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From Conference on Robot Learning, cofounder Michael Cho - Rbt/Acc shared BitRobot’s vision with the world’s leading robotics minds: Crypto will drastically accelerate embodied AI research. We're building an open network where anyone can contribute to robotics R&D and get rewarded. Watch the keynote ↓

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BitRobot Network

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20,804 görüntüleme • 9 ay önce •via X (Twitter)

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At CoRL 2025, BitRobot brought crypto to the world’s top robotics stage. Our keynote shared how onchain coordination can accelerate embodied AI from data collection to deployment — and we unveiled our $5M Grand Challenges Fund. Recap video ↓
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At CoRL 2025, BitRobot brought crypto to the world’s top robotics stage. Our keynote shared how onchain coordination can accelerate embodied AI from data collection to deployment — and we unveiled our $5M Grand Challenges Fund. Recap video ↓

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You asked for it, we delivered. The full keynote is live. In this keynote, we unveil our enhanced vision to become the World’s Ears for AI & Robotics. We are creating the world’s first decentralized infrastructure for real-world audio intelligence. Check-out our new website: Start training Voice AI now & get rewarded: From noise-level mapping to multilingual voice data and the future of live audio streams, Silencio is building the critical audio data layer that will power foundation models, embodied AI, autonomous vehicles, and robotics.
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Thank you @solanaconf Abu Dhabi 2025 for hosting the first-ever Robot Arena with UFB - Ultimate Fighting Bots and io.net. Robot cage fighting is just the start. We're building open robotics on Solana, powering R&D breakthroughs with crowdsourced data, evaluation, and deployment. Accelerate.

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Hugging Face has acquired a French robotics startup, Pollen Robotics, for an undisclosed amount. The Reachy 2 robot, developed by Pollen, is an open-source and VR-compatible bimanual robot for advancing embodied AI, available to order at $70K. Hugging Face, the leading platform for sharing and fine-tuning LLMs, is also building LeRobot - a platform for providing models, tools, and datasets for robotics AI. Hugging Face was valued at $4.5B in the last round.
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Hugging Face has acquired a French robotics startup, Pollen Robotics, for an undisclosed amount. The Reachy 2 robot, developed by Pollen, is an open-source and VR-compatible bimanual robot for advancing embodied AI, available to order at $70K. Hugging Face, the leading platform for sharing and fine-tuning LLMs, is also building LeRobot - a platform for providing models, tools, and datasets for robotics AI. Hugging Face was valued at $4.5B in the last round.

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1/ Cherry AI Robotics is building the world’s first data layer for robotics. Every autonomous robot needs a neural network to operate, which requires massive domain-specific data. Cherry AI Robotics has an entire ecosystem of products with 200k+ communities and 800k+ users. These products generate large amounts of data, which is parsed to create valuable data sets for robotics. Learn more:
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1/ Cherry AI Robotics is building the world’s first data layer for robotics. Every autonomous robot needs a neural network to operate, which requires massive domain-specific data. Cherry AI Robotics has an entire ecosystem of products with 200k+ communities and 800k+ users. These products generate large amounts of data, which is parsed to create valuable data sets for robotics. Learn more:

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A few months ago we set out to understand exactly how our models can be used to accelerate progress in robotics and other AI systems that don’t just represent the world, but are actually able to interact with it. We’ve been collaborating with leading companies in the space and we’ve developed an initial approach that we're now opening up to accelerate development across the industry. Our fifth announcement is GWM Robotics. GWM Robotics is a learned simulator that generates synthetic data for scalable robot training and policy evaluation, removing the bottlenecks of physical hardware.

