Загрузка видео...

Не удалось загрузить видео

На главную

Intelligence Factory is building human intelligence for robots. They train general-purpose manipulation models on human demonstration data (vision, action, and touch), then deploy them in warehouses, grocery stores, and data centers. Congrats on the launch, Yash and Jalaj!

ycombinator's profile picture

Y Combinator

1,648,359 subscribers

44,765 просмотров • 3 месяцев назад •via X (Twitter)

Наука и технологии
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Liva AI (@thelivaAI) provides high-quality human voice and video data for companies building realistic AI models. Congrats on the launch, aoi and Ashley!
0:53

Liva AI (@thelivaAI) provides high-quality human voice and video data for companies building realistic AI models. Congrats on the launch, aoi and Ashley!

Y Combinator

43,106 просмотров • 1 год назад

.@oximyhq shows enterprises everything their employees do with AI. Which tools, how much they cost, and where sensitive data is going. One platform for discovery, spend intelligence, and data protection. Congrats on the launch Naman Ambavi!
1:29

.@oximyhq shows enterprises everything their employees do with AI. Which tools, how much they cost, and where sensitive data is going. One platform for discovery, spend intelligence, and data protection. Congrats on the launch Naman Ambavi!

Y Combinator

42,311 просмотров • 7 месяцев назад

Embodied intelligence can’t afford bad data. Perle Labs is building AI data infrastructure designed for this reality: → Human-verified, expert-validated work → On-chain auditability → Sovereign and enterprise-grade design Built to benefit everyone.
0:35

Embodied intelligence can’t afford bad data. Perle Labs is building AI data infrastructure designed for this reality: → Human-verified, expert-validated work → On-chain auditability → Sovereign and enterprise-grade design Built to benefit everyone.

Perle Labs

2,693,032 просмотров • 7 месяцев назад

Heard some people like wheels？😁 Humanoid robots are the ideal form of general-purpose robots (perfect for general AI and human-derived data). They can work without wheels — but they can also have wheels if they want. Whatever works.
1:14

Heard some people like wheels？😁 Humanoid robots are the ideal form of general-purpose robots (perfect for general AI and human-derived data). They can work without wheels — but they can also have wheels if they want. Whatever works.

Unitree

8,166,866 просмотров • 4 месяцев назад

Today I’m excited to introduce micro1 Intelligence, the world’s most advanced platform for training frontier AI models. Achieving AGI is bottlenecked by one main thing: high-quality data. Data based on real-world environments that capture human expert workflows, complex decision-making, and reward signals models need to learn. With micro1 Intelligence, frontier labs can train on RL environments across every subject matter all in one place.
1:33

Today I’m excited to introduce micro1 Intelligence, the world’s most advanced platform for training frontier AI models. Achieving AGI is bottlenecked by one main thing: high-quality data. Data based on real-world environments that capture human expert workflows, complex decision-making, and reward signals models need to learn. With micro1 Intelligence, frontier labs can train on RL environments across every subject matter all in one place.

Ali Ansari

333,129 просмотров • 9 месяцев назад

Chelsea Finn (Chelsea Finn) on building general-purpose robotics, and bringing intelligence into the physical world. At AI Startup School in San Francisco. 00:00 - General Purpose Robots 00:11 - Challenges in Robotics Applications 00:57 - Physical Intelligence: A New Approach 01:47 - Learning from Language Models 02:08 - Data Sources for Training Robots 03:32 - Training with Real-World Data 04:39 - Initial Successes and Challenges 09:10 - Breakthrough in Robot Training 11:03 - Improving Performance 15:43 - Expanding Capabilities 17:34 - Robots in Unseen Environments 25:54 - Handling Open-Ended Prompts 29:36 - Evaluating Robot Performance 30:03 - Future Directions and Challenges 31:27 - Audience Q&A
44:52

