Загрузка видео...

Не удалось загрузить видео

На главную

Your next robotics project could start with these steps. Today, we're open-sourcing Asimov 1's locomotion policy and the training code behind it, giving developers a foundation to build on. Alongside the trained policy checkpoint, we're sharing our Isaac Lab-based training code, including reward definitions, hardware-tuned actuator configurations, and domain...

asimovinc's profile picture

Asimov

24,293 subscribers

55,910 просмотров • 4 дней назад •via X (Twitter)

ОбразованиеНаука и технологии
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 5

Фото профиля Σ
Σ4 дней назад

Love the project but the next step should definitely be to work on the legs so it doesn't walk like Biden

Фото профиля Asimov
Asimov4 дней назад

It's now open-source. Your best walk is one pull request away 🧡

Фото профиля Roushan
Roushan4 дней назад

Awesome

Фото профиля satvik
satvik4 дней назад

Wow finally!!!

Фото профиля Indem
Indem4 дней назад

Shipping the actuator config alongside the checkpoint is the detail I like here. For a deployed fleet, I’d carry that pairing into each robot’s run history. “Latest version” gets vague fast when hardware starts diverging.

Похожие видео

We're open-sourcing Asimov v1, a humanoid robot. With Asimov v1, you can build, train on, and make it your own humanoid robot. It's the first step of building a humanoid labor force for the rest of us. Asimov v1 is 1.2 m tall, 35 kg, with 25 actuated degrees of freedom. Structural parts machined in 7075 aluminium and 3D-printed in MJF PA12 nylon. We're releasing the mechanical design and simulation files. Ready for locomotion policy training out of the box. The BOM is open too. Source everything yourself, or order the DIY Kit. All components, ready to assemble. $499 deposit, $15,000 target price. Ships end of summer 2026. GitHub: Manual: DIY Kit: Most humanoid robots are controlled by the companies that build them. Asimov v1 is built for the rest of us. Build it, test it, and share your feedback with the community.
1:09

We're open-sourcing Asimov v1, a humanoid robot. With Asimov v1, you can build, train on, and make it your own humanoid robot. It's the first step of building a humanoid labor force for the rest of us. Asimov v1 is 1.2 m tall, 35 kg, with 25 actuated degrees of freedom. Structural parts machined in 7075 aluminium and 3D-printed in MJF PA12 nylon. We're releasing the mechanical design and simulation files. Ready for locomotion policy training out of the box. The BOM is open too. Source everything yourself, or order the DIY Kit. All components, ready to assemble. $499 deposit, $15,000 target price. Ships end of summer 2026. GitHub: Manual: DIY Kit: Most humanoid robots are controlled by the companies that build them. Asimov v1 is built for the rest of us. Build it, test it, and share your feedback with the community.

Asimov

343,323 просмотров • 5 месяцев назад

here are 5 robots you could build after reading this article: 1. the SO-101 arm, $122 in parts build it, calibrate every servo, teleoperate it, then print your own gripper fingers 2. a ROS 2 rover that maps a room and navigates it SLAM Toolbox and Nav2, and you can do the whole thing in simulation with no hardware at all 3. self-balancing robot it will not stand up until your filter and your loop timing are both correct, which is exactly the point 4. an ACT policy trained on your own demonstrations record 50 demos, train, deploy, measure the success rate, then record 50 more and beat it 5. line follower with PID your first closed loop, and filming it badly tuned next to properly tuned is the whole interview answer that's what will make you at least advanced junior at Robotics Engineering and will help you to get your first offer in robotics company
1:18

here are 5 robots you could build after reading this article: 1. the SO-101 arm, $122 in parts build it, calibrate every servo, teleoperate it, then print your own gripper fingers 2. a ROS 2 rover that maps a room and navigates it SLAM Toolbox and Nav2, and you can do the whole thing in simulation with no hardware at all 3. self-balancing robot it will not stand up until your filter and your loop timing are both correct, which is exactly the point 4. an ACT policy trained on your own demonstrations record 50 demos, train, deploy, measure the success rate, then record 50 more and beat it 5. line follower with PID your first closed loop, and filming it badly tuned next to properly tuned is the whole interview answer that's what will make you at least advanced junior at Robotics Engineering and will help you to get your first offer in robotics company

