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Sunday Robotics' Tony Zhao says they're using gloves worn by people doing household chores to create the dataset they'll use to train their foundation model: “This gives us really high-quality data, but also a really high diversity and quantity of data.”

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We asked Angus about the future of robotics and AI training. “I built an industrial-grade kinematic solver for 6 degrees of freedom motion, with full path planning and joint control." "You can stream AI model outputs into it, or run it like a traditional industrial robot." "The benefit of that is all of that information you can stream and record from those joints… you can use that as the training data." "Frankly, moving a robot with a lever is really crap data for training robots. But this gives you smooth, high-quality motion, without needing two robots.”

We asked Angus about the future of robotics and AI training. “I built an industrial-grade kinematic solver for 6 degrees of freedom motion, with full path planning and joint control." "You can stream AI model outputs into it, or run it like a traditional industrial robot." "The benefit of that is all of that information you can stream and record from those joints… you can use that as the training data." "Frankly, moving a robot with a lever is really crap data for training robots. But this gives you smooth, high-quality motion, without needing two robots.”

TBPN

18,811 Aufrufe • vor 1 Jahr

Today we're launching Hebbian Robotics (YC S26) Hebbian Robotics (YC S26) . We build APIs for evaluating data quality, without training a robotics model. Data vendors use our API to search and analyze Physical AI data at scale, getting on-demand quality signals and metrics without managing infrastructure. High-quality data is the bottleneck to the next frontier of intelligence in robotics. Buyers want data they can trust. Data providers are focused on operational excellence. They don't have the bandwidth to understand the quality of their data at scale. We're fixing this. Vendors use our APIs to understand the impact of their decisions on their data quality: - Buyers demanding per-collector hour limits? Prove compliance while we stay ahead of the workarounds. - Changed your collection SOPs? Monitor for quality drift and regression. - Suspect duplicate samples? Verify with a single API call. Before Hebbian, I trained AI models for industrial cleaning robots, and kingston kuan spent years building large-scale infrastructure at Jane Street.

Today we're launching Hebbian Robotics (YC S26) Hebbian Robotics (YC S26) . We build APIs for evaluating data quality, without training a robotics model. Data vendors use our API to search and analyze Physical AI data at scale, getting on-demand quality signals and metrics without managing infrastructure. High-quality data is the bottleneck to the next frontier of intelligence in robotics. Buyers want data they can trust. Data providers are focused on operational excellence. They don't have the bandwidth to understand the quality of their data at scale. We're fixing this. Vendors use our APIs to understand the impact of their decisions on their data quality: - Buyers demanding per-collector hour limits? Prove compliance while we stay ahead of the workarounds. - Changed your collection SOPs? Monitor for quality drift and regression. - Suspect duplicate samples? Verify with a single API call. Before Hebbian, I trained AI models for industrial cleaning robots, and kingston kuan spent years building large-scale infrastructure at Jane Street.

Brandon Ong

165,680 Aufrufe • vor 20 Tagen

Sunday Robotics CEO Tony Zhao believes home robots only need to master a handful of chores before they become indispensable. "What is the minimum number of tasks that a robot needs to do to justify its own existence so that people love having it in their homes? I actually think the list is pretty short. The tasks are pretty repetitive. You just need to learn it and just keep doing that over and over again, like folding shirts or loading dishwashers."

Sunday Robotics CEO Tony Zhao believes home robots only need to master a handful of chores before they become indispensable. "What is the minimum number of tasks that a robot needs to do to justify its own existence so that people love having it in their homes? I actually think the list is pretty short. The tasks are pretty repetitive. You just need to learn it and just keep doing that over and over again, like folding shirts or loading dishwashers."

TBPN

65,751 Aufrufe • vor 1 Monat

Origami Robotics is building high-DOF robotic hands with in-joint motors and a co-designed data-collection glove to eliminate the embodiment gap by collecting high-quality, real-world data at scale. Congrats on the launch, Quanting Xie and Ryan Xie!

Origami Robotics is building high-DOF robotic hands with in-joint motors and a co-designed data-collection glove to eliminate the embodiment gap by collecting high-quality, real-world data at scale. Congrats on the launch, Quanting Xie and Ryan Xie!

