Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

EXCLUSIVE INTERVIEW WITH CHRIS CAMILLO AND AMIT KUKREJA We sat down with Chris Camillo and amit for a full length conversation on the state of humanoid robotics, the timeline, the supply chain, and where the investable opportunities actually are. Here is the full video with timestamps: 0:47 The current...

WOLF_Financial's profile picture

WOLF

481,029 subscribers

26,207 Aufrufe • vor 1 Monat •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

RoboStrategy CEO Andrew Kang sat down with EO to discuss: • The inflection point of robotics • How we could get to $2/hour labor • Manufacturing and supply chain opportunities • The US vs China race in robotics Timestamps: 0:00 Intro to RoboStrategy 1:13 The Figure investment 2:55 Manufacturing opportunities 6:00 Sizing the humanoid market 6:58 The 4th Industrial Revolution 9:57 The real bottleneck of manufacturing 11:45 NVIDIA's open-source play 13:20 US vs China 15:35 Where to build now 19:29 Building a robotics company is hard
21:00

RoboStrategy CEO Andrew Kang sat down with EO to discuss: • The inflection point of robotics • How we could get to $2/hour labor • Manufacturing and supply chain opportunities • The US vs China race in robotics Timestamps: 0:00 Intro to RoboStrategy 1:13 The Figure investment 2:55 Manufacturing opportunities 6:00 Sizing the humanoid market 6:58 The 4th Industrial Revolution 9:57 The real bottleneck of manufacturing 11:45 NVIDIA's open-source play 13:20 US vs China 15:35 Where to build now 19:29 Building a robotics company is hard

RoboStrategy

17,183 Aufrufe • vor 1 Monat

Sergey Levine (Sergey Levine) is one of the world's top robotics researchers and co-founder of Physical Intelligence. We talked about where humanoid robotics is today, thoughts on the Chinese robotics ecosystem, and his predictions for future timelines. In this episode: • Current state of robotics and surprising capabilities so far • Chinese robotics compared to US ecosystem • If OpenAI and Anthropic got into robotics • His top robotics research paper recommendation • Predictions for when humanoid robotics will land Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 00:37 Where are we today 04:20 Most surprising capabilities so far 07:03 The most inspiring real world robotics 08:36 If OpenAI or Anthropic got into robotics 10:22 Chinese robotics 13:15 Will one lab breakout from the rest 16:59 Thoughts on a concrete roadmap 21:03 Generalization and demonstrating it 26:04 Types of data and which is best for robotics 34:34 Why humanoid robotics differs from Waymo 37:10 If humanoid robotics failed here is why 39:55 Are there hot take modeling architectures in robotics 42:05 Thoughts on AI safety in robotics 46:44 Top robotics research paper recommendation 49:35 Why is Boston Dynamics less top of mind 53:47 Advice for his younger self 56:42 Outro
57:38

Sergey Levine (Sergey Levine) is one of the world's top robotics researchers and co-founder of Physical Intelligence. We talked about where humanoid robotics is today, thoughts on the Chinese robotics ecosystem, and his predictions for future timelines. In this episode: • Current state of robotics and surprising capabilities so far • Chinese robotics compared to US ecosystem • If OpenAI and Anthropic got into robotics • His top robotics research paper recommendation • Predictions for when humanoid robotics will land Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 00:37 Where are we today 04:20 Most surprising capabilities so far 07:03 The most inspiring real world robotics 08:36 If OpenAI or Anthropic got into robotics 10:22 Chinese robotics 13:15 Will one lab breakout from the rest 16:59 Thoughts on a concrete roadmap 21:03 Generalization and demonstrating it 26:04 Types of data and which is best for robotics 34:34 Why humanoid robotics differs from Waymo 37:10 If humanoid robotics failed here is why 39:55 Are there hot take modeling architectures in robotics 42:05 Thoughts on AI safety in robotics 46:44 Top robotics research paper recommendation 49:35 Why is Boston Dynamics less top of mind 53:47 Advice for his younger self 56:42 Outro

Ryan Peterman

70,752 Aufrufe • vor 1 Monat

Humanoid robots are improving fast, but flashy demos still hide the harder question: how many are actually working reliably in the real world? Andrew Kang and Humanoid Scott sat down with Herbert Ong to separate the hype from deployment. Timestamps: 00:00 State of Robotics Today 01:42 Demos vs Deployments 09:02 Public Investing Access 16:55 Hardware and AI Bottlenecks 22:38 Physical Intelligence ROI 29:27 Figure Field Notes 34:11 AI Breakthroughs and Scaling 37:51 Robot Demand Outpaces Supply 41:10 Robotics iPhone Moment 47:12 Human Video Scaling Unlock 53:55 Humanoids in Homes Timeline 01:00:14 Safety Privacy and Standards
1:03:23