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The world today is built for humans, & cities built for cars... The world tomorrow will be built around the evolution of robotics. It was a pleasure hosting this week's Robotics episode of the Super Cycle Pod with Michael Cho - Rbt/Acc (BitRobot Network) & Nils of (Auki) have packed this full of insanely valuable insights: 0:00 - Intro + wen terminator? 5:13 - Robotics vs "GPT moment" 7:08 - Privacy in the world of robotics 11:40 - Web3 robotics + intro to frodobots / bitrobot 14:50 - Impact of $HNT on Michael and Nils 17:06 - Intro to $AUKI 19:26 - Why does dePIN as an investable asset suck? 25:36 - $AUKI community building philosophy 28:30 - Bitrobot mission w/ PhD researchers 31:40 - Bitrobot subnet structure 35:28 - Bitrobot value accrual + Impact 39:40 - $AUKI and proving people wrong 42:20 - Robotics is the biggest industry in the world 50:16 - Dangers of physical AI 55:25 - Human Philosophy in Physical AI 57:05 - How cities will change w/ robots 1:03:20 - Skills of the future 1:06:32 - Responsibility as innovators in robotics Where do you think we are in the robotics cycle? My DMs are open to teams wanting to chat about what they're building.
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The world today is built for humans, & cities built for cars... The world tomorrow will be built around the evolution of robotics. It was a pleasure hosting this week's Robotics episode of the Super Cycle Pod with Michael Cho - Rbt/Acc (BitRobot Network) & Nils of (Auki) have packed this full of insanely valuable insights: 0:00 - Intro + wen terminator? 5:13 - Robotics vs "GPT moment" 7:08 - Privacy in the world of robotics 11:40 - Web3 robotics + intro to frodobots / bitrobot 14:50 - Impact of $HNT on Michael and Nils 17:06 - Intro to $AUKI 19:26 - Why does dePIN as an investable asset suck? 25:36 - $AUKI community building philosophy 28:30 - Bitrobot mission w/ PhD researchers 31:40 - Bitrobot subnet structure 35:28 - Bitrobot value accrual + Impact 39:40 - $AUKI and proving people wrong 42:20 - Robotics is the biggest industry in the world 50:16 - Dangers of physical AI 55:25 - Human Philosophy in Physical AI 57:05 - How cities will change w/ robots 1:03:20 - Skills of the future 1:06:32 - Responsibility as innovators in robotics Where do you think we are in the robotics cycle? My DMs are open to teams wanting to chat about what they're building.

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The 2025 World Robot Conference kicked off on Aug 8 in Beijing E-Town, bringing together over 200 robotics enterprises — including Unitree and SIASUN — and unveiling more than 100 debut products. China is strengthening its foundations in scientific research and fostering collaborative innovation across government, industry, academia and research, refining technical standards and certification, cultivating open-source hardware and software ecosystems, and accelerating the adoption of humanoid robots. China is expanding its global robotics cooperation network, deepening collaboration in R&D, industry development, standard-setting, talent training and safety governance. The country is also promoting AI ethics research and public science education while working with international partners to build a globally integrated robotics innovation ecosystem.

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Robotics: coding agents’ next frontier. So how good are they? We introduce CaP-X: an open-source framework and benchmark for coding agents, where they write code for robot perception and control, execute it on sim and real robots, observe the outcomes, and iteratively improve code reliability. From NVIDIA Berkeley AI Research CMU Robotics Institute Stanford AI Lab 🧵

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2:09

Jensen Huang explains that AI has progressed through four major phases. The first wave was Perception AI, where deep learning enabled superhuman vision and speech recognition. The second wave was Generative AI, allowing AI to create text, images, video, and more. We are now in the third wave, Reasoning AI, where models can think through problems, apply logic, and even conduct research. The fourth wave will be Physical AI, where models gain real-world understanding and common sense, leading to advanced robotics.