Chelsea Finn (Chelsea Finn) on building general-purpose robotics, and bringing intelligence into the physical world. At AI Startup School in San Francisco. 00:00 - General Purpose Robots 00:11 - Challenges in Robotics Applications 00:57 - Physical Intelligence: A New Approach 01:47 - Learning from Language Models 02:08 - Data Sources for Training Robots 03:32 - Training with Real-World Data 04:39 - Initial Successes and Challenges 09:10 - Breakthrough in Robot Training 11:03 - Improving Performance 15:43 - Expanding Capabilities 17:34 - Robots in Unseen Environments 25:54 - Handling Open-Ended Prompts 29:36 - Evaluating Robot Performance 30:03 - Future Directions and Challenges 31:27 - Audience Q&A

Y Combinator

129,834 просмотров • 1 год назад

AI is trained on human creativity and intelligence, funded by federal research using taxpayer dollars, and powered by data centers built on American land. The success of AI should belong to all of us. It’s time to tax AI and invest in people.
2:38

AI is trained on human creativity and intelligence, funded by federal research using taxpayer dollars, and powered by data centers built on American land. The success of AI should belong to all of us. It’s time to tax AI and invest in people.

Elizabeth Warren

485,822 просмотров • 3 месяцев назад

Collecting robot data at scale is key to deploying working manipulation policies, and the team from Tutor Intelligence Tutor is here to tell us about how to accomplish it. Their new announcement: a massive, 100-robot “data factory,” with a behind-the-scenes look at how to build a teleoperation platform and how to make robots and policies that are useful for their customers. Tutor Intelligence is a full-stack robotics company: they build robot arms, they sell robot arms, they write the software and they train neural networks. Josh Gruenstein, Jesse Michel, Shiraz, and Joe McCalmon, and Joe McCalmon join us to tell us more about how they scale both teleop data and human interventions from their teleoperators in order to train the policies they need. Watch Episode #85 of RoboPapers, with Chris Paxton and Jiafei Duan, to learn more!
1:01:03

Collecting robot data at scale is key to deploying working manipulation policies, and the team from Tutor Intelligence Tutor is here to tell us about how to accomplish it. Their new announcement: a massive, 100-robot “data factory,” with a behind-the-scenes look at how to build a teleoperation platform and how to make robots and policies that are useful for their customers. Tutor Intelligence is a full-stack robotics company: they build robot arms, they sell robot arms, they write the software and they train neural networks. Josh Gruenstein, Jesse Michel, Shiraz, and Joe McCalmon, and Joe McCalmon join us to tell us more about how they scale both teleop data and human interventions from their teleoperators in order to train the policies they need. Watch Episode #85 of RoboPapers, with Chris Paxton and Jiafei Duan, to learn more!

RoboPapers

36,041 просмотров • 3 месяцев назад

Meta's Joe Spisak explains how AI models can train themselves by generating images, asking itself questions about them, and choosing the best answers, in order to move beyond human data and human fine-tuning, and teach itself from synthetic data
1:13

Meta's Joe Spisak explains how AI models can train themselves by generating images, asking itself questions about them, and choosing the best answers, in order to move beyond human data and human fine-tuning, and teach itself from synthetic data

Tsarathustra

42,390 просмотров • 1 год назад

🇮🇳 Rural India shapes global AI models Tending crops and then logging on for data labelling, Chandmani Kerketta, 27, is helping power an artificial intelligence revolution. The work is essential for machine learning: data labelling, annotation and quality checks.
2:22

🇮🇳 Rural India shapes global AI models Tending crops and then logging on for data labelling, Chandmani Kerketta, 27, is helping power an artificial intelligence revolution. The work is essential for machine learning: data labelling, annotation and quality checks.

AFP News Agency

38,176 просмотров • 7 месяцев назад

Coming from someone who actually is credentialed on the human and environmental impacts on these hyperscale data centers, and not funded by China.
2:23

Coming from someone who actually is credentialed on the human and environmental impacts on these hyperscale data centers, and not funded by China.