Y Combinator

89,317 Aufrufe • vor 5 Monaten

Of course I have 100s and 1000s of hours of fire, police, air traffic radio saved from over a decade to train AI models on for high protein non-Reddit data. I also am the only AI engineer using CB radio. This data is more complex, not high order, but needed. Dull example:

Of course I have 100s and 1000s of hours of fire, police, air traffic radio saved from over a decade to train AI models on for high protein non-Reddit data. I also am the only AI engineer using CB radio. This data is more complex, not high order, but needed. Dull example:

Brian Roemmele

281,158 Aufrufe • vor 11 Monaten

Sunday Robotics raised $165M to deploy their home robot Memo, but the more interesting story is how they got here. Instead of starting with a robot, they started by putting sensor-equipped gloves into real homes to capture how people actually do chores like dishes, laundry, and cleaning. That data is now what powers Memo. Here’s my conversation with Co-founder & CEO Tony Zhao. 1:34 Why does the world need Sunday? 2:07 What does Sunday get right? 2:37 Hardest part of building a home robot? 3:12 What does the future of robotics look like? 4:54 What is Memo? 5:23 Biggest misconception about robotics? 5:54 What does a successful launch look like? 6:29 $1B valuation pre-launch. How do you handle it? 8:12 What do people underestimate about Sunday? 10:34 Favorite consumer hardware product Tony Zhao Sunday

Sunday Robotics raised $165M to deploy their home robot Memo, but the more interesting story is how they got here. Instead of starting with a robot, they started by putting sensor-equipped gloves into real homes to capture how people actually do chores like dishes, laundry, and cleaning. That data is now what powers Memo. Here’s my conversation with Co-founder & CEO Tony Zhao. 1:34 Why does the world need Sunday? 2:07 What does Sunday get right? 2:37 Hardest part of building a home robot? 3:12 What does the future of robotics look like? 4:54 What is Memo? 5:23 Biggest misconception about robotics? 5:54 What does a successful launch look like? 6:29 $1B valuation pre-launch. How do you handle it? 8:12 What do people underestimate about Sunday? 10:34 Favorite consumer hardware product Tony Zhao Sunday

Ritwik Pavan

26,762 Aufrufe • vor 4 Monaten

Model progress is no longer constrained by architecture, but by access to high-quality, human-generated data. Scraped internet data is finite, low-signal and increasingly synthetic. Kled AI pays real people to upload authentic, real world content task by task in their mobile app. We are super excited to back Avi Patel and Kled AI as they build a massive data marketplace. If you are in need of a great data partner, reach out! More from us here (we were not investors when we filmed):

Model progress is no longer constrained by architecture, but by access to high-quality, human-generated data. Scraped internet data is finite, low-signal and increasingly synthetic. Kled AI pays real people to upload authentic, real world content task by task in their mobile app. We are super excited to back Avi Patel and Kled AI as they build a massive data marketplace. If you are in need of a great data partner, reach out! More from us here (we were not investors when we filmed):

Nichole Wischoff

36,974 Aufrufe • vor 5 Monaten

I really hope Vince isn’t still embarrassed by this. Being able to create this high quality of content with only 3 people left in the game is truly a gift #bb28

I really hope Vince isn’t still embarrassed by this. Being able to create this high quality of content with only 3 people left in the game is truly a gift #bb28

Big Brother Tea

24,850 Aufrufe • vor 1 Monat

.Ilya Sutskever on why OpenAI gave up on robotics: "Progress comes from the combination of compute and data. There was no path to data from robotics. I'd say that now it is possible to create a path forward, but one needs to really commit. You could imagine a gradual path of improvement where you build more robots, they do more things, you collect more data and so on. But you need to really love robots and need to be really willing to solve all the physical and logistical problems of dealing with them. It's not the same as software at all."

.Ilya Sutskever on why OpenAI gave up on robotics: "Progress comes from the combination of compute and data. There was no path to data from robotics. I'd say that now it is possible to create a path forward, but one needs to really commit. You could imagine a gradual path of improvement where you build more robots, they do more things, you collect more data and so on. But you need to really love robots and need to be really willing to solve all the physical and logistical problems of dealing with them. It's not the same as software at all."