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Robotics has changed dramatically over the last eight years. Ted Xiao has been involved in the cutting edge of robot learning through this period, spending those eight years at Google Brain/Google Deepmind. And he’s identified three eras of robot learning. These eras are: - The Era of Existence Proofs - trying different methods like QT-Opt, on-robot RL - The Era of Foundation Models - transitioning to data collection and clean objectives (i.e. supervised learning) - The Era of Scaling - orders of magnitude more data and larger models, enabling reasoning, long-horizon actions, and cross-embodiment transfer Watch Episode 78 of RoboPapers, with Michael Cho - Rbt/Acc and Jiafei Duan to learn more!
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Robotics has changed dramatically over the last eight years. Ted Xiao has been involved in the cutting edge of robot learning through this period, spending those eight years at Google Brain/Google Deepmind. And he’s identified three eras of robot learning. These eras are: - The Era of Existence Proofs - trying different methods like QT-Opt, on-robot RL - The Era of Foundation Models - transitioning to data collection and clean objectives (i.e. supervised learning) - The Era of Scaling - orders of magnitude more data and larger models, enabling reasoning, long-horizon actions, and cross-embodiment transfer Watch Episode 78 of RoboPapers, with Michael Cho - Rbt/Acc and Jiafei Duan to learn more!

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1/ New episode – Enabling AI Models to Drive Robots with Michael Cho - Rbt/Acc from BitRobot Network Hosts: Connor Lovely 🥷 EV3 Sal We discuss: - Building the world's largest robotic driving dataset - Working with researchers from Google DeepMind - Launching a memecoin ($SAM) pre-TGE Timestamps: 00:00 - Introduction 01:47 - Intersection of Robotics and AI 02:50 - Real-World Evaluation vs. Digital AI 06:00 - The Importance of Real-World Testing 07:07 - Mapping and Navigation in Robotics 08:12 - Value of Real-World Data for AI 09:38 - Differences in Data Utility 13:07 - Exploring Different Robotic Form Factors 14:04 - Cross-Embodiment in Robotics 16:35 - Introduction to BitRobot 17:30 - Transition from Frotobots to BitRobot 22:05 - Future Plans for BitRobot 24:27 - Meme Coins in Community Building 27:46 - Conclusion Watch on all platforms below ⬇️
29:16

1/ New episode – Enabling AI Models to Drive Robots with Michael Cho - Rbt/Acc from BitRobot Network Hosts: Connor Lovely 🥷 EV3 Sal We discuss: - Building the world's largest robotic driving dataset - Working with researchers from Google DeepMind - Launching a memecoin ($SAM) pre-TGE Timestamps: 00:00 - Introduction 01:47 - Intersection of Robotics and AI 02:50 - Real-World Evaluation vs. Digital AI 06:00 - The Importance of Real-World Testing 07:07 - Mapping and Navigation in Robotics 08:12 - Value of Real-World Data for AI 09:38 - Differences in Data Utility 13:07 - Exploring Different Robotic Form Factors 14:04 - Cross-Embodiment in Robotics 16:35 - Introduction to BitRobot 17:30 - Transition from Frotobots to BitRobot 22:05 - Future Plans for BitRobot 24:27 - Meme Coins in Community Building 27:46 - Conclusion Watch on all platforms below ⬇️

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New Episode: Michael Cho - Rbt/Acc, co-founder and CEO of FrodoBots and Ultimate Fighting Bots. We talk about Michael’s journey, a near-death plane crash that reshaped his outlook, his passion for robotics, and data collection via real-world games. His big thesis: aligning economic incentives for robotics work through the BitRobot Network. 00:00 Introduction 01:30 Potential of robot fighting 02:02 Robotic gaming and entertainment 02:35 Inspiration from sci-fi and robotics passion 03:10 Entrepreneurial journey and impact of a plane crash 05:38 Michael's Background 08:32 What is FrodoBots 10:35 Data collection through robotic gaming 12:07 Human vs. AI competitions in robotics 13:42 The limiting factor in embodied AI 15:34 Challenges in robotic AI evaluation 21:49 BitRobot Network 23:58 Distributed architecture and socio-economics 30:47 RoboPapers podcast 35:14 Hardware limitations in humanoid robotics 45:46 Things new founders could focus on
48:42