Kristen Meghan👩‍🔬🐻

323,285 просмотров • 12 дней назад

is building full-stack data science AI agents that turn raw data into insights and answers in minutes, not days. Putting the power of data-driven decisions into anyone's hands. Congrats on the launch, matin and @whyispaper!
1:11

is building full-stack data science AI agents that turn raw data into insights and answers in minutes, not days. Putting the power of data-driven decisions into anyone's hands. Congrats on the launch, matin and @whyispaper!

Y Combinator

30,324 просмотров • 1 год назад

Asimov (Asimov) pays households and businesses worldwide to record their daily routines, generating thousands of hours a day of diverse human movement data to train humanoid robots. They've built a global network, along with the full stack, from proprietary collection hardware to annotation tooling, and are already providing data to the largest robotics companies in the world. Congrats on the launch, Lyem Ningthou and Anshul!
0:44

Asimov (Asimov) pays households and businesses worldwide to record their daily routines, generating thousands of hours a day of diverse human movement data to train humanoid robots. They've built a global network, along with the full stack, from proprietary collection hardware to annotation tooling, and are already providing data to the largest robotics companies in the world. Congrats on the launch, Lyem Ningthou and Anshul!

Y Combinator

74,683 просмотров • 6 месяцев назад

Constellation (Constellation Space) predicts satellite network failures before they happen and automatically reroutes traffic in seconds—no human intervention, no data loss. Congrats on the launch Kamran Majid, Raaid Kabir, Laith, omeed!
0:49

Constellation (Constellation Space) predicts satellite network failures before they happen and automatically reroutes traffic in seconds—no human intervention, no data loss. Congrats on the launch Kamran Majid, Raaid Kabir, Laith, omeed!

Y Combinator

16,970 просмотров • 8 месяцев назад

Ever wondered what robots 🤖 could achieve if they could not just see – but also feel and hear? Introducing FuSe: a recipe for finetuning large vision-language-action (VLA) models with heterogeneous sensory data, such as vision, touch, sound, and more. Details in the thread 👇
0:49

Ever wondered what robots 🤖 could achieve if they could not just see – but also feel and hear? Introducing FuSe: a recipe for finetuning large vision-language-action (VLA) models with heterogeneous sensory data, such as vision, touch, sound, and more. Details in the thread 👇

Carlo Sferrazza

46,111 просмотров • 1 год назад

1/🧠Humans are the best robot data source — but video alone misses one thing: force. 2/🙁Tactile gloves capture force — but they're costly and block the real touch manipulation depends on. 3/💪Maybe the future of touch lives on your wrist: surface EMG reads the muscles that cause force — tactile sensing without ever touching a tactile sensor. 4/🔥Want a fully open-source framework — hardware + software — to train your own force-aware learn-from-human-data robot policy? 🚀We introduce ForceBand: Learning Forceful Manipulation with sEMG -- bring force into human videos with sEMG, for force-aware manipulation ⬇️ ✦ Zero-Shot Human-to-Robot Transfer ✦ Force Beyond Vision ✦ Free-Hand Force Sensing ✦ Collect by Anyone, Anytime, Anywhere ✦ Deploy on Any Robot, Any Camera, Any Environment ✦ Open-Source & Low-Cost & Easy-to-Implement Let's squeeze every bit of signal out of human data, and let robots feel the force! 🌐 Website: 📄 Paper: 💻 Code: 🎥 Video: 🧵 1/n
1:48