Ronin

44,120 просмотров • 26 дней назад

If you're looking for a weekend project, how about training your own text-to-speech model from scratch on your own GPU, and then running it on any device's CPU? We just open-sourced the entire Pocket TTS training stack: data pipeline, recipes, and evals. It learns pretty damn fast: ~15k steps: babbling starts turning into words ~50k steps: it reads anything you type (WER under 1%) ~200k steps: the voice stops sounding synthetic On a beefy consumer GPU, that's a week of training. On eight H100s: 10-20 hours. A TTS training run will cost you less than $200 if you rent your hardware, and an order of magnitude less if you just pay for power. Some things we'd love to see people try: - Train it in your own language (a few hundred hours of speech gets you surprisingly far). - Add new features to Pocket TTS (Emotion tags? Make it sing?). - Beat us at our own game: make it faster and smaller. Show us what you build! We'll highlight the best models and new languages for the whole community to enjoy. Pocket TTS has already found many use cases, from reading for people with visual impairments to making NPCs in video games talk, and we're sure there's much more to do with it! Here's an example of a Czech Pocket TTS. Try just asking your favorite agent to find data and apply the method, and you can have your own. Get started:
0:32

If you're looking for a weekend project, how about training your own text-to-speech model from scratch on your own GPU, and then running it on any device's CPU? We just open-sourced the entire Pocket TTS training stack: data pipeline, recipes, and evals. It learns pretty damn fast: ~15k steps: babbling starts turning into words ~50k steps: it reads anything you type (WER under 1%) ~200k steps: the voice stops sounding synthetic On a beefy consumer GPU, that's a week of training. On eight H100s: 10-20 hours. A TTS training run will cost you less than $200 if you rent your hardware, and an order of magnitude less if you just pay for power. Some things we'd love to see people try: - Train it in your own language (a few hundred hours of speech gets you surprisingly far). - Add new features to Pocket TTS (Emotion tags? Make it sing?). - Beat us at our own game: make it faster and smaller. Show us what you build! We'll highlight the best models and new languages for the whole community to enjoy. Pocket TTS has already found many use cases, from reading for people with visual impairments to making NPCs in video games talk, and we're sure there's much more to do with it! Here's an example of a Czech Pocket TTS. Try just asking your favorite agent to find data and apply the method, and you can have your own. Get started:

kyutai

105,814 просмотров • 1 месяц назад

What if legacy doesn’t start with the next generation? What if it starts with you? The Legacy Fellowship by Celebration Church is an invitation to grow what God placed in your hands and heart. We are offering you the right tools, training, and tribe to support you as you launch that project to change a life. Ready to build? Apply now.
2:12

What if legacy doesn’t start with the next generation? What if it starts with you? The Legacy Fellowship by Celebration Church is an invitation to grow what God placed in your hands and heart. We are offering you the right tools, training, and tribe to support you as you launch that project to change a life. Ready to build? Apply now.

Celebration Church International

11,050 просмотров • 1 год назад

Today, we're open sourcing the code behind "The Infinite Crate," our VST/AU plugin that lets you play with Lyria RealTime directly inside your favorite DAW! 🎧🎶 Since we released The Infinite Crate last year, it’s been used by some of our favorite artists - including a wonderful showcase with Daito Manabe in Tokyo - and being featured as a top new music tool at NAMM 2026. We’re now fully open sourcing the plugin for developers to fork, modify, and make their own under the permissive Apache 2.0 license. 💾 Get it here:
0:39