New Episode: Michael Cho - Rbt/Acc, co-founder and CEO of FrodoBots and Ultimate Fighting Bots. We talk about Michael’s journey, a near-death plane crash that reshaped his outlook, his passion for robotics, and data collection via real-world games. His big thesis: aligning economic incentives for robotics work through the BitRobot Network. 00:00 Introduction 01:30 Potential of robot fighting 02:02 Robotic gaming and entertainment 02:35 Inspiration from sci-fi and robotics passion 03:10 Entrepreneurial journey and impact of a plane crash 05:38 Michael's Background 08:32 What is FrodoBots 10:35 Data collection through robotic gaming 12:07 Human vs. AI competitions in robotics 13:42 The limiting factor in embodied AI 15:34 Challenges in robotic AI evaluation 21:49 BitRobot Network 23:58 Distributed architecture and socio-economics 30:47 RoboPapers podcast 35:14 Hardware limitations in humanoid robotics 45:46 Things new founders could focus on

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VLAI Robotics Launches High-Dexterity Dual-Arm Robot Starting at ~$5,500 USD VLAI Robotics, utilizing the open-source design of Japan’s OpenArm team, has introduced a high-dexterity, low-cost bimanual robotic system. The product is priced from 39,900 RMB (approximately 5,500 USD), making high-level research tools accessible to institutions and developers. The robot features a human-scale, arm-hand integrated design with up to 16 DOF (8 DOF per arm, including the gripper). It can handle a dual-arm peak payload of 12 kg while maintaining high precision. A key breakthrough is its ability to replicate human upper limb movement trajectories, which enhances data quality for imitation learning and remote operation. VLAI Robotics handled the domestic engineering, manufacturing, and VLA (Vision-Language-Action) algorithm integration, with quality control organized according to the strict standards of the OpenArm R&D framework. The robot is highly adaptable for research, education, and Physical AI training, supporting easy expansion for features like VR teleoperation.
1:43

VLAI Robotics Launches High-Dexterity Dual-Arm Robot Starting at ~$5,500 USD VLAI Robotics, utilizing the open-source design of Japan’s OpenArm team, has introduced a high-dexterity, low-cost bimanual robotic system. The product is priced from 39,900 RMB (approximately 5,500 USD), making high-level research tools accessible to institutions and developers. The robot features a human-scale, arm-hand integrated design with up to 16 DOF (8 DOF per arm, including the gripper). It can handle a dual-arm peak payload of 12 kg while maintaining high precision. A key breakthrough is its ability to replicate human upper limb movement trajectories, which enhances data quality for imitation learning and remote operation. VLAI Robotics handled the domestic engineering, manufacturing, and VLA (Vision-Language-Action) algorithm integration, with quality control organized according to the strict standards of the OpenArm R&D framework. The robot is highly adaptable for research, education, and Physical AI training, supporting easy expansion for features like VR teleoperation.

RoboHub🤖

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Hugging Face CEO Clem Delangue predicts that a growing share of AI inference will run locally, on-device. It's faster. Cheaper. Private by default. And as open source AI moves from apps to machines, it could trigger “some sort of ChatGPT moment for robotics.” The next AI breakthrough will happen where intelligence becomes embodied, cheap, private, and open.
1:27

Hugging Face CEO Clem Delangue predicts that a growing share of AI inference will run locally, on-device. It's faster. Cheaper. Private by default. And as open source AI moves from apps to machines, it could trigger “some sort of ChatGPT moment for robotics.” The next AI breakthrough will happen where intelligence becomes embodied, cheap, private, and open.