Dwarkesh Patel

325,893 Aufrufe • vor 2 Jahren

John: There is a lot of opposition to building in America, broadly. That's just the nature of our society. I was thinking about, what do Americans want to build? Because it's easy to look at the data center stuff and be like, "Well, everyone's against building data centers." I was reflecting on the whole reindustrialization meme this weekend. And I was thinking about the actual knock-on effects of reindustrialization — most people don't want a car factory in their town. I actually think people don't really want change. They don't want things built. Data centers are probably at the bottom of the list. They're the least popular. But people don't want stuff built, generally. There are very few things that people are like, "Yeah, I'd be down for that to be built." People like the status quo. They're happy with things as they are. And they don't like change. People block home construction all the time. Also, permitting and expansion of existing homes. I'm not saying that they're as unpopular as data centers. Data centers are at the bottom. But new housing in communities is like razor's edge. I do think there's an element of like, Americans don't want to build anything.

John: There is a lot of opposition to building in America, broadly. That's just the nature of our society. I was thinking about, what do Americans want to build? Because it's easy to look at the data center stuff and be like, "Well, everyone's against building data centers." I was reflecting on the whole reindustrialization meme this weekend. And I was thinking about the actual knock-on effects of reindustrialization — most people don't want a car factory in their town. I actually think people don't really want change. They don't want things built. Data centers are probably at the bottom of the list. They're the least popular. But people don't want stuff built, generally. There are very few things that people are like, "Yeah, I'd be down for that to be built." People like the status quo. They're happy with things as they are. And they don't like change. People block home construction all the time. Also, permitting and expansion of existing homes. I'm not saying that they're as unpopular as data centers. Data centers are at the bottom. But new housing in communities is like razor's edge. I do think there's an element of like, Americans don't want to build anything.

TBPN

107,111 Aufrufe • vor 3 Monaten

Introducing: Advanced Data Assets™ By LayerAI 🧬 Data is used to power Big Data and AI. The increasing demand for high quality data to improve AI models will lead to new companies creating value in the global data market. The problem: current data collection methods make data fall short of its true potential. Data is limited. Building a decentralized solution where users choose to productize and earn from their data opens untapped sources of income. 🌐 Creating Advanced Data Assets™ There exists a market opportunity to create a digital blockchain-based global data marketplace. Data collected using our nodes, our native network apps, settled on LayerAI. The Advanced Data. Meet the Ecosystem that empowers users to participate in the Data Economy.

Introducing: Advanced Data Assets™ By LayerAI 🧬 Data is used to power Big Data and AI. The increasing demand for high quality data to improve AI models will lead to new companies creating value in the global data market. The problem: current data collection methods make data fall short of its true potential. Data is limited. Building a decentralized solution where users choose to productize and earn from their data opens untapped sources of income. 🌐 Creating Advanced Data Assets™ There exists a market opportunity to create a digital blockchain-based global data marketplace. Data collected using our nodes, our native network apps, settled on LayerAI. The Advanced Data. Meet the Ecosystem that empowers users to participate in the Data Economy.

LayerAI | AI2Earn

27,136 Aufrufe • vor 2 Jahren

This magic is unlocked by AI in combination with high-quality, diverse vision and force feedback data. Memo by Sunday Robotics autonomously stacks and folds socks into a tucked bundle (1x speed). The task generalizes across diverse rooms and table setups. It took 3 months of engineering effort and 16 H100 nodes to accomplish this. The age of general-purpose robots is upon us.

This magic is unlocked by AI in combination with high-quality, diverse vision and force feedback data. Memo by Sunday Robotics autonomously stacks and folds socks into a tucked bundle (1x speed). The task generalizes across diverse rooms and table setups. It took 3 months of engineering effort and 16 H100 nodes to accomplish this. The age of general-purpose robots is upon us.

