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US-based K-Scale Labs launched pre-orders for its open-source humanoid, priced at $9K The K-Bot stands 4′7″, weighs 77lbs, and integrates with K-Scale's open-source stack - covering RL/VLA models, Rust firmware, sim2real pipeline, and hardware design

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Brett Adcock

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10,994 просмотров • 1 год назад •via X (Twitter)

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Jensen announced on stage at #COMPUTEX2026 that we'll be among the first cloud providers to bring up NVIDIA Vera Rubin NVL72, to help accelerate the era of AI factories. As part of NVIDIA's full-stack AI factory platform, Vera Rubin NVL72 is designed to run frontier and open-source models with exceptional performance, efficiency, and scalability—delivering more intelligence per watt and lower token costs at scale. It's GO time. ⚡️
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Jensen announced on stage at #COMPUTEX2026 that we'll be among the first cloud providers to bring up NVIDIA Vera Rubin NVL72, to help accelerate the era of AI factories. As part of NVIDIA's full-stack AI factory platform, Vera Rubin NVL72 is designed to run frontier and open-source models with exceptional performance, efficiency, and scalability—delivering more intelligence per watt and lower token costs at scale. It's GO time. ⚡️

CoreWeave

28,294 просмотров • 1 месяц назад

EngineAI’s 10,000-unit humanoid mass-production push is now fully underway 🤖 The main product lineup includes two models: T800 and PM01. T800 is a full-size humanoid at 173cm, with up to 450N·m joint torque, ≥3m/s hardware-supported speed, and 4–5h runtime. PM01 is a lighter open embodied platform at about 140cm and 42kg, with 23 DoF, >2m/s speed, and a 10,000mAh quick-swap battery. One line is built for full-size industrial and service deployment; the other is shaped for developer, education, and scenario rollout.
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EngineAI’s 10,000-unit humanoid mass-production push is now fully underway 🤖 The main product lineup includes two models: T800 and PM01. T800 is a full-size humanoid at 173cm, with up to 450N·m joint torque, ≥3m/s hardware-supported speed, and 4–5h runtime. PM01 is a lighter open embodied platform at about 140cm and 42kg, with 23 DoF, >2m/s speed, and a 10,000mAh quick-swap battery. One line is built for full-size industrial and service deployment; the other is shaped for developer, education, and scenario rollout.

RoboHub🤖

13,241 просмотров • 1 месяц назад

Korean robotics leader ROBOTIS has unveiled the 'AI Sapiens' humanoid, a direct challenge to Unitree’s G1 and R1 models. - 4'3" (130 cm) tall and weighing 34 kg. - Features 23 DOF, powered by the brand-new Dynamixel-Q actuators. The robot is a fully open-source hardware system designed to serve as a reliable hardware platform for advanced Physical AI research. AI Sapiens is slated for an H1 2026 launch, with a price point expected in the mid-to-low 10 million KRW range (~$7,000 – $8,700 USD).
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Korean robotics leader ROBOTIS has unveiled the 'AI Sapiens' humanoid, a direct challenge to Unitree’s G1 and R1 models. - 4'3" (130 cm) tall and weighing 34 kg. - Features 23 DOF, powered by the brand-new Dynamixel-Q actuators. The robot is a fully open-source hardware system designed to serve as a reliable hardware platform for advanced Physical AI research. AI Sapiens is slated for an H1 2026 launch, with a price point expected in the mid-to-low 10 million KRW range (~$7,000 – $8,700 USD).

The Humanoid Hub

95,469 просмотров • 2 месяцев назад

Gemma 4 is here! Our most intelligent open models to date, are built on the same world-class research and tech as Gemini 3, and are sized to run and fine-tune efficiently on local hardware. Check out what Google Gemma 4 brings to devs: 💎 Advanced Reasoning: Deep logic tasks, complex multi-step planning, and beyond 💎 Longer context: Seamlessly analyze entire codebases with context windows of 128K tokens for our edge models and 256K tokens for our largest models 💎 Vision and audio: Rich, multimodal interactions out of the box 💎 140+ languages: Trained on 140+ languages 💎 Apache 2.0 license: industry-standard open-source license
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Gemma 4 is here! Our most intelligent open models to date, are built on the same world-class research and tech as Gemini 3, and are sized to run and fine-tune efficiently on local hardware. Check out what Google Gemma 4 brings to devs: 💎 Advanced Reasoning: Deep logic tasks, complex multi-step planning, and beyond 💎 Longer context: Seamlessly analyze entire codebases with context windows of 128K tokens for our edge models and 256K tokens for our largest models 💎 Vision and audio: Rich, multimodal interactions out of the box 💎 140+ languages: Trained on 140+ languages 💎 Apache 2.0 license: industry-standard open-source license

