. Quick 🧵

Joel Jang

117,574 views • 1 year ago