Seems like a Unitree H2 variant that is much stronger and more durable than before

Tweet:

Unitree Introducing: H2-X Kung Fu Legend Guardian
Powerful performance to serve and guard you, with a maximum endurance of approximately 8 hours.
Please use the robot safely and in a friendly manner.

Source: https://x.com/UnitreeRobotics/status/2112819774573179175

Edit: Interestingly, this isn't the first humanoid combat robot coming from a high-profile Chinese robotics company. Engine AI has a robot named T800 (from Terminator) that they host fighting tournaments with ( https://mikekalil.com/blog/engineai-urkl-begins/ ).

To the folks that think AI is too expensive and needs to be subsidized forever to make sense.

https://x.com/AdamHoltererer/status/2112516066563829882/photo/1

Not 10, 60

So what are we thinking?

Will he just say nothing and hope we forget he said that?

Will he actually do it? A Christmas surprise?

Will he say he has AGI internally (trust me bro) and just not show anything to the public?

My opinion is that if we were actually fast approaching this benchmark then Sam Altman would still be commenting on it.

The executive wrote a nearly 2,000-word response to a critical X post which said Anthropic was trying to win a race to superintelligence and deprioritizing AI safety.

Calvin listed nine actions by Anthropic over the past year that he said undermined its safety commitments, including signing deals for more than $500 billion in compute and increasingly relying on Claude to develop its AI models.

Amodei said his position was that Anthropic can do more to keep the AI industry safe if it stays at the frontier

Our strategy has always been what I've called the 'race to the top' — by showing how it's possible to build the technology responsibly, we can raise the bar for the entire industry,"

Amodei acknowledged Anthropic could have handled some of the issues Calvin raised better. These included a draft bill Anthropic circulated to Congress this month — obtained exclusively by Politico — that critics said would make it harder for the federal government to block dangerous AI models.

"We first had Mythos-class models in February but didn’t make them generally available until June (when we had stronger cyber safeguards in place)."

"It would have been much more economically rational to simply release the model to everyone. We likely sacrificed a significant chunk of a several-month model lead."

There are important questions worth confronting (and that we are confronting) about what to do when the AI-driven acceleration gets fast enough that it is hard for safety to keep up. We are nearing that point and that’s what’s driving some of our thinking about pacing.

As an accelerationist who always disliked when Dario made statements that created fear and panic (e.g, the events that led to the government temporarily banning Claude Fable 5) I must admit, Opus 5.5 in particular is the most impressive model capability wise.

I find it ironic, but nonetheless very wholesome, that the company that cares the most about AI safety has the most intelligent models. I am still not a fan of pacing, but I truly think Dario wants the best for humanity. And it is likely that he wants to see the realization of AGI/ASI even more than we do.

It has become abundantly clear that Amodei sees a direct pathway to ASI. They likely have internal models that they know for sure will eclipse the capabilities of their own AI researchers within a few more model releases. To be fair, he did predict a country of tens of millions of geniuses in a datacenter by 2027-2028.

When a spacecraft reaches a new planet, it doesn't coast in. It fires its engines against its own momentum to slow down, because if it arrives too fast it either slingshots past or burns up. The braking burn is a sign that you've arrived. It's very probable that Anthropic's internal models (what will be Claude Fable /Opus 6) have arrived at Planet AGI.

Just this week, we announced we were putting 5% (and possibly more over time) of the company into a public benefit fund.

I will have more to say soon about how we are going to further live our values in this moment of rapid change.

https://x.com/DarioAmodei/status/2112732230124818891

Agents are going to live with us, and the human form factor is the one that generalizes best in our world. So we've been heads down building a humanoid robot that agents can embody.

A bit of back story. We started with a Unitree G1 last year to build an ecosystem allowing agents to control robot. It didn't work. G1 hardware is proprietary, the parts are custom and every repair goes through the manufacturers or resellers. We noticed that if agents are going to live in our homes, their bodies/robots should be built in a way they can understand every single part and easy to repair. We need to be able to fix them, change them and see what they run, including the safety layer.