Today, we're open sourcing the code behind "The Infinite Crate," our VST/AU plugin that lets you play with Lyria RealTime directly inside your favorite DAW! 🎧🎶 Since we released The Infinite Crate last year, it’s been used by some of our favorite artists - including a wonderful showcase with Daito Manabe in Tokyo - and being featured as a top new music tool at NAMM 2026. We’re now fully open sourcing the plugin for developers to fork, modify, and make their own under the permissive Apache 2.0 license. 💾 Get it here:

Jesse Engel

20,912 просмотров • 6 месяцев назад

The largest fully annotated open egocentric human dataset. Today we're open-sourcing EgoSuite-Open100K with Hugging Face : 100,000 hours of egocentric human data, free for anyone to use. Physical AI has a scaling law of its own now, and its input is human data. That part is settled. What the field still needs is a shared foundation to build on. 15,000+ tasks. 15,000+ real scenes, from factory floors to retail backrooms. Hand pose, body pose and subtask-level semantics, with wrist camera coverage on part of the set. Licensed for commercial training, not research-only. We build the data infrastructure for Physical AI. Open100K is the first public layer of it. The first 10,000 hours are live now, with the rest rolling out in stages.
1:18

The largest fully annotated open egocentric human dataset. Today we're open-sourcing EgoSuite-Open100K with Hugging Face : 100,000 hours of egocentric human data, free for anyone to use. Physical AI has a scaling law of its own now, and its input is human data. That part is settled. What the field still needs is a shared foundation to build on. 15,000+ tasks. 15,000+ real scenes, from factory floors to retail backrooms. Hand pose, body pose and subtask-level semantics, with wrist camera coverage on part of the set. Licensed for commercial training, not research-only. We build the data infrastructure for Physical AI. Open100K is the first public layer of it. The first 10,000 hours are live now, with the rest rolling out in stages.

Lightwheel

74,327 просмотров • 1 месяц назад

What if you could train AI agents on a laptop as easily as on a GPU cluster? Researchers from UIUC's U Lab, led by Prof. Jiaxuan You, just open-sourced OpenTinker. It's a new "Reinforcement-Learning-as-a-Service" (RLaaS) system that decouples the complex training pipeline into simple, distributed services with friendly APIs. The result? It breaks down the major engineering barriers to RL, outperforming traditional frameworks in accessibility and ease of deployment, finally making agent training viable for more developers and teams. Project: Code: U Lab: Our report: 📬 #PapersAccepted by Jiqizhixin
0:42

What if you could train AI agents on a laptop as easily as on a GPU cluster? Researchers from UIUC's U Lab, led by Prof. Jiaxuan You, just open-sourced OpenTinker. It's a new "Reinforcement-Learning-as-a-Service" (RLaaS) system that decouples the complex training pipeline into simple, distributed services with friendly APIs. The result? It breaks down the major engineering barriers to RL, outperforming traditional frameworks in accessibility and ease of deployment, finally making agent training viable for more developers and teams. Project: Code: U Lab: Our report: 📬 #PapersAccepted by Jiqizhixin

机器之心 JIQIZHIXIN

15,893 просмотров • 8 месяцев назад

Meet AMD Skills: A growing catalog of agent skills that helps AI coding assistants work more effectively with AMD hardware and software. Compatible with coding agents including Cursor, Claude Code, OpenAI Codex, and Gemini CLI, AMD Skills provides the knowledge, scripts, and best practices developers need to build faster on AMD. Why try it? → Install in seconds with the Skills CLI → Learn AMD best practices and workflows → Build AI applications from client to cloud → Pick only the skills you need Get started: npx skills add amd/skills Explore the project, install a skill, and let us know what you'd like to see next:
0:40

Meet AMD Skills: A growing catalog of agent skills that helps AI coding assistants work more effectively with AMD hardware and software. Compatible with coding agents including Cursor, Claude Code, OpenAI Codex, and Gemini CLI, AMD Skills provides the knowledge, scripts, and best practices developers need to build faster on AMD. Why try it? → Install in seconds with the Skills CLI → Learn AMD best practices and workflows → Build AI applications from client to cloud → Pick only the skills you need Get started: npx skills add amd/skills Explore the project, install a skill, and let us know what you'd like to see next:

AI at AMD

13,609 просмотров • 1 месяц назад

WATCH: Elon Musk's companies trained a whole generation of America's hardware engineers. On David Senra's podcast, Base Power founder Zach Dell and host David Senra talked about how Tesla, SpaceX and Anduril taught a whole cohort of engineers how to build hardware, scale manufacturing and ramp a supply chain. As one put it: "We have these companies to thank for training a whole cohort of engineers on how to build hardware products, how to scale manufacturing, how to ramp a supply chain." On Elon Musk, one added: "Could you imagine the deficit that America would have if Elon didn't exist in this domain... It's the most incredible contribution I think anyone has ever made to humanity." Their bigger point was that it is not just the companies Elon built, but the engineers he trained who went on to build other great companies. Source: David Senra × Zach Dell (Base Power), Sept 2026
0:42

WATCH: Elon Musk's companies trained a whole generation of America's hardware engineers. On David Senra's podcast, Base Power founder Zach Dell and host David Senra talked about how Tesla, SpaceX and Anduril taught a whole cohort of engineers how to build hardware, scale manufacturing and ramp a supply chain. As one put it: "We have these companies to thank for training a whole cohort of engineers on how to build hardware products, how to scale manufacturing, how to ramp a supply chain." On Elon Musk, one added: "Could you imagine the deficit that America would have if Elon didn't exist in this domain... It's the most incredible contribution I think anyone has ever made to humanity." Their bigger point was that it is not just the companies Elon built, but the engineers he trained who went on to build other great companies. Source: David Senra × Zach Dell (Base Power), Sept 2026

Muskonomy

12,203 просмотров • 22 дней назад

Cerebras CFO Bob Komin on concentration risk: "How do you build up a big company? Start with one large customer, add another, add another, and we're on that trajectory right now." "Now we have an over $20 billion customer. Of course, they're going to be a high percentage of our revenue. But the second step out was to get a foundation model lab using our hardware, and then the third step is our first hyperscaler customer with AWS, and we haven't even gotten started with them."
0:54

Cerebras CFO Bob Komin on concentration risk: "How do you build up a big company? Start with one large customer, add another, add another, and we're on that trajectory right now." "Now we have an over $20 billion customer. Of course, they're going to be a high percentage of our revenue. But the second step out was to get a foundation model lab using our hardware, and then the third step is our first hyperscaler customer with AWS, and we haven't even gotten started with them."

Deirdre Bosa

38,913 просмотров • 4 месяцев назад

Another win for open-source robotics! 🔥 Hugging Face just released a fully open-source humanoid robot, and you can build one for $2,500. I'm a huge advocate of open-source in robotics space. Why? Robotics is too hard to solve alone. So lowering the entry point is crucial. Also, ROS proved open ecosystems create lasting industry standards. So let's have a look at the new member of humanoids family! LeRobot Humanoid is a 3D-printed, bipedal humanoid platform designed for real robot learning experiments. It's a complete and, buildable robot Anddddd yes, it's a full stack release: → Hardware files, bill of materials and full assembly documentation → Simulation assets and training environments → Runtime tools for calibration and real-world control → Sim-to-real identification pipeline When a part breaks, reprint it. When a design choice doesn't work, modify it and test again. The whole point is fast iteration on real hardware, not treating the robot as a fixed artefact. The timing is not a coincidence. As foundation models for robotics mature, the field desperately needs open physical platforms to train, validate and deploy them on. clem 🤗 LET'S GO!!! Build it here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
0:20