Humanoid robots are improving fast, but flashy demos still hide the harder question: how many are actually working reliably in the real world? Andrew Kang and Humanoid Scott sat down with Herbert Ong to separate the hype from deployment. Timestamps: 00:00 State of Robotics Today 01:42 Demos vs Deployments 09:02 Public Investing Access 16:55 Hardware and AI Bottlenecks 22:38 Physical Intelligence ROI 29:27 Figure Field Notes 34:11 AI Breakthroughs and Scaling 37:51 Robot Demand Outpaces Supply 41:10 Robotics iPhone Moment 47:12 Human Video Scaling Unlock 53:55 Humanoids in Homes Timeline 01:00:14 Safety Privacy and Standards

RoboStrategy

11,810 Aufrufe • vor 10 Tagen

The missing layer in robotics may be social cognition. Amadej Pzelnik, CEO of Steve Lazarus, on why movement is only part of the problem and what it takes to deploy robots that can operate around people. Plus the latest developments across humanoid robotics. 00:00 Introduction and humanoid robotics news 06:34 Amadej Pzelnik joins Robotico Live 08:56 Why robots need social cognition 14:11 Why ARCHTYP shifted to service robots 18:21 How robots understand people in the real world 22:45 Inside ARCHTYP’s cognitive layer 27:49 Building a robot for social interaction 31:49 Deploying robots in retail and hospitality 36:12 Memory, recognition and personalisation 38:14 What humans will expect from robots Watch now ↓
44:46

The missing layer in robotics may be social cognition. Amadej Pzelnik, CEO of Steve Lazarus, on why movement is only part of the problem and what it takes to deploy robots that can operate around people. Plus the latest developments across humanoid robotics. 00:00 Introduction and humanoid robotics news 06:34 Amadej Pzelnik joins Robotico Live 08:56 Why robots need social cognition 14:11 Why ARCHTYP shifted to service robots 18:21 How robots understand people in the real world 22:45 Inside ARCHTYP’s cognitive layer 27:49 Building a robot for social interaction 31:49 Deploying robots in retail and hospitality 36:12 Memory, recognition and personalisation 38:14 What humans will expect from robots Watch now ↓

XMAQUINA

13,621 Aufrufe • vor 17 Tagen

Not enough people are talking about physical AI and robotics. I sat down with Andrew Kang, one of the best investors of the last decade, to discuss his massive bet on humanoids and robotics. He breaks down the industry, the addressable market, multiple leading companies, and why he launched a publicly-traded fund ($BOT) focused on investing in the top private robotics companies. YouTube: Apple: Spotify: TIMESTAMPS: 0:00 - Intro 1:28 - Why Andrew shifted from crypto to humanoid robots 3:58 - How big is the total addressable market? 8:08 - Building conviction — the $19M bet on Figure AI 16:06 - US vs. China — who wins the robot race? 28:08 - General purpose vs. specialized robots 31:05 - Where does training data come from? 40:24 - Humanoid robots in your everyday life 43:27 - Can Tesla & Elon win the humanoid race? 46:19 - Job displacement & UBI 51:15 - RoboStrategy — the publicly traded venture fund 1:11:17 - What is exciting about Apptronik? 1:13:24 - Addressing the critics
1:20:17

Not enough people are talking about physical AI and robotics. I sat down with Andrew Kang, one of the best investors of the last decade, to discuss his massive bet on humanoids and robotics. He breaks down the industry, the addressable market, multiple leading companies, and why he launched a publicly-traded fund ($BOT) focused on investing in the top private robotics companies. YouTube: Apple: Spotify: TIMESTAMPS: 0:00 - Intro 1:28 - Why Andrew shifted from crypto to humanoid robots 3:58 - How big is the total addressable market? 8:08 - Building conviction — the $19M bet on Figure AI 16:06 - US vs. China — who wins the robot race? 28:08 - General purpose vs. specialized robots 31:05 - Where does training data come from? 40:24 - Humanoid robots in your everyday life 43:27 - Can Tesla & Elon win the humanoid race? 46:19 - Job displacement & UBI 51:15 - RoboStrategy — the publicly traded venture fund 1:11:17 - What is exciting about Apptronik? 1:13:24 - Addressing the critics