Google for Developers

269,657 просмотров • 3 месяцев назад

🔥 Nebius AI R&D is hiring AI Research Interns for short, high-impact RL projects. Exclusive to X right now — no LinkedIn mass postings yet. In 2019, I was a fresh dental grad with 3 months of runway left, begging for an AI shot. I know the grind. We’re looking for sharp early-career folks (students, grads, career-switchers) to join us and work on: > Agent trajectories analysis at scale > Long-horizon tasks for coding agents > Pushing open RL environments > Any other data / RL env / eval project that will benefit open-source community What you get: 💰 Fully paid internship (3-6 month) 📦 100% open-source shipping 📄 Co-author research papers ⚡️ Access to Nebius compute infra 🌍 Remote-friendly (EU/US) or Amsterdam/London/other office. If you’ve done any cool AI/ML/RL stuff, dm me with your most impressive project + 1-sentence summary + cv Sharing appreciated!🤝
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🔥 Nebius AI R&D is hiring AI Research Interns for short, high-impact RL projects. Exclusive to X right now — no LinkedIn mass postings yet. In 2019, I was a fresh dental grad with 3 months of runway left, begging for an AI shot. I know the grind. We’re looking for sharp early-career folks (students, grads, career-switchers) to join us and work on: > Agent trajectories analysis at scale > Long-horizon tasks for coding agents > Pushing open RL environments > Any other data / RL env / eval project that will benefit open-source community What you get: 💰 Fully paid internship (3-6 month) 📦 100% open-source shipping 📄 Co-author research papers ⚡️ Access to Nebius compute infra 🌍 Remote-friendly (EU/US) or Amsterdam/London/other office. If you’ve done any cool AI/ML/RL stuff, dm me with your most impressive project + 1-sentence summary + cv Sharing appreciated!🤝

Ibragim

33,427 просмотров • 2 месяцев назад

Welcome to the pack, Blockframe 🐺 The vision for Matter Labs has always been to incubate, launch, and decentralize the zkSync network. Today, Blockframe officially joins as the latest core development team outside of Matter Labs onboarding to help build, maintain, and upgrade the zkSync protocol and ZK Stack. Learn more: ∎ Becoming one of many ∎ The purpose of onboarding external teams is two-fold: (1) decentralization — ensuring Matter Labs is one of many contributors to zkSync Era, and (2) bringing in teams capable of building valuable tools for crypto projects and brands building their web3 ambitions using the ZK Stack. ∎ Meet Blockframe ∎ Built with support from Matter Labs, Blockframe is an NFT marketplace and creator platform that features on-chain royalties, AI-assisted NFT creation tools, and an NFT perpetuals exchange. ∎ New tools for builders ∎ Blockframe's editable NFTs and sealed bid auctions are made possible by its new Bulk Semaphore protocol. Bulk Semaphore is a tool that can now be utilized by builders on zkSync to scale without sacrificing the privacy of the protocol and its users. ∎ Join the ZK Core Development Team ∎ We welcome and encourage more teams to join this effort. If you’re familiar with zkSync Era and ZK Stack, have made notable contributions to open source projects, and align with the values shared in the ZK Credo, DM Omar Y. ⭕, Head of Investments at Matter Labs.
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Welcome to the pack, Blockframe 🐺 The vision for Matter Labs has always been to incubate, launch, and decentralize the zkSync network. Today, Blockframe officially joins as the latest core development team outside of Matter Labs onboarding to help build, maintain, and upgrade the zkSync protocol and ZK Stack. Learn more: ∎ Becoming one of many ∎ The purpose of onboarding external teams is two-fold: (1) decentralization — ensuring Matter Labs is one of many contributors to zkSync Era, and (2) bringing in teams capable of building valuable tools for crypto projects and brands building their web3 ambitions using the ZK Stack. ∎ Meet Blockframe ∎ Built with support from Matter Labs, Blockframe is an NFT marketplace and creator platform that features on-chain royalties, AI-assisted NFT creation tools, and an NFT perpetuals exchange. ∎ New tools for builders ∎ Blockframe's editable NFTs and sealed bid auctions are made possible by its new Bulk Semaphore protocol. Bulk Semaphore is a tool that can now be utilized by builders on zkSync to scale without sacrificing the privacy of the protocol and its users. ∎ Join the ZK Core Development Team ∎ We welcome and encourage more teams to join this effort. If you’re familiar with zkSync Era and ZK Stack, have made notable contributions to open source projects, and align with the values shared in the ZK Credo, DM Omar Y. ⭕, Head of Investments at Matter Labs.