Another win for open-source robotics! 🔥 Hugging Face just released a fully open-source humanoid robot, and you can build one for $2,500. I'm a huge advocate of open-source in robotics space. Why? Robotics is too hard to solve alone. So lowering the entry point is crucial. Also, ROS proved open ecosystems create lasting industry standards. So let's have a look at the new member of humanoids family! LeRobot Humanoid is a 3D-printed, bipedal humanoid platform designed for real robot learning experiments. It's a complete and, buildable robot Anddddd yes, it's a full stack release: → Hardware files, bill of materials and full assembly documentation → Simulation assets and training environments → Runtime tools for calibration and real-world control → Sim-to-real identification pipeline When a part breaks, reprint it. When a design choice doesn't work, modify it and test again. The whole point is fast iteration on real hardware, not treating the robot as a fixed artefact. The timing is not a coincidence. As foundation models for robotics mature, the field desperately needs open physical platforms to train, validate and deploy them on. clem 🤗 LET'S GO!!! Build it here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

20,457 просмотров • 4 месяцев назад

We put 1000s of hours into building open-source camera glasses And now we're giving away everything we learned for free. Checkout this in-depth teardown of the Mentra Live smart glasses. As an OS company, our goal is to spread our OS. That goal encourages us to do crazy things, like build the world's best AI glasses for business and then show you how we made them... all in the name of spreading the OS. It also convinced us to make it 100% open source, so adoption is faster and easier. We're at risk of our competitors easily copypasting our code now... all in the name of spreading our OS. Now we've built the glasses for you, and we've taken the risk, and we've released an open SDK. Now your AI apps and agents can enter the real world on smart glasses. So now, what will you build?
13:19

We put 1000s of hours into building open-source camera glasses And now we're giving away everything we learned for free. Checkout this in-depth teardown of the Mentra Live smart glasses. As an OS company, our goal is to spread our OS. That goal encourages us to do crazy things, like build the world's best AI glasses for business and then show you how we made them... all in the name of spreading the OS. It also convinced us to make it 100% open source, so adoption is faster and easier. We're at risk of our competitors easily copypasting our code now... all in the name of spreading our OS. Now we've built the glasses for you, and we've taken the risk, and we've released an open SDK. Now your AI apps and agents can enter the real world on smart glasses. So now, what will you build?

cayden 凯登

20,584 просмотров • 4 месяцев назад

“don’t train your own model” is common ai advice. it's wrong. your token bill's the proof. today, we’re excited to launch castform into open preview. castform is the easiest way for you to train your own model, on your own data. open-weights models are performant and much cheaper. when trained on your task & proprietary data, they beat closed models. the thing standing between you and that was weeks of plumbing & years of ml expertise. with castform, model training is as simple as prompt engineering. castform bring your agent traces or raw corpora. castform turns it into training data, picks the right algorithmic recipes, manages gpus, and gives you an ide to watch and chat with your model as it learns. see what you can build with castform👇
2:23

“don’t train your own model” is common ai advice. it's wrong. your token bill's the proof. today, we’re excited to launch castform into open preview. castform is the easiest way for you to train your own model, on your own data. open-weights models are performant and much cheaper. when trained on your task & proprietary data, they beat closed models. the thing standing between you and that was weeks of plumbing & years of ml expertise. with castform, model training is as simple as prompt engineering. castform bring your agent traces or raw corpora. castform turns it into training data, picks the right algorithmic recipes, manages gpus, and gives you an ide to watch and chat with your model as it learns. see what you can build with castform👇

girish

462,836 просмотров • 3 месяцев назад

𝗗𝗮𝘆𝘀, 𝗻𝗼𝘁 𝗺𝗼𝗻𝘁𝗵𝘀. 𝗧𝗵𝗮𝘁'𝘀 𝗵𝗼𝘄 𝗹𝗼𝗻𝗴 𝗶𝘁 𝘁𝗮𝗸𝗲𝘀 𝘁𝗼 𝗴𝗲𝘁 𝗻𝗲𝘄 𝗵𝗮𝗿𝗱𝘄𝗮𝗿𝗲 𝗿𝘂𝗻𝗻𝗶𝗻𝗴 𝗼𝗻 𝗡𝗲𝘂𝗿𝗮𝗰𝗼𝗿𝗲. Get started with our Meta Quest teleop, open source on GitHub, and start collecting data on day one. Neuracore is hardware agnostic by design. OpenArm is the latest addition to our growing list of supported platforms, and like every embodiment we integrate, the code is open for the community to pick up and build on. The OpenArm repository is landing in the next couple of weeks. With Neuracore, teams can skip the integration slog and get straight to the interesting part: collecting data, training policies, and deploying to the real world. Get started for free today: Access our Github here:
0:28