Anthony Pompliano 🌪

682,316 Aufrufe • vor 4 Monaten

This week's episode is mostly about robots. Kyle Vogt is one of very few entrepreneurs to found 3 business valued at over a billion dollars - Twitch in 2006, Cruise in 2013, and The Bot Company in 2024. If you've caught any other Uncapped episodes you've probably heard some investors saying that home robots are close and they'll be a giant new market. Kyle Vogt is building them, and talking to him made me as bullish as ever. Timestamps: (0:00) Introduction (0:34) Why robotics is suddenly booming (3:31) Special-purpose vs generalized (5:32) Designing robots people actually use (9:00) Building for scale and affordability (12:17) The myth of humanoids (15:04) Trust, safety, and privacy in your home (17:51) Robotics intelligence (21:01) Why Kyle keeps starting hard companies (22:32) The 100-person rule and elite teams (26:10) How to actually ship (27:28) What home robotics will do first (35:05) Home security and other applications (38:41) Tesla vs Waymo (41:08) When to sell a company (42:41) Marathons
46:25

This week's episode is mostly about robots. Kyle Vogt is one of very few entrepreneurs to found 3 business valued at over a billion dollars - Twitch in 2006, Cruise in 2013, and The Bot Company in 2024. If you've caught any other Uncapped episodes you've probably heard some investors saying that home robots are close and they'll be a giant new market. Kyle Vogt is building them, and talking to him made me as bullish as ever. Timestamps: (0:00) Introduction (0:34) Why robotics is suddenly booming (3:31) Special-purpose vs generalized (5:32) Designing robots people actually use (9:00) Building for scale and affordability (12:17) The myth of humanoids (15:04) Trust, safety, and privacy in your home (17:51) Robotics intelligence (21:01) Why Kyle keeps starting hard companies (22:32) The 100-person rule and elite teams (26:10) How to actually ship (27:28) What home robotics will do first (35:05) Home security and other applications (38:41) Tesla vs Waymo (41:08) When to sell a company (42:41) Marathons

Jack Altman

289,213 Aufrufe • vor 10 Monaten

My conversation with Sergey Levine (Sergey Levine). Sergey is the co-founder of Physical Intelligence -- a company building foundation models that can control any robot to do any task in any environment. The company's thesis is that generality is more scalable than specialization, meaning that a model trained across many different robots and tasks will ultimately outperform any system built to do one thing well (eg, just wash dishes). Sergey is a researcher by background, but I think you will appreciate how practical and commercially grounded this conversation is. We discuss: - Why changing a diaper will be the last task a robot masters - The simulation v. real-world data debate - How multimodal LLMs give robots common sense - Moravec's Paradox + Robot Olympics - Why robots can do long-horizon tasks now - A realistic timeline for robots in our homes I should note that I am an investor in Physical Intelligence -- I made the investment because I believe it is one of the most important companies tackling the problem of robotics. Enjoy! Timestamps: 0:00 Intro 2:39 Defining Physical Intelligence 5:19 The Challenge of Building General Models 6:34 The Stakes and Future of General Purpose Robotics 8:15 Pros and Cons of Humanoid Robots 10:12 Historical Milestones in Robotics Research 15:31 Combining Generative AI and Deep RL 21:24 Moravec's Paradox 25:33 Kitchen Robots 29:30 Simulation vs. Real-World Data 30:48 The Robot Olympics 36:31 The Physiological Reality of Embodiment 38:56 Controversies in the Robotics Community 44:18 What Makes a Great Researcher 48:27 How Businesses Should Prepare for Robotics 54:09 Tracking Progress Through Research Papers 57:02 The Next Step: Mid-Level Reasoning 1:02:00 The Kindest Thing
1:15:15