The Humanoid Hub

32,239 Aufrufe • vor 9 Monaten

Been looking into RICE AI ( ◉ - ◉ ) lately, and it’s one of the few projects actually tackling a real challenge in robotics and AGI: the lack of high-quality training data. Robots can’t get truly intelligent without it. They building a decentralized way to collect and share robotics data, using a DePIN network to train physical AI foundation models. The project was even hand-picked by CZ as a winner of the Dubai BNB Chain Demo Day, and it’s backed by Floki while also being part of the NVIDIA Inception Program. They also launched FLOKI Minibot M1 - a small AI companion that doubles as a data node. Every interaction with it feeds the RICE AI Foundry, the first decentralized platform for Robotics Foundation Models, and contributors earn $RICE tokens in return. And it’s working: – 800 minibots sold in 24h – 33,000% oversubscribed Binance IDO – 500+ robots already deployed worldwide Feels like a project with real long-term potential. Worth keeping an eye on. RICE AI ( ◉ - ◉ )

Been looking into RICE AI ( ◉ - ◉ ) lately, and it’s one of the few projects actually tackling a real challenge in robotics and AGI: the lack of high-quality training data. Robots can’t get truly intelligent without it. They building a decentralized way to collect and share robotics data, using a DePIN network to train physical AI foundation models. The project was even hand-picked by CZ as a winner of the Dubai BNB Chain Demo Day, and it’s backed by Floki while also being part of the NVIDIA Inception Program. They also launched FLOKI Minibot M1 - a small AI companion that doubles as a data node. Every interaction with it feeds the RICE AI Foundry, the first decentralized platform for Robotics Foundation Models, and contributors earn $RICE tokens in return. And it’s working: – 800 minibots sold in 24h – 33,000% oversubscribed Binance IDO – 500+ robots already deployed worldwide Feels like a project with real long-term potential. Worth keeping an eye on. RICE AI ( ◉ - ◉ )

Christiaan

12,696 Aufrufe • vor 11 Monaten

.Snorkel AI helps organizations leverage their own data and expertise to build high-quality, specialized AI systems orders of magnitude faster than fully manual approaches. The company drives value in partnership with AWS and NVIDIA to help their customers. Available in AWS Marketplace, Snorkel’s AI Data Development platform enables enterprises to turn their proprietary data and domain knowledge into expert evaluation and training data, with options for in house data development or white glove dataset delivery.

.Snorkel AI helps organizations leverage their own data and expertise to build high-quality, specialized AI systems orders of magnitude faster than fully manual approaches. The company drives value in partnership with AWS and NVIDIA to help their customers. Available in AWS Marketplace, Snorkel’s AI Data Development platform enables enterprises to turn their proprietary data and domain knowledge into expert evaluation and training data, with options for in house data development or white glove dataset delivery.

AWS Startups

2,760,137 Aufrufe • vor 2 Monaten

Kraken Robotics’ subsea LiDAR is used in dynamic mode, collecting data from a moving ROV, to capture a high-resolution 3D dataset. This data was collected from the base of a subsea structure up the platform jacket leg, including the existing riser system, to support an upcoming riser replacement project. Learn more:

Kraken Robotics’ subsea LiDAR is used in dynamic mode, collecting data from a moving ROV, to capture a high-resolution 3D dataset. This data was collected from the base of a subsea structure up the platform jacket leg, including the existing riser system, to support an upcoming riser replacement project. Learn more:

Kraken Robotics

24,042 Aufrufe • vor 2 Monaten

The co-founders of Flapping Airplanes call the current RL paradigm for model training "environment slop." They explain: "The reinforcement paradigms of today are shockingly inefficient. You don't really get much generalization across tasks, you teach a model through one kind of learning and then you teach it the next one. It's kind of like whack-a-mole. We look at this and think it's kind of crazy. The next paradigm of AI will not be environment slop." "Human level intelligence is not the ceiling, it is merely the floor on what is possible. If you can train models with vastly less data and possibly more compute in very different ways, what is going to happen? We actually don't know. But I do think they'll be different and weird and they'll have interesting capabilities that we'll find really valuable ways to use."

The co-founders of Flapping Airplanes call the current RL paradigm for model training "environment slop." They explain: "The reinforcement paradigms of today are shockingly inefficient. You don't really get much generalization across tasks, you teach a model through one kind of learning and then you teach it the next one. It's kind of like whack-a-mole. We look at this and think it's kind of crazy. The next paradigm of AI will not be environment slop." "Human level intelligence is not the ceiling, it is merely the floor on what is possible. If you can train models with vastly less data and possibly more compute in very different ways, what is going to happen? We actually don't know. But I do think they'll be different and weird and they'll have interesting capabilities that we'll find really valuable ways to use."