𝗗𝗮𝘆𝘀, 𝗻𝗼𝘁 𝗺𝗼𝗻𝘁𝗵𝘀. 𝗧𝗵𝗮𝘁'𝘀 𝗵𝗼𝘄 𝗹𝗼𝗻𝗴 𝗶𝘁 𝘁𝗮𝗸𝗲𝘀 𝘁𝗼 𝗴𝗲𝘁 𝗻𝗲𝘄 𝗵𝗮𝗿𝗱𝘄𝗮𝗿𝗲 𝗿𝘂𝗻𝗻𝗶𝗻𝗴 𝗼𝗻 𝗡𝗲𝘂𝗿𝗮𝗰𝗼𝗿𝗲. Get started with our Meta Quest teleop, open source on GitHub, and start collecting data on day one. Neuracore is hardware agnostic by design. OpenArm is the latest addition to our growing list of supported platforms, and like every embodiment we integrate, the code is open for the community to pick up and build on. The OpenArm repository is landing in the next couple of weeks. With Neuracore, teams can skip the integration slog and get straight to the interesting part: collecting data, training policies, and deploying to the real world. Get started for free today: Access our Github here:

Neuracore

63,368 просмотров • 5 месяцев назад

Our pricing evolves to give you more freedom to build ⚡ Over the past few months, we’ve spoken with many of you about how you use n8n and realized we could make our pricing work better for the way you build. Our goal: to help you automate more, without limits getting in the way. Here’s what’s new: ⚡ No more limits on active workflows Every n8n plan now includes unlimited active workflows, unlimited steps, and unlimited users. You’re only charged based on executions—that is, how many times your workflows run from start to finish. This way, you can build as much as you want and only pay for what actually delivers value. ⚡ A new self-hosted Business Plan for growing teams If you’re running workflows in production, need more control, but aren’t ready for a full enterprise setup, the Business Plan is for you. It’s self-hosted and includes features like environments, Git version control, and SSO. Plus, pricing scales with the value you get. Check out the updated plans at and make sure to update your n8n instance to apply the changes. We can’t wait to see what you build next!
1:10

Our pricing evolves to give you more freedom to build ⚡ Over the past few months, we’ve spoken with many of you about how you use n8n and realized we could make our pricing work better for the way you build. Our goal: to help you automate more, without limits getting in the way. Here’s what’s new: ⚡ No more limits on active workflows Every n8n plan now includes unlimited active workflows, unlimited steps, and unlimited users. You’re only charged based on executions—that is, how many times your workflows run from start to finish. This way, you can build as much as you want and only pay for what actually delivers value. ⚡ A new self-hosted Business Plan for growing teams If you’re running workflows in production, need more control, but aren’t ready for a full enterprise setup, the Business Plan is for you. It’s self-hosted and includes features like environments, Git version control, and SSO. Plus, pricing scales with the value you get. Check out the updated plans at and make sure to update your n8n instance to apply the changes. We can’t wait to see what you build next!

n8n.io

117,695 просмотров • 1 год назад

Announcing the Style Guide in primeui. Customize your project theme with a shadcn-compatible token system. Preview it live with as many variants as you need on the canvas. Export clean, production-ready Next.js code in minutes. Prime UI gives you a strong foundation for your website, whether you build it yourself or with AI. It includes 200+ UI components, all crafted by humans with pixel-perfect quality, a solid design system, and clean code. Plan your site with the Sitemap tool. Explore content, layout ideas, and storytelling in Prototype. Shape the look and feel in Style Guide, then export everything to Next.js. You get more than just landing pages. You get a consistent foundation for your entire site, including Blog, Docs, Pricing, and more, without having to worry about architecture, content blocks, SEO, or performance. Available today.
0:25