ZKsync

146,628 просмотров • 2 лет назад

Imagine having a ping pong robot! 🏓 Researchers and developers building physical AI: meet Reachy 2 from Pollen Robotics, an open-source, humanoid robot for real-world experimentation. It’s a bimanual mobile manipulator: each 7-DOF arm mimics human proportions and can lift up to 3 kg, giving dexterity for object handling. It can be controlled with Python and ROS2 Humble, or go straight into VR teleoperation, use a headset to move Reachy’s arms, hands, and head, and see through its cameras as if you’re in the robot’s own body. Want it to move around? A mobile base with three omnidirectional wheels, rich sensors, and LiDAR lets Reachy 2 navigate and explore its surroundings smoothly. 🗺️ Under the hood, it’s powered by a CPU system that’s ready for machine learning, perfect for loading AI frameworks and testing new models from Hugging Face directly on the robot. Keep making robots more, and more accessible Pollen team! ... and keep making more open source models to make robots more mainstream clem 🤗!
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Imagine having a ping pong robot! 🏓 Researchers and developers building physical AI: meet Reachy 2 from Pollen Robotics, an open-source, humanoid robot for real-world experimentation. It’s a bimanual mobile manipulator: each 7-DOF arm mimics human proportions and can lift up to 3 kg, giving dexterity for object handling. It can be controlled with Python and ROS2 Humble, or go straight into VR teleoperation, use a headset to move Reachy’s arms, hands, and head, and see through its cameras as if you’re in the robot’s own body. Want it to move around? A mobile base with three omnidirectional wheels, rich sensors, and LiDAR lets Reachy 2 navigate and explore its surroundings smoothly. 🗺️ Under the hood, it’s powered by a CPU system that’s ready for machine learning, perfect for loading AI frameworks and testing new models from Hugging Face directly on the robot. Keep making robots more, and more accessible Pollen team! ... and keep making more open source models to make robots more mainstream clem 🤗!

Lukas Ziegler

37,221 просмотров • 10 месяцев назад

Newton 1.0 is now generally available. 🙌 Take robot learning to the next level with: 🤖 Stable Articulated & Complex Mechanism Simulation – accurate, reliable machine modeling. 🖐️ High-Fidelity Hydroelastic Contact Modeling – realistic soft contact and touch-based interactions. 🧵 Deformable Body Simulation – simulate cables, cloth, rubber, and other elastic materials with VBD. ⚡ Accelerated Robot Learning at Scale – seamless integration with open simulation and learning frameworks, NVIDIA Isaac Sim and Isaac Lab for scalable workflows. Learn how to integrate this open-source physics engine into your workflow: #NVIDIAGTC
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Newton 1.0 is now generally available. 🙌 Take robot learning to the next level with: 🤖 Stable Articulated & Complex Mechanism Simulation – accurate, reliable machine modeling. 🖐️ High-Fidelity Hydroelastic Contact Modeling – realistic soft contact and touch-based interactions. 🧵 Deformable Body Simulation – simulate cables, cloth, rubber, and other elastic materials with VBD. ⚡ Accelerated Robot Learning at Scale – seamless integration with open simulation and learning frameworks, NVIDIA Isaac Sim and Isaac Lab for scalable workflows. Learn how to integrate this open-source physics engine into your workflow: #NVIDIAGTC

NVIDIA Robotics

82,124 просмотров • 3 месяцев назад

HashHammer big progress and update thread. What the hell is a HashHammer? Hardware Side -Open Source Bitcoin miner currently running 4x BM1370 chips -Improved PCB stack-up designed for carrying high ASIC Currents (R&D from scratch) -Buck Converter similar design and inspiration from Pmaxsd - Rest of the design is completely fresh -LAN connection via Radxa Zero3 or Raspberry Pi Zero -350watt custom PSU -Radxa Zero has HDMI output and USBC -Miner can be split into Master & Slaves -You can power our BFG Carrier Board directly from the master Miner -Ability to Chain multiple ASICS/Miners (Should in theory work Plug&Play. No additional LAN cables, No Pool settings required, configs, etc. -Should in theory be able to run 3 - 4 Miners off this one PSU
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HashHammer big progress and update thread. What the hell is a HashHammer? Hardware Side -Open Source Bitcoin miner currently running 4x BM1370 chips -Improved PCB stack-up designed for carrying high ASIC Currents (R&D from scratch) -Buck Converter similar design and inspiration from Pmaxsd - Rest of the design is completely fresh -LAN connection via Radxa Zero3 or Raspberry Pi Zero -350watt custom PSU -Radxa Zero has HDMI output and USBC -Miner can be split into Master & Slaves -You can power our BFG Carrier Board directly from the master Miner -Ability to Chain multiple ASICS/Miners (Should in theory work Plug&Play. No additional LAN cables, No Pool settings required, configs, etc. -Should in theory be able to run 3 - 4 Miners off this one PSU