My conversation with Sergey Levine (Sergey Levine). Sergey is the co-founder of Physical Intelligence -- a company building foundation models that can control any robot to do any task in any environment. The company's thesis is that generality is more scalable than specialization, meaning that a model trained across many different robots and tasks will ultimately outperform any system built to do one thing well (eg, just wash dishes). Sergey is a researcher by background, but I think you will appreciate how practical and commercially grounded this conversation is. We discuss: - Why changing a diaper will be the last task a robot masters - The simulation v. real-world data debate - How multimodal LLMs give robots common sense - Moravec's Paradox + Robot Olympics - Why robots can do long-horizon tasks now - A realistic timeline for robots in our homes I should note that I am an investor in Physical Intelligence -- I made the investment because I believe it is one of the most important companies tackling the problem of robotics. Enjoy! Timestamps: 0:00 Intro 2:39 Defining Physical Intelligence 5:19 The Challenge of Building General Models 6:34 The Stakes and Future of General Purpose Robotics 8:15 Pros and Cons of Humanoid Robots 10:12 Historical Milestones in Robotics Research 15:31 Combining Generative AI and Deep RL 21:24 Moravec's Paradox 25:33 Kitchen Robots 29:30 Simulation vs. Real-World Data 30:48 The Robot Olympics 36:31 The Physiological Reality of Embodiment 38:56 Controversies in the Robotics Community 44:18 What Makes a Great Researcher 48:27 How Businesses Should Prepare for Robotics 54:09 Tracking Progress Through Research Papers 57:02 The Next Step: Mid-Level Reasoning 1:02:00 The Kindest Thing

Patrick OShaughnessy

134,397 Aufrufe • vor 6 Monaten

I spoke with Andrew Kang, Co-Founder and CEO of RoboStrategy. RoboStrategy already holds concentrated positions in industry-defining companies including Figure, Apptronik, Standard Bots, and Dyna Robotics. It is the first publicly listed vehicle purpose-built to give investors liquid exposure to private robotics and physical AI giants, applying the MicroStrategy capital-markets playbook to automation. The first episode of the third season! Full interview now live: Ep 101 | Investing $19M in Humanoids with Zero Robotics Experience 📽️ YouTube: 🎧 Spotify: And thanks for making this happen, intern & Humanoid Scott, Jack 🤖! Timestamps 0:00 Why we built a public fund for private robotics 0:35 Building the MicroStrategy for robotics 1:22 Escaping the tiger parent trap 2:11 Video games are elite training for game theory and critical thinking 6:30 Learning arbitrage in RuneScape and Neopets 7:59 Don't believe experts just because of their titles 10:24 Why investing is just a video game with real money 12:40 Harvard nutrition professors don't know what they're talking about 18:48 Recreating global finance from first principles 19:57 Why robotics is the early days of crypto all over again 21:50 Realizing humanoids are no longer sci-fi 22:58 Why I wrote a $19M check when every VC told me not to 27:24 How SPVs are democratizing venture investing 30:55 Bet on the founder and their execution speed, not the pitch deck 36:39 The math behind a $50 trillion physical labor market 41:44 Applying the MicroStrategy playbook to private markets 45:48 Humanoids are the GPUs of physical labor 47:48 Building a new SoftBank for the robotics era 50:51 Why robotics startups need engineers for attention 54:35 Don't be satisfied with surface level answers
55:49

I spoke with Andrew Kang, Co-Founder and CEO of RoboStrategy. RoboStrategy already holds concentrated positions in industry-defining companies including Figure, Apptronik, Standard Bots, and Dyna Robotics. It is the first publicly listed vehicle purpose-built to give investors liquid exposure to private robotics and physical AI giants, applying the MicroStrategy capital-markets playbook to automation. The first episode of the third season! Full interview now live: Ep 101 | Investing $19M in Humanoids with Zero Robotics Experience 📽️ YouTube: 🎧 Spotify: And thanks for making this happen, intern & Humanoid Scott, Jack 🤖! Timestamps 0:00 Why we built a public fund for private robotics 0:35 Building the MicroStrategy for robotics 1:22 Escaping the tiger parent trap 2:11 Video games are elite training for game theory and critical thinking 6:30 Learning arbitrage in RuneScape and Neopets 7:59 Don't believe experts just because of their titles 10:24 Why investing is just a video game with real money 12:40 Harvard nutrition professors don't know what they're talking about 18:48 Recreating global finance from first principles 19:57 Why robotics is the early days of crypto all over again 21:50 Realizing humanoids are no longer sci-fi 22:58 Why I wrote a $19M check when every VC told me not to 27:24 How SPVs are democratizing venture investing 30:55 Bet on the founder and their execution speed, not the pitch deck 36:39 The math behind a $50 trillion physical labor market 41:44 Applying the MicroStrategy playbook to private markets 45:48 Humanoids are the GPUs of physical labor 47:48 Building a new SoftBank for the robotics era 50:51 Why robotics startups need engineers for attention 54:35 Don't be satisfied with surface level answers