Announcing the Style Guide in primeui. Customize your project theme with a shadcn-compatible token system. Preview it live with as many variants as you need on the canvas. Export clean, production-ready Next.js code in minutes. Prime UI gives you a strong foundation for your website, whether you build it yourself or with AI. It includes 200+ UI components, all crafted by humans with pixel-perfect quality, a solid design system, and clean code. Plan your site with the Sitemap tool. Explore content, layout ideas, and storytelling in Prototype. Shape the look and feel in Style Guide, then export everything to Next.js. You get more than just landing pages. You get a consistent foundation for your entire site, including Blog, Docs, Pricing, and more, without having to worry about architecture, content blocks, SEO, or performance. Available today.

Alex Barashkov

32,330 просмотров • 6 месяцев назад

Build a humanoid robot yourself! 🪚 OpenArm is an open-source humanoid robot. It comes with full CAD, control code, firmware, and simulation tools, everything needed to build, modify, and operate it. The arms are designed to be compliant and backdrivable. Teleoperation is supported, with force feedback and real-time gravity compensation so operators can guide the arm naturally. Super important, on the simulation side, OpenArm works with platforms like MuJoCo and Isaac Sim, letting developers test policies in virtual environments before running on hardware. Assemble it yourself from a kit or get it prebuilt, the goal is accessibility for research labs, small teams, and enthusiasts. The project is run by Enactic in Tokyo, Japan, and aims to lower the barrier for experimenting with dexterous manipulation. Let's put robotics in mainstream! 🔥🔥 P.S. I put the project page in the comments!
1:07

Build a humanoid robot yourself! 🪚 OpenArm is an open-source humanoid robot. It comes with full CAD, control code, firmware, and simulation tools, everything needed to build, modify, and operate it. The arms are designed to be compliant and backdrivable. Teleoperation is supported, with force feedback and real-time gravity compensation so operators can guide the arm naturally. Super important, on the simulation side, OpenArm works with platforms like MuJoCo and Isaac Sim, letting developers test policies in virtual environments before running on hardware. Assemble it yourself from a kit or get it prebuilt, the goal is accessibility for research labs, small teams, and enthusiasts. The project is run by Enactic in Tokyo, Japan, and aims to lower the barrier for experimenting with dexterous manipulation. Let's put robotics in mainstream! 🔥🔥 P.S. I put the project page in the comments!

Lukas Ziegler

233,153 просмотров • 11 месяцев назад

I DON’T THINK PEOPLE REALIZE HOW MASSIVE THIS IS YET Hugging Face and Pollen Robotics just released Microduck. It is a new legged robot for $399. It passed $1 million in sales in under SEVEN hours 🤯 The hardware packs 15 actuators, a camera, and LiDAR into a 25 cm frame. It weighs under 800 grams and runs for about an hour on a single charge. Out of the box, it can > walk > roller-skate > pick up objects > recover from falls .. and so much more! You can drive the 7 shipped policies from the first boot using a gamepad. But the real hook is the training stack. The software is entirely open: → MuJoCo simulation and PPO training → 50 Hz onboard policy loop → Browser simulator included alongside hardware → Full control stack available on GitHub The mechanical and electronic design files are still proprietary. But don’t let the cute robotic duck fool you. Under the closed chassis is a FULLY OPEN-SOURCE, hackable brain you can experiment with and build on. Repo in 🧵↓
0:38

I DON’T THINK PEOPLE REALIZE HOW MASSIVE THIS IS YET Hugging Face and Pollen Robotics just released Microduck. It is a new legged robot for $399. It passed $1 million in sales in under SEVEN hours 🤯 The hardware packs 15 actuators, a camera, and LiDAR into a 25 cm frame. It weighs under 800 grams and runs for about an hour on a single charge. Out of the box, it can > walk > roller-skate > pick up objects > recover from falls .. and so much more! You can drive the 7 shipped policies from the first boot using a gamepad. But the real hook is the training stack. The software is entirely open: → MuJoCo simulation and PPO training → 50 Hz onboard policy loop → Browser simulator included alongside hardware → Full control stack available on GitHub The mechanical and electronic design files are still proprietary. But don’t let the cute robotic duck fool you. Under the closed chassis is a FULLY OPEN-SOURCE, hackable brain you can experiment with and build on. Repo in 🧵↓