TBPN

85,358 Aufrufe • vor 7 Monaten

Synthetic data will provide the next trillion tokens to fuel our hungry models. I'm excited to announce MimicGen: massively scaling up data pipeline for robot learning! We multiply high-quality human data in simulation with digital twins. Using 50,000 training episodes across 18 tasks, multiple simulators, and even in the real-world! The idea is simple: 1. Humans tele-operate the robot to complete a task. It is extremely high-quality but also very slow and expensive. 2. We create a digital twin of the robot and the scene in high-fidelity, GPU-accelerated simulation. 3. We can now move objects around, replace with new assets, and even change the robot hand - basically augment the training data with procedural generation. 4. Export the successful episodes, and feed that to a neural network! You now have an near-infinite stream of data. One of the key reasons that robotics lags far behind other AI fields is the lack of data: you cannot scrape control signals from the internet. They simply don't exist in-the-wild. MimicGen shows the power of synthetic data and simulation to keep our scaling laws alive. I believe this principle apply beyond robotics. We are quickly exhausting the high-quality, real tokens from the web. Artificial intelligence from artificial data will be the way forward. We are big fans of the OSS community. As usual, we open-source everything, including the generated dataset! - Website: - Paper: - Dataset is hosted on HuggingFace (thanks AK!!): - Code: MimicGen is led by Ajay Mandlekar, deep dive in the thread:

Synthetic data will provide the next trillion tokens to fuel our hungry models. I'm excited to announce MimicGen: massively scaling up data pipeline for robot learning! We multiply high-quality human data in simulation with digital twins. Using 50,000 training episodes across 18 tasks, multiple simulators, and even in the real-world! The idea is simple: 1. Humans tele-operate the robot to complete a task. It is extremely high-quality but also very slow and expensive. 2. We create a digital twin of the robot and the scene in high-fidelity, GPU-accelerated simulation. 3. We can now move objects around, replace with new assets, and even change the robot hand - basically augment the training data with procedural generation. 4. Export the successful episodes, and feed that to a neural network! You now have an near-infinite stream of data. One of the key reasons that robotics lags far behind other AI fields is the lack of data: you cannot scrape control signals from the internet. They simply don't exist in-the-wild. MimicGen shows the power of synthetic data and simulation to keep our scaling laws alive. I believe this principle apply beyond robotics. We are quickly exhausting the high-quality, real tokens from the web. Artificial intelligence from artificial data will be the way forward. We are big fans of the OSS community. As usual, we open-source everything, including the generated dataset! - Website: - Paper: - Dataset is hosted on HuggingFace (thanks AK!!): - Code: MimicGen is led by Ajay Mandlekar, deep dive in the thread:

Jim Fan

332,238 Aufrufe • vor 2 Jahren

🎆Chainbase is building the largest omnichain data network to provide high-quality data for the AGI era. Just like Oracle to Defi, Data to AI We aim to create a decentralized data economy and enhance the crypto world with advanced AI capabilities, where anyone can participate, contribute, and be incentivized. Explore the unique network features with us.🧵👇

🎆Chainbase is building the largest omnichain data network to provide high-quality data for the AGI era. Just like Oracle to Defi, Data to AI We aim to create a decentralized data economy and enhance the crypto world with advanced AI capabilities, where anyone can participate, contribute, and be incentivized. Explore the unique network features with us.🧵👇

Chainbase (💜,💛)

340,756 Aufrufe • vor 2 Jahren

People love to debate quality over quantity, but a reminder: quality is subjective. we all like different things. Raw, authentic, high polished, high fidelity, humor, beauty, strange, weird … But quantity is not debatable, so either you're doing the reps or you're not. I could not recommend more for people to have more accounts, more opportunities to post, and try different things. One piece of content can change everything.

People love to debate quality over quantity, but a reminder: quality is subjective. we all like different things. Raw, authentic, high polished, high fidelity, humor, beauty, strange, weird … But quantity is not debatable, so either you're doing the reps or you're not. I could not recommend more for people to have more accounts, more opportunities to post, and try different things. One piece of content can change everything.

Gary Vaynerchuk

19,984 Aufrufe • vor 6 Monaten