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Anthropic said no to the Pentagon.
Now Sam Altman is backing them:
"For all the differences I have with Anthropic, I mostly trust them as a company and I think they really do care about safety."
OpenAI and Anthropic both drawing the same line.
This is a big deal.
Humanoid robots are increasingly blending into daily life 🤖🍱
Shenzhen’s DEXFORCE Robotics DexForce W1 Pro (Gen2) wheeled humanoid is now running autonomously in a community convenience store: it crafts nutritious, weight-loss-friendly meals based on customer preferences, expertly heats them in the microwave, and delivers right to you.
Soon, we’ll treat these AI humanoids as everyday helpers.
Great Honor to Welcome German Chancellor Merz 🥳
It was a great honor to welcome German Chancellor and his delegation to visit Unitree Robotics!
We sincerely appreciate the enthusiasm from German entrepreneurs for Unitree robots!
We look forward to working with more outstanding companies around the world to achieve mutual success,
and to jointly advance intelligent robotics technology for the benefit of all humanity.
Unitree just unveiled the As2, a compact robotic companion that packs surprisingly serious industrial-grade specs. 🤖💪
The new model features a maximum torque of 90N·m and can run for over 4 hours straight on a single charge while unloaded.
It handles a 15 kg (33 lbs) payload with a range exceeding 13 km (8.1 miles), designed to tackle real-world tasks.
Built for the elements, the As2 is IP54 rainproof and fully open for secondary development to empower specialized industry apps.
Source: Unitree
#Robot #Humanoid #Robotics #AI #EmbodiedAI #PhysicalAI #Unitree #Automation
What can half of GPT-1 do? We trained a 42M transformer called SONIC to control the body of a humanoid robot. It takes a remarkable amount of subconscious processing for us humans to squat, turn, crawl, sprint. SONIC captures this "System 1" - the fast, reactive whole-body intelligence - in a single model that translates any motion command into stable, natural motor signals. And it's all open-source!!
The key insight: motion tracking is the one, true scalable task for whole body control. Instead of hand-engineering rewards for every new skill, we use dense, frame-by-frame supervision from human mocap data. The data itself encodes the reward function: "configure your limbs in any human-like position while maintaining balance".
We scaled humanoid motion RL to an unprecedented scale: 100M+ mocap frames and 500,000+ parallel robots across 128 GPUs. NVIDIA Isaac Lab allows us to accelerate physics at 10,000x faster tick, giving robots many years of virtual experience in only hours of wall clock time. After 3 days of training, the neural net transfers zero-shot to the real G1 robot with no finetuning. 100% success rate across 50 diverse real-world motion sequences.
One SONIC policy supports all of the following:
- VR whole-body teleoperation
- Human video. Just point a webcam to live stream motions.
- Text prompts. "Walk sideways", "dance like a monkey", "kick your left foot", etc.
- Music audio. The robot dances to the beat, adapting to tempo and rhythm.
- VLA foundation models. We plugged in GR00T N1.5 and achieved 95% success on mobile tasks.
We open-source the code and model checkpoints!! Deep dive in thread:
🇨🇳 China actually started putting humanoid robot attendants on their high-speed trains to help out during the Spring Festival travel rush
They are basically testing how these bots handle the chaos.
Hey @Tesla_Optimus your competition is growing.
Damn impressively too.
Yes, I know that they aren't generalized. Or safe enough to bring into our homes. But wow. What a show. Hey @cixliv I could see multiple robots fighting in the cage in San Francisco next. No?
Japan Pavilion connects Japan’s robotics and AI leaders with Shenzhen’s world-leading robotics ecosystem.
It’s a focused delegation to visit top companies, real factories, and large-scale deployments — building real cross-border collaboration.
AI-generated fakes are flooding X, making it nearly impossible to tell real engineering from digital junk.
This video originally had an AI-generated disclaimer, but some are posting it without any mention of that, even vaguely claiming it's "totally in charge."
amazing, this is massive
New 100x faster 3D printing method (than previous volumetric methods).
This will change manufacturing and the world.
"Tsinghua University-based team say they can 3D print complex millimeter-scale objects within only 0.6s, in an academic paper published by Nature"
AI-generated trash is spiraling out of control, with people churning out fake "robot soldiers" and superhuman humanoids just to farm clicks. 🤖🚫
It’s honestly shady how these creators prioritize viral engagement over actual tech reality.
Not a preplanned motion sequence.
A robot deciding mid-jump what to do next.
[📍 paper + demo]
Researchers just showed a humanoid doing real parkour using only onboard perception. No motion script, no fixed obstacle layout.
The system is called Perceptive Humanoid Parkour (PHP).
Instead of memorizing a path, the robot reads depth from its cameras and continuously chooses actions. Step, vault, climb, or roll depending on what geometry appears in front of it.
To make that possible, they combine three ideas:
First, they stitch together human motion clips into long movement references so the robot learns fluid transitions instead of isolated tricks.
Second, they train tracking policies with reinforcement learning so contacts land at the right time and the robot keeps balance during dynamic moves.
Finally, everything is distilled into one perception policy that runs directly from depth input to action selection.
The result on a Unitree G1:
about 3 m/s vaults
wall climbs up to 1.25 m
nearly one minute continuous obstacle traversal
adapting when obstacles move
What matters is not the tricks.
It is the shift in capability.
Earlier humanoids executed motions.
This one navigates situations.
Once robots react to geometry instead of replaying trajectories, environments stop needing to be predictable. Warehouses, homes, and outdoors suddenly become the same problem.
Thanks for sharing, @zhenkirito123!
Paper + demo:
https://t.co/fWau86kmN6
https://t.co/Txh8BVx50E
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