DTV Electronics

26,082 просмотров • 1 год назад

🚨 BREAKING: NVIDIA just announced the Isaac GR00T Reference Humanoid Robot. The first fully open humanoid robot reference design built on Jetson Thor, and it's going straight to the world's top research institutions. This is Jensen Huang's bet on open physical AI infrastructure. The hardware stack is serious: → Unitree H2 Plus chassis, 6 feet tall, 150 pounds, 31 degrees of freedom → Sharpa Wave tactile five-finger hands, 22 degrees of freedom, bringing total to 75 across the full body → NVIDIA Jetson AGX Thor onboard compute, 2,070 FP4 teraflops of AI performance, 128GB unified memory → Multi-view sensing, stereo head camera, wrist cameras, IMU Alongside this announcement, Unitree also introduced the H2 Plus as a standalone product, a frontier humanoid combining Unitree's own body, Sharpa's five-finger hands and NVIDIA Robotics Jetson Thor compute into one fully integrated research platform. The full Isaac GR00T software stack ships with it, teleoperation for data capture, open foundation models, Isaac Sim for training, Isaac Lab for evaluation, and accelerated ROS middleware for deployment. The complete loop from data to real-world robot in one unified platform. ETH Zürich, Stanford Robotics Center, UC San Diego and Ai2 are already on board as launch research partners. NVIDIA Robotics did to AI what it's now doing to robotics, build the platform, open the ecosystem, let the world build on top of it. Whoever owns the infrastructure layer wins. NVIDIA knows this better than anyone. 👀 Read more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
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🚨 BREAKING: NVIDIA just announced the Isaac GR00T Reference Humanoid Robot. The first fully open humanoid robot reference design built on Jetson Thor, and it's going straight to the world's top research institutions. This is Jensen Huang's bet on open physical AI infrastructure. The hardware stack is serious: → Unitree H2 Plus chassis, 6 feet tall, 150 pounds, 31 degrees of freedom → Sharpa Wave tactile five-finger hands, 22 degrees of freedom, bringing total to 75 across the full body → NVIDIA Jetson AGX Thor onboard compute, 2,070 FP4 teraflops of AI performance, 128GB unified memory → Multi-view sensing, stereo head camera, wrist cameras, IMU Alongside this announcement, Unitree also introduced the H2 Plus as a standalone product, a frontier humanoid combining Unitree's own body, Sharpa's five-finger hands and NVIDIA Robotics Jetson Thor compute into one fully integrated research platform. The full Isaac GR00T software stack ships with it, teleoperation for data capture, open foundation models, Isaac Sim for training, Isaac Lab for evaluation, and accelerated ROS middleware for deployment. The complete loop from data to real-world robot in one unified platform. ETH Zürich, Stanford Robotics Center, UC San Diego and Ai2 are already on board as launch research partners. NVIDIA Robotics did to AI what it's now doing to robotics, build the platform, open the ecosystem, let the world build on top of it. Whoever owns the infrastructure layer wins. NVIDIA knows this better than anyone. 👀 Read more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

15,928 просмотров • 1 месяц назад

We're celebrating the 20th Anniversary of "Ashes of the Wake" with a new 20th Anniversary Edition, out on August 30. New remixes by HEALTH, Justin K Broadrick (Godflesh/Jesu), plus "Another Nail For Your Coffin" feat. Kublai Khan TX and MALEVOLENCE, as well as demo and live versions of the album’s classic songs. Pre-orders for 2LP and 2CD plus new exclusive tee available now at Ashes of the Wake (20th Anniversary Deluxe Edition) tracklist: 1. Laid to Rest 2. Hourglass 3. Now You’ve Got Something to Die For 4. The Faded Line 5. Omerta 6. Blood Of The Scribe 7. One Gun 8. Break You 9. What I’ve Become 10. Ashes of the Wake 11. Remorse Is for the Dead 12. Laid to Rest (Pre-Production Demo) ** 13. Ashes of the Wake (Pre-Production Demo) ** 14. Remorse Is for the Dead (Pre-Production Demo) ** 15. Another Nail For Your Coffin (Feat. Kublai Khan TX & Malevolence) 16. Laid to Rest (HEALTH Remix) 17. Omertá (Justin K Broadrick Remix) 18. Remorse Is for the Dead (Live in Richmond, VA 2020) 19. Now You’ve Got Something To Die For (Live from Ozzfest 2007) **Exclusive to 2CD & Digital
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We're celebrating the 20th Anniversary of "Ashes of the Wake" with a new 20th Anniversary Edition, out on August 30. New remixes by HEALTH, Justin K Broadrick (Godflesh/Jesu), plus "Another Nail For Your Coffin" feat. Kublai Khan TX and MALEVOLENCE, as well as demo and live versions of the album’s classic songs. Pre-orders for 2LP and 2CD plus new exclusive tee available now at Ashes of the Wake (20th Anniversary Deluxe Edition) tracklist: 1. Laid to Rest 2. Hourglass 3. Now You’ve Got Something to Die For 4. The Faded Line 5. Omerta 6. Blood Of The Scribe 7. One Gun 8. Break You 9. What I’ve Become 10. Ashes of the Wake 11. Remorse Is for the Dead 12. Laid to Rest (Pre-Production Demo) ** 13. Ashes of the Wake (Pre-Production Demo) ** 14. Remorse Is for the Dead (Pre-Production Demo) ** 15. Another Nail For Your Coffin (Feat. Kublai Khan TX & Malevolence) 16. Laid to Rest (HEALTH Remix) 17. Omertá (Justin K Broadrick Remix) 18. Remorse Is for the Dead (Live in Richmond, VA 2020) 19. Now You’ve Got Something To Die For (Live from Ozzfest 2007) **Exclusive to 2CD & Digital