vitrupo

37,764 görüntüleme • 1 yıl önce

Today we are excited to open up Neuracore to the academic community! Neuracore is a new data foundation built to accelerate robot learning by removing one of the field’s biggest bottlenecks: capturing and working with high-fidelity multimodal robotics data. For the first time, researchers can store, view, and work with robotics data in a cloud-native system built specifically for large-scale learning, and we are making this core platform completely free for academia. The platform lets teams capture every sensor at its native rate, store and visualize data without loss, and then train and deploy models locally using our open-source code (Link in the comments). We are rolling out access to select academic institutions first. Anyone with an academic email can sign up, and if your institution is not part of the initial rollout, you will be able to join the waitlist directly. Beyond providing this infrastructure, we see an opportunity to build a global community where engineers and researchers can share, collaborate, and advance the frontier of robot learning together. Supported by our recent $3M pre-seed round led by Earlybird VC, we are excited to take this mission even further. Our long-term goal is for Neuracore to become the natural home for cutting-edge robot learning algorithms and real-world robotics experimentation, helping accelerate the next wave of Physical AI.
1:00

Today we are excited to open up Neuracore to the academic community! Neuracore is a new data foundation built to accelerate robot learning by removing one of the field’s biggest bottlenecks: capturing and working with high-fidelity multimodal robotics data. For the first time, researchers can store, view, and work with robotics data in a cloud-native system built specifically for large-scale learning, and we are making this core platform completely free for academia. The platform lets teams capture every sensor at its native rate, store and visualize data without loss, and then train and deploy models locally using our open-source code (Link in the comments). We are rolling out access to select academic institutions first. Anyone with an academic email can sign up, and if your institution is not part of the initial rollout, you will be able to join the waitlist directly. Beyond providing this infrastructure, we see an opportunity to build a global community where engineers and researchers can share, collaborate, and advance the frontier of robot learning together. Supported by our recent $3M pre-seed round led by Earlybird VC, we are excited to take this mission even further. Our long-term goal is for Neuracore to become the natural home for cutting-edge robot learning algorithms and real-world robotics experimentation, helping accelerate the next wave of Physical AI.

Neuracore

40,620 görüntüleme • 7 ay önce

Modern AI is confined to the digital world. At Skild AI, we are building towards AGI for the real world, unconstrained by robot type or task — a single, omni-bodied brain. Today, we are sharing our journey, starting with early milestones, with more to come in the weeks ahead. Our Mission: Artificial General Intelligence grounded in the physical world. We believe AGI that can truly understand and reason in the real world can only be built through grounding in the physical world. Our Vision: Any robot, Any task, One brain. We tackle robotics in its full generality – building a continually improving, omni-bodied brain that can control any hardware for any task. Who are we? A passionate group of scientists & engineers driven by our shared vision. We have been researching AI and robotics for more than a decade. Our team includes pioneers of self-supervised learning, curiosity-driven exploration, end-to-end sim2real for visual locomotion, dexterous manipulation, learning from human videos, robot parkour, and many more. Many of these works have won awards at top-tier AI and Robotics conferences. Our team has also built production-ready systems at Anduril, Tesla, Nvidia, Meta, Kitty Hawk, Google, Everyday Robotics, and Amazon. Join us in our mission to build the robot brains of tomorrow.
2:48

Modern AI is confined to the digital world. At Skild AI, we are building towards AGI for the real world, unconstrained by robot type or task — a single, omni-bodied brain. Today, we are sharing our journey, starting with early milestones, with more to come in the weeks ahead. Our Mission: Artificial General Intelligence grounded in the physical world. We believe AGI that can truly understand and reason in the real world can only be built through grounding in the physical world. Our Vision: Any robot, Any task, One brain. We tackle robotics in its full generality – building a continually improving, omni-bodied brain that can control any hardware for any task. Who are we? A passionate group of scientists & engineers driven by our shared vision. We have been researching AI and robotics for more than a decade. Our team includes pioneers of self-supervised learning, curiosity-driven exploration, end-to-end sim2real for visual locomotion, dexterous manipulation, learning from human videos, robot parkour, and many more. Many of these works have won awards at top-tier AI and Robotics conferences. Our team has also built production-ready systems at Anduril, Tesla, Nvidia, Meta, Kitty Hawk, Google, Everyday Robotics, and Amazon. Join us in our mission to build the robot brains of tomorrow.

Skild AI

382,440 görüntüleme • 11 ay önce