Charly Wargnier ♨️

652,744 просмотров • 1 месяц назад

Today I'm excited to introduce Hark, a new artificial intelligence lab building the most advanced, personal intelligence in the world We've been in stealth for 8 months, assembling one of the greatest AI and hardware teams on the planet I want to explain why I started Hark and what we're focused on I've spent the last 3 years working on the hardest AI challenge imaginable: giving AI a humanoid body. On the digital side, I've been using all the existing LLM chatbots - and I have to say, they feel incredibly dumb to me AGI, in the limit, should feel like a sci-fi movie. It should be able to listen and talk. It should have persistent memory and be highly personalized. It should see and touch the world. But we're far from this today We are crafting a new interface to AGI. Intelligence that lets you offload your mental workload into a system that begins to think like you and sometimes ahead of you We started Hark with one goal: build the world's most advanced personal intelligence - paired with next-generation hardware designed to serve as a universal interface between humans and machines
2:14

Today I'm excited to introduce Hark, a new artificial intelligence lab building the most advanced, personal intelligence in the world We've been in stealth for 8 months, assembling one of the greatest AI and hardware teams on the planet I want to explain why I started Hark and what we're focused on I've spent the last 3 years working on the hardest AI challenge imaginable: giving AI a humanoid body. On the digital side, I've been using all the existing LLM chatbots - and I have to say, they feel incredibly dumb to me AGI, in the limit, should feel like a sci-fi movie. It should be able to listen and talk. It should have persistent memory and be highly personalized. It should see and touch the world. But we're far from this today We are crafting a new interface to AGI. Intelligence that lets you offload your mental workload into a system that begins to think like you and sometimes ahead of you We started Hark with one goal: build the world's most advanced personal intelligence - paired with next-generation hardware designed to serve as a universal interface between humans and machines

Brett Adcock

1,415,284 просмотров • 6 месяцев назад

384GB of VRAM. On your desk. Not in a datacenter. Autonomous, the company behind SmartDesk, just open sourced complete build guides for a personal AI computer that runs open models on hardware no one can switch off. It's called Autonomous Computer. Three configurations, one philosophy: a model you rent can be cut off overnight. A model running in your own house can't. → Home build: 2x RTX 5090 workstation → Team build: 4x RTX PRO 6000 Blackwell, 384GB VRAM → On-prem business build: 8x RTX 4090/5090, up to 256GB VRAM Every config ships with the full bill of materials, 3D printable and CNC housing files, wiring diagrams, BIOS tuning, and assembly photos. Software side covers OS setup, NVIDIA drivers, and serving open models through Ollama, vLLM, and llama.cpp. Fork it. Change it. Build it. Sell it. MIT License. 100% Opensource. Repo:
0:22

384GB of VRAM. On your desk. Not in a datacenter. Autonomous, the company behind SmartDesk, just open sourced complete build guides for a personal AI computer that runs open models on hardware no one can switch off. It's called Autonomous Computer. Three configurations, one philosophy: a model you rent can be cut off overnight. A model running in your own house can't. → Home build: 2x RTX 5090 workstation → Team build: 4x RTX PRO 6000 Blackwell, 384GB VRAM → On-prem business build: 8x RTX 4090/5090, up to 256GB VRAM Every config ships with the full bill of materials, 3D printable and CNC housing files, wiring diagrams, BIOS tuning, and assembly photos. Software side covers OS setup, NVIDIA drivers, and serving open models through Ollama, vLLM, and llama.cpp. Fork it. Change it. Build it. Sell it. MIT License. 100% Opensource. Repo:

Harman

48,089 просмотров • 2 месяцев назад