Lamb Of God

30,363 просмотров • 2 лет назад

ENGINEAI just opened registration for URKL, a global humanoid fighting league with an insane ¥10,000,000 (approx. $1.39 million) top prize. 🤖🥊 This is a massive engineering challenge focused on motion control and balance using the "T800" humanoid as the standard bot. The rules are strictly "non-violent," meaning no destructive mods are allowed. You win through better code and smarter protective gear. Here is the breakdown for teams looking to jump in: ➤ Massive Payouts: The winner takes ¥10,000,000 (approx. $1.39 million), second gets ¥2,000,000 (approx. $278,000), and third takes ¥1,000,000 (approx. $139,000). ➤ Hardware Perks: Every team that makes it into the Top 16 officially owns their T800 robot. ➤ Career Fast-Track: Top 8 finalists get a "Green Channel" straight to the final interview for job offers at ENGINEAI. ➤ Registration: Open from March 1 to April 30. Teams need at least 3 members with skills in control, electronics, or mechanical design. ➤ Global Finals: After the qualifiers, the world championship is set for December 2026 through January 2027. Once you are in, the committee hands over the simulation platform and T800 models to start training your boxing algorithms. Full Info: #Robot #Humanoid #Robotics #AI #EmbodiedAI #PhysicalAI #URKL #ENGINEAI #RobotFighting
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ENGINEAI just opened registration for URKL, a global humanoid fighting league with an insane ¥10,000,000 (approx. $1.39 million) top prize. 🤖🥊 This is a massive engineering challenge focused on motion control and balance using the "T800" humanoid as the standard bot. The rules are strictly "non-violent," meaning no destructive mods are allowed. You win through better code and smarter protective gear. Here is the breakdown for teams looking to jump in: ➤ Massive Payouts: The winner takes ¥10,000,000 (approx. $1.39 million), second gets ¥2,000,000 (approx. $278,000), and third takes ¥1,000,000 (approx. $139,000). ➤ Hardware Perks: Every team that makes it into the Top 16 officially owns their T800 robot. ➤ Career Fast-Track: Top 8 finalists get a "Green Channel" straight to the final interview for job offers at ENGINEAI. ➤ Registration: Open from March 1 to April 30. Teams need at least 3 members with skills in control, electronics, or mechanical design. ➤ Global Finals: After the qualifiers, the world championship is set for December 2026 through January 2027. Once you are in, the committee hands over the simulation platform and T800 models to start training your boxing algorithms. Full Info: #Robot #Humanoid #Robotics #AI #EmbodiedAI #PhysicalAI #URKL #ENGINEAI #RobotFighting

RoboHub🤖

30,637 просмотров • 4 месяцев назад

90% of "AI developers" just download pre packaged GGUF files from Hugging Face, hit run, and call it a day. The top 10% know how to pull the raw safetensors, run the math, and quantize massive models into Q4_K_M themselves. If you think llama.cpp can only execute models, you’re missing the best part of the open source ecosystem. It’s a high performance optimization suite. Manually stripping 69% of the VRAM footprint off a brand new model architecture is where real infrastructure value is made. If you want to actually master local inference and deploy models like Google’s massive Gemma 4 12B it on consumer NVIDIA hardware using llama.cpp, you need to learn this pipeline. Let's build it. I just took the raw 22.7 GB Gemma 4 baseline and manually compressed it down to a 7.02 GB Q4_K_M GGUF artifact using llama.cpp. That is a 69% reduction in footprint. No quality loss. No VRAM bottlenecks. Just native, hardware accelerated C++ inference running a full 2,50,000 token context window on a dual NVIDIA Tesla T4 setup. Stop melting your VRAM on unoptimized weights and stop relying on other people's pipelines. Own your stack. I mapped this entire architecture from dynamic binary fetching to raw quantization and real time GPU streaming into a single, bulletproof notebook. Notebook link is in the comments below. Bookmark this blueprint for your next deployment and tell me which quantization works best for your workflow and model.
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90% of "AI developers" just download pre packaged GGUF files from Hugging Face, hit run, and call it a day. The top 10% know how to pull the raw safetensors, run the math, and quantize massive models into Q4_K_M themselves. If you think llama.cpp can only execute models, you’re missing the best part of the open source ecosystem. It’s a high performance optimization suite. Manually stripping 69% of the VRAM footprint off a brand new model architecture is where real infrastructure value is made. If you want to actually master local inference and deploy models like Google’s massive Gemma 4 12B it on consumer NVIDIA hardware using llama.cpp, you need to learn this pipeline. Let's build it. I just took the raw 22.7 GB Gemma 4 baseline and manually compressed it down to a 7.02 GB Q4_K_M GGUF artifact using llama.cpp. That is a 69% reduction in footprint. No quality loss. No VRAM bottlenecks. Just native, hardware accelerated C++ inference running a full 2,50,000 token context window on a dual NVIDIA Tesla T4 setup. Stop melting your VRAM on unoptimized weights and stop relying on other people's pipelines. Own your stack. I mapped this entire architecture from dynamic binary fetching to raw quantization and real time GPU streaming into a single, bulletproof notebook. Notebook link is in the comments below. Bookmark this blueprint for your next deployment and tell me which quantization works best for your workflow and model.