1/🧠Humans are the best robot data source — but video alone misses one thing: force. 2/🙁Tactile gloves capture force — but they're costly and block the real touch manipulation depends on. 3/💪Maybe the future of touch lives on your wrist: surface EMG reads the muscles that cause force — tactile sensing without ever touching a tactile sensor. 4/🔥Want a fully open-source framework — hardware + software — to train your own force-aware learn-from-human-data robot policy? 🚀We introduce ForceBand: Learning Forceful Manipulation with sEMG -- bring force into human videos with sEMG, for force-aware manipulation ⬇️ ✦ Zero-Shot Human-to-Robot Transfer ✦ Force Beyond Vision ✦ Free-Hand Force Sensing ✦ Collect by Anyone, Anytime, Anywhere ✦ Deploy on Any Robot, Any Camera, Any Environment ✦ Open-Source & Low-Cost & Easy-to-Implement Let's squeeze every bit of signal out of human data, and let robots feel the force! 🌐 Website: 📄 Paper: 💻 Code: 🎥 Video: 🧵 1/n

Zhi (Leo) Wang

52,180 просмотров • 2 месяцев назад

Labric (Labric) is building data and AI infrastructure for scientific labs, streaming and organizing experiment data from all sources (instruments, Excel, etc) into one searchable, AI-ready platform. Congrats on the launch, Connor Hogan and Caitlin!
1:13

Labric (Labric) is building data and AI infrastructure for scientific labs, streaming and organizing experiment data from all sources (instruments, Excel, etc) into one searchable, AI-ready platform. Congrats on the launch, Connor Hogan and Caitlin!

Y Combinator

16,628 просмотров • 1 год назад

Schaeffler is bringing UK's humanoid robots from concept to factory reality. Within the next 5 years, hundreds of humanoid robots will be deployed in Schaeffler's global factories, with beta versions first implemented in 2026–2027. Schaeffler is also becoming the preferred supplier of joint actuators for the humanoid wheeled platform and is jointly exploring next-generation actuator architectures with its partner. More importantly, the two companies will collaborate deeply on data and skills: continuously accumulating real-world manufacturing data through teleoperation, synthetic data, and peripheral data acquisition robots to train AI models, enabling humanoid robots to learn faster and perform more reliably in the factory.
0:41

Schaeffler is bringing UK's humanoid robots from concept to factory reality. Within the next 5 years, hundreds of humanoid robots will be deployed in Schaeffler's global factories, with beta versions first implemented in 2026–2027. Schaeffler is also becoming the preferred supplier of joint actuators for the humanoid wheeled platform and is jointly exploring next-generation actuator architectures with its partner. More importantly, the two companies will collaborate deeply on data and skills: continuously accumulating real-world manufacturing data through teleoperation, synthetic data, and peripheral data acquisition robots to train AI models, enabling humanoid robots to learn faster and perform more reliably in the factory.

CyberRobo

19,907 просмотров • 8 месяцев назад

Embedder (Embedder) is building the Cursor for embedded: upload data sheets, chat with agents, and generate production-level driver code in seconds. Congrats on the launch, Ethan Gibbs and Bob Wei!
2:13

Embedder (Embedder) is building the Cursor for embedded: upload data sheets, chat with agents, and generate production-level driver code in seconds. Congrats on the launch, Ethan Gibbs and Bob Wei!

Y Combinator

55,581 просмотров • 1 год назад

Today we are introducing Dyna-2, a world-action model pre-trained on one million hours of human video. At this scale, for the first time, we discovered several new scaling laws: • world-action models exhibit scaling law on human data across four orders of magnitude, from 1000 to 1,000,000 hours, • this human data scaling law implied a scaling law on never seen robot data, • both data and objective matter; world modeling and scaling on video data are essential for cross-embodiment scaling transfer to emerge 🧵
1:42

Today we are introducing Dyna-2, a world-action model pre-trained on one million hours of human video. At this scale, for the first time, we discovered several new scaling laws: • world-action models exhibit scaling law on human data across four orders of magnitude, from 1000 to 1,000,000 hours, • this human data scaling law implied a scaling law on never seen robot data, • both data and objective matter; world modeling and scaling on video data are essential for cross-embodiment scaling transfer to emerge 🧵

Dyna Robotics

1,787,807 просмотров • 1 месяц назад