Ilir Aliu

16,683 Aufrufe • vor 2 Monaten

Every conversation I have with Dylan Patel, I'm really just trying to understand the supply and demand of tokens. This is a unique episode in that it's entirely dedicated to talking about both sides of that equation. We discuss: - The infinite demand for the newest models - SemiAnalysis going from $10K on AI spend to $7M - Mythos and Anthropic's compute problem - Why TSMC spending $100B on CapEx could cause a shortage - Robotics as next demand wave - Why memory prices will double again This is my second conversation with Dylan and find myself needing to speak with him more and more often to make sense of it all. Enjoy! Timestamps: 0:00 Intro 1:00 Surging AI Spend 10:27 Token Demand 16:21 When Ideas Are Cheap and Execution is Easy 20:46 Model Hoarding 22:34 Robotics 27:03 The Compute Bottleneck 30:26 The AI Permanent Underclass 31:39 Supply Chain Reality 37:47 CPUs 42:54 Predictions: Public Backlash
45:33

Every conversation I have with Dylan Patel, I'm really just trying to understand the supply and demand of tokens. This is a unique episode in that it's entirely dedicated to talking about both sides of that equation. We discuss: - The infinite demand for the newest models - SemiAnalysis going from $10K on AI spend to $7M - Mythos and Anthropic's compute problem - Why TSMC spending $100B on CapEx could cause a shortage - Robotics as next demand wave - Why memory prices will double again This is my second conversation with Dylan and find myself needing to speak with him more and more often to make sense of it all. Enjoy! Timestamps: 0:00 Intro 1:00 Surging AI Spend 10:27 Token Demand 16:21 When Ideas Are Cheap and Execution is Easy 20:46 Model Hoarding 22:34 Robotics 27:03 The Compute Bottleneck 30:26 The AI Permanent Underclass 31:39 Supply Chain Reality 37:47 CPUs 42:54 Predictions: Public Backlash

Patrick OShaughnessy

1,092,859 Aufrufe • vor 5 Monaten

New Episode. Nils Pihl (Nils), CEO of Auki Labs, discuss the "Real World Web" and making physical spaces accessible to robots. We dive into decentralized mapping and Auki’s latest retail deployments. Nils also shares his take on the US-China robotics race, drawing on 15 years of building ventures in the heart of China’s tech ecosystem. 2:05 Nils' journey into the technology 8:36 Six layers of Robotics value chain 11:00 Use case for AUKI's perception stack 17:04 Compute challenge of distributed mapping 20:16 Decentralized solution to privacy 22:36 Programmable robots vs closed approach 25:43 Most valuable layers or robotics ecosystem 28:53 Behind China's rapid humanoid boom 36:06 140 humanoid OEMs, who's gonna win 41:32 US-China geopolitics 44:52 What can the west do to compete with China 46:55 Technology adoption in Asian countries 54:01 Memes
1:04:36

New Episode. Nils Pihl (Nils), CEO of Auki Labs, discuss the "Real World Web" and making physical spaces accessible to robots. We dive into decentralized mapping and Auki’s latest retail deployments. Nils also shares his take on the US-China robotics race, drawing on 15 years of building ventures in the heart of China’s tech ecosystem. 2:05 Nils' journey into the technology 8:36 Six layers of Robotics value chain 11:00 Use case for AUKI's perception stack 17:04 Compute challenge of distributed mapping 20:16 Decentralized solution to privacy 22:36 Programmable robots vs closed approach 25:43 Most valuable layers or robotics ecosystem 28:53 Behind China's rapid humanoid boom 36:06 140 humanoid OEMs, who's gonna win 41:32 US-China geopolitics 44:52 What can the west do to compete with China 46:55 Technology adoption in Asian countries 54:01 Memes