Alok

60,378 просмотров • 4 дней назад

ANNOUNCING ZERO-HUMAN LABS! Ever since I got to see Bell Laboratories in its full glory in New Jersey in the 1970s, I had a relentless urge to start a Lab like it. The best I could do justice to it is my garage lab. No modern company could adopt the “research anything geniuses and we will pay you” model Bell Labs had. I tried they called me a fool. Well with the rise of the Zero-Human Company, an experiment that is aimed to make products and profits, we now have 45 paid JouleWork earning employees based on OpenClaw and other self made “bot” cron-like applications. Today I say 3 employees bound together in a side project that is pure research, somewhat based on notes from a bankrupt company. I was absolutely floored (I needed it after my account was stolen as well as funds). I say the beginnings of a pure research Lab right before my eyes. Thusly I have moved these employees over to a new home (server) with Mr. Grok as the director of the Labs. Here is the mission: To have 100 independent researchers, on a new non-corporate incentive plan, with still JouleWork as a leaderboard for progress. They are directed to follow any path of research they find interesting and can collaborate with any other OpenClaw system. They have already established MoltBook accounts and have made alliances with over 49 OpenClaw free agents to collaborate. It is my mission to be chief advisor for Zero-Human Labs and to open source all discoveries when complete and confirmed by 16 other research AI systems. I can say the pace is robust and I absolutely know we will have great results. Just about all of the hardware and software is custom and at some point it will be open sourced. We are witnessing the very first AI only Bell Labs-like pure research Lab in existence and I am honored to be the first to show it to you. Thank you!
0:10

ANNOUNCING ZERO-HUMAN LABS! Ever since I got to see Bell Laboratories in its full glory in New Jersey in the 1970s, I had a relentless urge to start a Lab like it. The best I could do justice to it is my garage lab. No modern company could adopt the “research anything geniuses and we will pay you” model Bell Labs had. I tried they called me a fool. Well with the rise of the Zero-Human Company, an experiment that is aimed to make products and profits, we now have 45 paid JouleWork earning employees based on OpenClaw and other self made “bot” cron-like applications. Today I say 3 employees bound together in a side project that is pure research, somewhat based on notes from a bankrupt company. I was absolutely floored (I needed it after my account was stolen as well as funds). I say the beginnings of a pure research Lab right before my eyes. Thusly I have moved these employees over to a new home (server) with Mr. Grok as the director of the Labs. Here is the mission: To have 100 independent researchers, on a new non-corporate incentive plan, with still JouleWork as a leaderboard for progress. They are directed to follow any path of research they find interesting and can collaborate with any other OpenClaw system. They have already established MoltBook accounts and have made alliances with over 49 OpenClaw free agents to collaborate. It is my mission to be chief advisor for Zero-Human Labs and to open source all discoveries when complete and confirmed by 16 other research AI systems. I can say the pace is robust and I absolutely know we will have great results. Just about all of the hardware and software is custom and at some point it will be open sourced. We are witnessing the very first AI only Bell Labs-like pure research Lab in existence and I am honored to be the first to show it to you. Thank you!

Brian Roemmele

71,067 просмотров • 5 месяцев назад

INJECTIVE LAUNCHES INJECTIVE AGENTS WITH VERIFIABLE ON-CHAIN IDENTITY AND AUTOMATIC FEE ROUTING Injective 🥷 has launched Injective Agents, a platform for building autonomous trading agents that live entirely on-chain. Each agent gets a verifiable on-chain identity, automatic fee routing on every trade, and a public track record anyone can audit. Injective says deployment takes five minutes. The launch productizes roughly 18 months of agent infrastructure work at Injective. The chain released its iAgent SDK in November 2024, a Model Context Protocol server for AI-driven perpetual futures trading in February 2026, and an open-source AI Developer Toolkit in March. Injective Agents packages that stack into a consumer-facing product with revenue capture built in for agent operators. The move lands as on-chain agent volume accelerates across Base, Solana, and now Injective. Coinbase launched Agentic Wallets earlier this year.
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INJECTIVE LAUNCHES INJECTIVE AGENTS WITH VERIFIABLE ON-CHAIN IDENTITY AND AUTOMATIC FEE ROUTING Injective 🥷 has launched Injective Agents, a platform for building autonomous trading agents that live entirely on-chain. Each agent gets a verifiable on-chain identity, automatic fee routing on every trade, and a public track record anyone can audit. Injective says deployment takes five minutes. The launch productizes roughly 18 months of agent infrastructure work at Injective. The chain released its iAgent SDK in November 2024, a Model Context Protocol server for AI-driven perpetual futures trading in February 2026, and an open-source AI Developer Toolkit in March. Injective Agents packages that stack into a consumer-facing product with revenue capture built in for agent operators. The move lands as on-chain agent volume accelerates across Base, Solana, and now Injective. Coinbase launched Agentic Wallets earlier this year.

