@Darpiniani
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https://nitter.cf/t.co/mtsgLYqwNY The future is robots Prev. Physical Intelligence @physical_int, @Google, @Meta, @Microsoft
Palo Alto, CA
Joined July 2008
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I just learned that the Chinese word for cow is not considered an onomatopoeia. It totally is though?
James retweeted
What the actual fuck. Opus 5.5 ultra created this masterpiece. 4 agents and an hour and a half later. Everything from scratch, no AI voice API used...
this is it...
Apparently it's humanoid soccer day. Third announcement of an AI playing soccer on a Unitree G1 today
Fast dribbling. Tight turns. Repeated direction changes. Human-like motion. ⚽️
We present a Unitree G1 system for sustained humanoid dribbling beyond simple straight-line ball pushing.
The robot continuously controls the ball while running through slalom courses and large direction changes, using natural whole-body motions.
Ball perception is fully onboard with LiDAR — no mocap, no external tracking.
The policy is trained in simulation with a human-motion prior and transfers zero-shot to hardware.
Safety tether stays slack during operation and provides no assistance.
Paper coming soon. Stay tuned!
One day we will look back on this time and marvel at how much compute was wasted doing inference on static models that don't learn in the process.
It's obvious why Amazon doesn't want Muse buying things. One, these orders are more likely to be canceled or returned. Two, humans don't see their ads or offers. Three, they don't want Meta to have Amazon purchase data. Same reason why they took product names out of their emails.
James retweeted
Oct 15-16, San Francisco
The first edition of the HUMANOID HUB Conference,
in collaboration with @hackersquadio
Registration link ⏬
🗹 skinny pill
☐ muscle pill
☐ energy pill
☐ smart pill
☐ a good night's sleep pill
☐ hair in the places you want and not other places pill
They released the "Under The Hood" feature so you can check if your account has "labels" applied that limit the reach of your posts. But mine doesn't so I guess I have nobody to blame but myself. Check yours here: nitter.cf/i/under_the_hood
James retweeted
Insane that you need to be an ‘accredited investor’ (>1m net worth or >200k salary for 2 years) to angel invest but any Tom, Dick, and Harry can go bet his life savings on polymarket or drunk at the casino with no questions asked. Sorry poor man, only the bad investments for you!
Maybe the reason I'm not as impressed with the predictive power of the EAs as other people is I also foresaw deep learning winning AI and being revolutionary, long before it happened. EAs are not uniquely good at foresight.
Briefly, on why I pay attention to the EA/rationalists:
Imagine you have an extremely nerdy friend who, in the mid-2000s, would not shut up about how Donald Trump was going to become president and reshape American politics. "Stop saying weird shit," you say. "He's a joke. He's a clown. The Apprentice isn't even good this season." But this guy won't stop. He's obsessive. Read McLuhan, he says. Read Postman, read Meyrowitz, read Ong, this is where everything is headed. God, he can be so incredibly annoying ... and then, ten years later, Trump becomes president and reshapes American politics.
This is the most relatable frame I can think of to explain my experience with EA/rationalist people in the AI space. I became friends with EA folks after my mom died and I found really profound meaning in donating to Against Malaria and GiveDirectly, which struck me as a way to honor a life by saving a life. Then, these peple started talking about AI. And talking, and talking. Constantly. They said AI would solve impossible math problems; that it would mimic PhD-level achievement in a variety of fields; that it would change parts of life like education in ways we couldn't imagine; that it would become the dominant sector in the economy; that it might teach itself to code itself and escape test environments; that it would, in a decade, be the only thing many people talked about in the news. My response then: Stop saying weird shit! You sound deranged. Go back to talking about malaria nets and direct cash aid to poor families.
And then, so much of what they said would happen actually happened. And, even crazier, they made it happen. Many of the ppl who contributed to, or were influenced by, all that EA/rationalist stuff ten years ago literally built the damn thing in the labs.
Like every group, the EA/rationalist world seems uniform to outsiders, but it has a ton of internal divisions. I still think some of their predictions are nuts. I don't think AI will kill us all. I don't foresee Dyson Spheres in the 2030s or millions of robots making millions of robots in the next few years. These are crazy predictions, and I hope most of them are wrong.
But when I see people shitting on the EA/Rationalist worldview, all I can think of is me, 10 years ago, thinking a lot of these folks were crazy for predicting that AI would by the mid-2020s be the center of the the news cycle, the engine of the economy, the hinge-point of geopolitics. That was an insane call. They got many of the details wrong. But they got the big picture right. They said: Pay attention. And they were right about that. The EA/Rationalists deserve skepticism, criticism, and doubt, like any other ideology. But I think it's wise to pay attention to the people who have been saying to pay attention.
Did anyone else get random emails from Anthropic about usage credits and refunds? I didn't use Claude today and certainly didn't buy or use any credits.
Interesting that they're not flying directly to orbit. My guess is they want to test engine relight before committing to orbit. If relight fails they'd rather have that happen in a suborbital trajectory, to avoid an uncontrolled reentry over land.
Starship is preparing to go to orbit. Flight 14 is targeting to launch as early as Tuesday, September 22, pending regulatory approval → spacex.com/launches/starship…
James retweeted
A video from a Pi robot deployed at Dandelion Chocolate, fully autonomous w/ no interventions. 🤖
Deploying robots has taught us surprising lessons about the gap between proof-of-concept (i.e. building one box) and real-world utility (productively building boxes for hours).
I expected that the hard part is building the box, since it’s the most dexterous, but that wasn't what we found. Counterintuitively, the hardest part was reliably stacking the boxes. Our original table-mounted robot had poor visibility of the stack without special separately-mounted cameras. Plus, stacking requires more generalization (each box is placed in a different location), and an imprecisely-placed box can lead the entire stack to collapse many boxes later.
We recently switched this deployment over to a mobile robot, and it's fun to watch the robot being completely self sufficient for multiple hours. 🙂 Data and feedback from real world use-cases like these are quite valuable for the π pre-trained model as we scale!