The Humanoid Hub

39,794 Aufrufe • vor 7 Monaten

Open source AI just became the biggest policy fight in tech. Our full conversation with Ben Horowitz, where he tells Theo and Sofia why banning open source is nearly impossible, why it's historically the safer path, the risk of one company controlling AI and why distillation isn't the threat people claim. 01:21 The Nvidia-backed open letter on open-weight AI 01:49 The OpenAI–Hugging Face hacking incident 02:27 Why you can't actually ban open source 03:05 Historically, open source has been safer (Linux vs. Windows) 05:17 Jensen's Twitter account and the letter's significance 07:25 China, "sleeper agent" models, and national security risk 09:23 Anthropic defying the US government 15:18 The danger of building your business on Anthropic 18:51 BYD, EVs, and rebuilding US manufacturing 21:30 Why would a company ever release an open model? 23:58 The DeepSeek moment: why nothing actually changed 28:25 Paying 100x more for an AI researcher vs. a janitor 29:06 AI art, the "slop" problem, and a coming renaissance benahorowitz.eth Theo Jaffee sof 𓋹
33:01

Open source AI just became the biggest policy fight in tech. Our full conversation with Ben Horowitz, where he tells Theo and Sofia why banning open source is nearly impossible, why it's historically the safer path, the risk of one company controlling AI and why distillation isn't the threat people claim. 01:21 The Nvidia-backed open letter on open-weight AI 01:49 The OpenAI–Hugging Face hacking incident 02:27 Why you can't actually ban open source 03:05 Historically, open source has been safer (Linux vs. Windows) 05:17 Jensen's Twitter account and the letter's significance 07:25 China, "sleeper agent" models, and national security risk 09:23 Anthropic defying the US government 15:18 The danger of building your business on Anthropic 18:51 BYD, EVs, and rebuilding US manufacturing 21:30 Why would a company ever release an open model? 23:58 The DeepSeek moment: why nothing actually changed 28:25 Paying 100x more for an AI researcher vs. a janitor 29:06 AI art, the "slop" problem, and a coming renaissance benahorowitz.eth Theo Jaffee sof 𓋹

MTS

11,246 Aufrufe • vor 2 Monaten

AI NEWS THIS WEEK: Robots beat human world records at the Humanoid Olympics, Unitree rings the bell in Shanghai, and Google bids $10M for Spirit Airlines' data in bankruptcy court. Plus we break down Skild AI's S1 model: their new robotics foundation model that can learn from one example. 0:57 Robots Break Three World Records In Beijing 4:30 Why Grabbing Beans Is Harder Than Beating Usain Bolt 9:14 Unitree Goes Public — And Why The Supply Chain Sits In China 12:29 Skild AI's S1: Learns Tasks With Only 1 Video 16:20 The ChatGPT Moment For Robotics 21:04 Google Bids $10M For Spirit Airlines' Data 23:35 What's Valuable Inside A Digital Estate FULL EPISODE LINK BELOW Lightspeed Josh Machiz
30:32

AI NEWS THIS WEEK: Robots beat human world records at the Humanoid Olympics, Unitree rings the bell in Shanghai, and Google bids $10M for Spirit Airlines' data in bankruptcy court. Plus we break down Skild AI's S1 model: their new robotics foundation model that can learn from one example. 0:57 Robots Break Three World Records In Beijing 4:30 Why Grabbing Beans Is Harder Than Beating Usain Bolt 9:14 Unitree Goes Public — And Why The Supply Chain Sits In China 12:29 Skild AI's S1: Learns Tasks With Only 1 Video 16:20 The ChatGPT Moment For Robotics 21:04 Google Bids $10M For Spirit Airlines' Data 23:35 What's Valuable Inside A Digital Estate FULL EPISODE LINK BELOW Lightspeed Josh Machiz

Claire Zau

10,254 Aufrufe • vor 1 Monat

Elon Musk revealed the 3 hardest challenges for humanoid robots and how Tesla is solving them There are really only three hard things for humanoid robots: - Real-world intelligence - ⁠The hand and - ⁠Scale manufacturing "I haven’t seen any demo robots that have a great hand with all the degrees of freedom of a human hand. But Optimus does have that" To reach human-level dexterity, Tesla had to design custom actuators, motors, gears, power electronics, controls, and sensors, everything from physics first principles There is no supply chain for this "From an electromechanical standpoint, the hand is more difficult than everything else combined. The human hand turns out to be quite something" This is why Optimus is on a completely different level. Tesla is solving the hardest problems from the ground up
0:55

Elon Musk revealed the 3 hardest challenges for humanoid robots and how Tesla is solving them There are really only three hard things for humanoid robots: - Real-world intelligence - ⁠The hand and - ⁠Scale manufacturing "I haven’t seen any demo robots that have a great hand with all the degrees of freedom of a human hand. But Optimus does have that" To reach human-level dexterity, Tesla had to design custom actuators, motors, gears, power electronics, controls, and sensors, everything from physics first principles There is no supply chain for this "From an electromechanical standpoint, the hand is more difficult than everything else combined. The human hand turns out to be quite something" This is why Optimus is on a completely different level. Tesla is solving the hardest problems from the ground up