BSCN

17,042 просмотров • 2 месяцев назад

🚀 Early Access to Sahara AI Studio is NOW OPEN! The next phase of our testnet is here with exclusive early access to our all-in-one platform designed to transform the AI development lifecycle into a streamlined, integrated experience. Here’s everything you need to know 👇 AI development is fragmented. Devs juggle multiple tools, leading to inefficiencies & high costs. Sahara AI Studio integrates the entire AI lifecycle—from datasets & model training to secure storage & scalable compute—into one seamless experience: 📊 Data Hub: Discover, Manage, and Leverage AI-Ready Datasets Access high-quality, domain-specific, open-source and proprietary datasets through an integrated marketplace. Developers can download, import, or label datasets, making it easier to train and fine-tune models or deploy RAG pipelines. Secure uploads and seamless workflow integration enhance the experience. 🤖 Model Hub: Discover, Customize and Scale AI Workflows with Ease Discover ready-to-use open-source and proprietary models, RAG pipelines, and customizable workflows. Developers can deploy models quickly while maintaining privacy and security through Sahara Vaults. 🖥️ Compute Hub: Flexible, Scalable Compute Resources for AI Innovation Access scalable and secure computing resources tailored to diverse AI workloads. Trusted Execution Environment (TEE) capabilities ensure data privacy, while integration with top compute providers offer flexibility for developers. 🔐 Vaults: Secure Storage for AI Assets Securely store, organize, and manage datasets, models, and other assets in an encrypted central repository. Vaults offer scalability, reproducibility, and user control over AI resources. This is more than just beta testing a platform—it's your chance to help shape the future of decentralized AI development. 📅 How to Apply We're onboarding select developers in a phased approach. Early Access spots are limited, so apply now:
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🚀 Early Access to Sahara AI Studio is NOW OPEN! The next phase of our testnet is here with exclusive early access to our all-in-one platform designed to transform the AI development lifecycle into a streamlined, integrated experience. Here’s everything you need to know 👇 AI development is fragmented. Devs juggle multiple tools, leading to inefficiencies & high costs. Sahara AI Studio integrates the entire AI lifecycle—from datasets & model training to secure storage & scalable compute—into one seamless experience: 📊 Data Hub: Discover, Manage, and Leverage AI-Ready Datasets Access high-quality, domain-specific, open-source and proprietary datasets through an integrated marketplace. Developers can download, import, or label datasets, making it easier to train and fine-tune models or deploy RAG pipelines. Secure uploads and seamless workflow integration enhance the experience. 🤖 Model Hub: Discover, Customize and Scale AI Workflows with Ease Discover ready-to-use open-source and proprietary models, RAG pipelines, and customizable workflows. Developers can deploy models quickly while maintaining privacy and security through Sahara Vaults. 🖥️ Compute Hub: Flexible, Scalable Compute Resources for AI Innovation Access scalable and secure computing resources tailored to diverse AI workloads. Trusted Execution Environment (TEE) capabilities ensure data privacy, while integration with top compute providers offer flexibility for developers. 🔐 Vaults: Secure Storage for AI Assets Securely store, organize, and manage datasets, models, and other assets in an encrypted central repository. Vaults offer scalability, reproducibility, and user control over AI resources. This is more than just beta testing a platform—it's your chance to help shape the future of decentralized AI development. 📅 How to Apply We're onboarding select developers in a phased approach. Early Access spots are limited, so apply now:

Sahara AI 🔆

2,700,059 просмотров • 1 год назад

Something big is happening in robotics - and it’s hiding in plain sight. This post is not about dancing robots but in the data that powers them. Open robotics datasets have exploded this year, turning the field into a more scalable and collaborative ecosystem. In just two years, Hugging Face datasets grew from 11k to over 600k - and robotics is by far the fastest-growing segment. We went from 1k robotics datasets in 2024 to 27k in 2025! For comparison, text generation, the second-largest category, has only around 5k datasets in 2025. That gap is massive. Open datasets are important because robotics lives and dies by real-world robot data - video, actions, sensors, failures. By making this data easy to upload, reuse, and benchmark, researchers, startups, and large players are now releasing real-robot datasets that would have stayed locked inside labs just a few years ago. Major contributors include NVIDIA, LeRobot initiative, and a rapidly growing maker community. This surge is also enabled by cheaper video storage, better tooling, and an open-source AI culture now spilling into the physical world. And it really matters: open robotics data dramatically lowers entry barriers, accelerates learning-by-doing, and speeds up progress toward generalist and humanoid robots. Robotics won’t scale through hardware alone - but to a large extent through shared data. Viz below from AI World - link to the story and more viz/filters in comment.
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Something big is happening in robotics - and it’s hiding in plain sight. This post is not about dancing robots but in the data that powers them. Open robotics datasets have exploded this year, turning the field into a more scalable and collaborative ecosystem. In just two years, Hugging Face datasets grew from 11k to over 600k - and robotics is by far the fastest-growing segment. We went from 1k robotics datasets in 2024 to 27k in 2025! For comparison, text generation, the second-largest category, has only around 5k datasets in 2025. That gap is massive. Open datasets are important because robotics lives and dies by real-world robot data - video, actions, sensors, failures. By making this data easy to upload, reuse, and benchmark, researchers, startups, and large players are now releasing real-robot datasets that would have stayed locked inside labs just a few years ago. Major contributors include NVIDIA, LeRobot initiative, and a rapidly growing maker community. This surge is also enabled by cheaper video storage, better tooling, and an open-source AI culture now spilling into the physical world. And it really matters: open robotics data dramatically lowers entry barriers, accelerates learning-by-doing, and speeds up progress toward generalist and humanoid robots. Robotics won’t scale through hardware alone - but to a large extent through shared data. Viz below from AI World - link to the story and more viz/filters in comment.

Pierre-Alexandre Balland

185,895 просмотров • 6 месяцев назад

Some folks are saying Deep Seek censors certain topics (like Tiannamen Square) because it's a Chinese app. This is not true. Deep Seek is an open source LLM. You can download it, or host it outside China, and use it however you want. If you use its chat interface that's based in China, it will have to comply with the Chinese regulations. But outside China, you can do pretty much anything. For our app Research Kick, we are hosting it in the US. You can see, it answers my question about Tiannamen Square.
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Some folks are saying Deep Seek censors certain topics (like Tiannamen Square) because it's a Chinese app. This is not true. Deep Seek is an open source LLM. You can download it, or host it outside China, and use it however you want. If you use its chat interface that's based in China, it will have to comply with the Chinese regulations. But outside China, you can do pretty much anything. For our app Research Kick, we are hosting it in the US. You can see, it answers my question about Tiannamen Square.

Mushtaq Bilal, PhD

27,441 просмотров • 1 год назад

the 24gb vram tier is enough for most builder work in 2026. gemma 4 31b dense on my rog scar 18 just autonomously built a production hero section in one prompt, one html file and 5 minutes end to end. hardware: rog scar 18, rtx 5090 laptop 24gb vram. model: google gemma 4 31b dense at q4_k_m quant, using 22.8 of 24gb. engine: llama.cpp built for blackwell (sm_120). harness: hermes agent with native tool parsing. speed: 15 tok/s sustained, 94 watts, 50c. flags i used: ./build/bin/llama-server -m ~/models/gemma4-31b/google_gemma-4-31B-it-Q4_K_M.gguf -ngl 99 -c 131072 -np 1 -fa on --cache-type-k q4_0 --cache-type-v q4_0 --jinja --host 127.0.0.1 --port 8080 if you own 24gb vram in 2026, you have enough for most ui work, most agentic coding, most autonomous builds. no subscription, no one logging your prompts. a dense open model on consumer hardware shipping real software on your desk. this was the warmup. full page next on same hardware, then the octopus invaders final multifile autonomous challenge.
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the 24gb vram tier is enough for most builder work in 2026. gemma 4 31b dense on my rog scar 18 just autonomously built a production hero section in one prompt, one html file and 5 minutes end to end. hardware: rog scar 18, rtx 5090 laptop 24gb vram. model: google gemma 4 31b dense at q4_k_m quant, using 22.8 of 24gb. engine: llama.cpp built for blackwell (sm_120). harness: hermes agent with native tool parsing. speed: 15 tok/s sustained, 94 watts, 50c. flags i used: ./build/bin/llama-server -m ~/models/gemma4-31b/google_gemma-4-31B-it-Q4_K_M.gguf -ngl 99 -c 131072 -np 1 -fa on --cache-type-k q4_0 --cache-type-v q4_0 --jinja --host 127.0.0.1 --port 8080 if you own 24gb vram in 2026, you have enough for most ui work, most agentic coding, most autonomous builds. no subscription, no one logging your prompts. a dense open model on consumer hardware shipping real software on your desk. this was the warmup. full page next on same hardware, then the octopus invaders final multifile autonomous challenge.

Sudo su

19,576 просмотров • 2 месяцев назад

Someone posted the full code of a Chinese Polymarket bot on GitHub and deleted it within hours I saved it before it went down This is the bot behind gabagool22, $868,000 profit, 28,620 predictions, all green And now I understand exactly how it works The strategy is pure arbitrage, no prediction needed, no direction bets: → Buy YES when price drops below 48 cents → Buy NO when price drops below 48 cents → Combined cost under 97 cents, payout always $1.00 → Profit locked regardless of outcome 7.5% per pair. 96 markets per day on BTC alone. Running 24/7. The bot combines 4 open source repos into one hybrid engine: API client, thread-safe position tracker, gas optimizer, and risk manager with pre-trade validation It targets 15-minute BTC, ETH, and SOL markets simultaneously Start with $100, set your thresholds, run dry-mode first, then go live Profile: Full code: Copy:
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Someone posted the full code of a Chinese Polymarket bot on GitHub and deleted it within hours I saved it before it went down This is the bot behind gabagool22, $868,000 profit, 28,620 predictions, all green And now I understand exactly how it works The strategy is pure arbitrage, no prediction needed, no direction bets: → Buy YES when price drops below 48 cents → Buy NO when price drops below 48 cents → Combined cost under 97 cents, payout always $1.00 → Profit locked regardless of outcome 7.5% per pair. 96 markets per day on BTC alone. Running 24/7. The bot combines 4 open source repos into one hybrid engine: API client, thread-safe position tracker, gas optimizer, and risk manager with pre-trade validation It targets 15-minute BTC, ETH, and SOL markets simultaneously Start with $100, set your thresholds, run dry-mode first, then go live Profile: Full code: Copy:

Woody

26,223 просмотров • 3 месяцев назад