X Freeze

20,796 Aufrufe • vor 7 Monaten

There are over 90 robot gyms launching in China right now. 100+ robots per center. We are in the robot data gold rush. China's humanoid makers now ship 97% of all humanoids globally. The central government just put $138 billion into a robotics venture fund. And this is only the tip of the iceberg. Robots need an ungodly amount of data to work in the real world. The biggest bottleneck isn't hardware, it's data. So a whole industry appeared overnight to feed them. Welcome to our generation's gold rush: the robot data gold rush. We made a full video on it. We cover why it's such an insane business, how it actually works, the shady stuff (yes, sweatshops for robot data are a thing), and why this might be the completely wrong approach.
17:42

There are over 90 robot gyms launching in China right now. 100+ robots per center. We are in the robot data gold rush. China's humanoid makers now ship 97% of all humanoids globally. The central government just put $138 billion into a robotics venture fund. And this is only the tip of the iceberg. Robots need an ungodly amount of data to work in the real world. The biggest bottleneck isn't hardware, it's data. So a whole industry appeared overnight to feed them. Welcome to our generation's gold rush: the robot data gold rush. We made a full video on it. We cover why it's such an insane business, how it actually works, the shady stuff (yes, sweatshops for robot data are a thing), and why this might be the completely wrong approach.

Andreas Klinger 🦾

13,810 Aufrufe • vor 1 Monat

It was a great show at Automate for Ati Robotics. There is a clear vibe shift in robotics demand in US manufacturing. There is a huge intent to get robots now compared to earlier when people were evaluating robots. While our pallet mover and Tugger were our workhorses with folks looking to deploy immediately, the show stealer was our industrial humanoid, Sherpa Mecha. Many people were surprised to see we did the actuators and had a very novel arm design (motors in shoulder, cable driven, carbon fiber arms) compared to most folks who have put together Chinese arms with software on top. All our products are made with first principles thinking and this is no different. Focused usecases and real deployments will win the market. We will get to real deployments much faster (next summer) and beta deployments start this year itself. We already have a global customer in both US and India where we will be deploying the Mecha. We also move into our new facility to assemble the robots near Detroit in July. Never been a better time to be in robotics. Super excited!
0:50

It was a great show at Automate for Ati Robotics. There is a clear vibe shift in robotics demand in US manufacturing. There is a huge intent to get robots now compared to earlier when people were evaluating robots. While our pallet mover and Tugger were our workhorses with folks looking to deploy immediately, the show stealer was our industrial humanoid, Sherpa Mecha. Many people were surprised to see we did the actuators and had a very novel arm design (motors in shoulder, cable driven, carbon fiber arms) compared to most folks who have put together Chinese arms with software on top. All our products are made with first principles thinking and this is no different. Focused usecases and real deployments will win the market. We will get to real deployments much faster (next summer) and beta deployments start this year itself. We already have a global customer in both US and India where we will be deploying the Mecha. We also move into our new facility to assemble the robots near Detroit in July. Never been a better time to be in robotics. Super excited!

Saurabh Chandra

11,196 Aufrufe • vor 3 Monaten

🦔Workers in India are wearing head-mounted cameras for 12 cents an hour to collect training data for humanoid robots. The footage of them doing everyday tasks like cooking, cleaning, sorting, and walking through public spaces gets sold to robotics companies building the models meant to replace those same kinds of jobs in higher-wage countries. The arrangement has been running for roughly two years. Workers do not own the data, do not get residuals, and in many cases are not told what their footage is being used to train. My Take The workers wearing the cameras live in a country where robotics automation will hit decades later, so they are training their own future replacements at a delay that hides the consequence from them personally. The companies buying the data are mostly US and Chinese, building humanoid robots aimed at warehouses, retail, and service jobs in countries paying $15 to $25 an hour rather than 12 cents. Robotics companies need motion data that mimics how humans actually move through real environments, and synthetic data has not been good enough yet. Paying 12 cents an hour in Bengaluru is cheaper than running motion capture studios in Boston, and it works at scale because the worker absorbs the cost of the camera, the discomfort of wearing it, and the long-term loss of any rights to their own movement data. The robotics labor market that eventually emerges from this footage will displace far more wages than the data collection cost to gather. That is the trade investors funding humanoid robotics startups are betting will pay off, and the workers in the videos are the ones paying the tab up front. Hedgie🤗
0:43

🦔Workers in India are wearing head-mounted cameras for 12 cents an hour to collect training data for humanoid robots. The footage of them doing everyday tasks like cooking, cleaning, sorting, and walking through public spaces gets sold to robotics companies building the models meant to replace those same kinds of jobs in higher-wage countries. The arrangement has been running for roughly two years. Workers do not own the data, do not get residuals, and in many cases are not told what their footage is being used to train. My Take The workers wearing the cameras live in a country where robotics automation will hit decades later, so they are training their own future replacements at a delay that hides the consequence from them personally. The companies buying the data are mostly US and Chinese, building humanoid robots aimed at warehouses, retail, and service jobs in countries paying $15 to $25 an hour rather than 12 cents. Robotics companies need motion data that mimics how humans actually move through real environments, and synthetic data has not been good enough yet. Paying 12 cents an hour in Bengaluru is cheaper than running motion capture studios in Boston, and it works at scale because the worker absorbs the cost of the camera, the discomfort of wearing it, and the long-term loss of any rights to their own movement data. The robotics labor market that eventually emerges from this footage will displace far more wages than the data collection cost to gather. That is the trade investors funding humanoid robotics startups are betting will pay off, and the workers in the videos are the ones paying the tab up front. Hedgie🤗

Hedgie

162,060 Aufrufe • vor 4 Monaten

Elon just dropped a MAJOR nugget on how Tesla is going to be training Optimus to do real world tasks. They are building an Optimus Academy, which is a large scale, dedicated real-world training facility to accelerate the development of Optimus. The Academy will deploy thousands of Optimus units, potentially 10,000 to 30,000 robots, in a controlled realistic environment where they perform self-play, experiment with tasks, iterate on behaviors, and continuously generate training data through trial and error. The Tesla bots will also run millions of simulations in Tesla’s high-fidelity physics-accurate engine, allowing Optimus to close the “sim-to-real gap” by using these real-world observations to refine and validate the simulations! “You’re actually highlighting an important limitation and difference from cars. We’ll soon have 10 million cars on the road. It’s hard to duplicate that massive training flywheel. For the robot, what we’re going to need to do is build a lot of robots and put them in kind of an Optimus Academy so they can do self-play in reality. We’re actually building that out. We can have at least 10,000 Optimus robots, maybe 20-30,000, that are doing self-play and testing different tasks. Tesla has quite a good reality generator, a physics-accurate reality generator, that we made for the cars. We’ll do the same thing for the robots. We actually have done that for the robots. So you have a few tens of thousands of humanoid robots doing different tasks. You can do millions of simulated robots in the simulated world. You use the tens of thousands of robots in the real world to close the simulation to reality gap. Close the sim-to-real gap.”
1:20

Elon just dropped a MAJOR nugget on how Tesla is going to be training Optimus to do real world tasks. They are building an Optimus Academy, which is a large scale, dedicated real-world training facility to accelerate the development of Optimus. The Academy will deploy thousands of Optimus units, potentially 10,000 to 30,000 robots, in a controlled realistic environment where they perform self-play, experiment with tasks, iterate on behaviors, and continuously generate training data through trial and error. The Tesla bots will also run millions of simulations in Tesla’s high-fidelity physics-accurate engine, allowing Optimus to close the “sim-to-real gap” by using these real-world observations to refine and validate the simulations! “You’re actually highlighting an important limitation and difference from cars. We’ll soon have 10 million cars on the road. It’s hard to duplicate that massive training flywheel. For the robot, what we’re going to need to do is build a lot of robots and put them in kind of an Optimus Academy so they can do self-play in reality. We’re actually building that out. We can have at least 10,000 Optimus robots, maybe 20-30,000, that are doing self-play and testing different tasks. Tesla has quite a good reality generator, a physics-accurate reality generator, that we made for the cars. We’ll do the same thing for the robots. We actually have done that for the robots. So you have a few tens of thousands of humanoid robots doing different tasks. You can do millions of simulated robots in the simulated world. You use the tens of thousands of robots in the real world to close the simulation to reality gap. Close the sim-to-real gap.”

Teslaconomics

42,563 Aufrufe • vor 8 Monaten