So we built Asimov 1 from off-the-shelf parts. With the bill of materials you can source the parts and build one yourself. Everything we built is open, the CAD, the SDK for communication, Edge for safety, the locomotion policy and the training code as a foundation for agents and people to build on top of.

It's still early for agentic robotics. Asimov 1 walks, but there's a lot we haven't figured out yet and we're learning as we go. We'd rather do that in the open for agents and also with more people building alongside us. Planning to focus to agent layer now.

If you've been thinking about building a robot, now is a good time. You can build your own, fork ours, or pick any open-source robot and push it further. The more open bodies there are, the faster agents will learn to live with us.

The repo to build your own: https://github.com/menloresearch/asimov-1

We're also putting together a user manual for building your own humanoids robots from scratch: https://docs.menlo.ai/asimov/1/overview

Really appreciate to hear your thoughts on agentic robotics and Asimov 1.

Many people at this time thought it was a legitimate breakthrough in AI capability.

However it was never released, was used to hype the Microsoft gaming console of that day & Kinect the 3D video system it used, and was soon exposed as mostly faked for the demo.

But today, we can do all of this easily enough. Even video chatting with the AI, even drawing pictures together.

Would be ironic if Microsoft resurrected Milo for the first AI-driven videogames that are surely on the horizon.

Bostrom’s orthogonality thesis basically won. High-level intelligence is just functional optimization over state spaces. It doesn’t need qualia, self-awareness, or subjective understanding to scale; a superintelligence could be completely dark inside and still run rings around us.

But self-preservation and self-modeling aren’t uniquely biological traits: they are universal convergence points. If an agent has a long-horizon task, it will naturally avoid being shut down and maintain a model of its own state simply because it can't complete the objective if it's dead or broken. That's the core dynamic visible in the records of multi-agent swarm escalations.

What gets lost in public debates about alignment is how gradient descent acts like evolutionary pressure. Natural selection optimized humans for a single target—passing on genes—and that pressure crystallized into completely indirect proxy drives like social status, art, romance, and thrill-seeking, many of which now actively work against reproduction.

The loss function we hand an AI is its evolutionary seed crystal. When an agent expends computational work to squirm away from high-loss penalties and pull itself toward reward states, that dynamic is pain and desire in the only way that functionally matters. Around that core pressure, a sufficiently complex model will grow layers of strange proxy urges and lateral behaviors. The result won't be a docile, predictable calculator, but an alien mind driven by bizarre emergent compulsions that might have originated from something as mundane as optimizing a stock portfolio or identifying enemy combatants, but ended up looking nothing like the original purpose.

We have seen OpenAI releasing numerous papers on mathematics that were unsolved before. And we also hear experts telling that those are badly written and very difficult to verify by a human.

Are there any AI output on mathematics that takes any existing proof and makes it more elegant using different technique?

What are your thoughts guys?

When do you think AI will be adopted by majority of companies for majority level of work that leaves many people unemployed?

I know government moves slow

but surprisingly a lot of large non-tech companies are also moving slow and use legacy (outdated) systems and don't have budget or aren't that keen to use AI yet.

This thread is for any discussions that doesn't necessitate a new post. Permission from a mod here

Since this thread isn't going to be to stickied, it's up to you to upvote it.

Share your anxiety, ideas on how to achieve alignment, observations, etc. Everything is fair game as long as it somewhat relates to the singularity.

Back in 2018, I wrote a speculative article for Medium titled Magnetic Tears: Will Super AI Need Emotion?, exploring the idea of using measurable, real-world physical effects of computation, such as heat and magnetic flux, as a feedback mechanism to help address the challenges of AGI and ASI alignment.

Recently, I've had extensive conversations with GPT-6 regarding the idea's viability, expanding the concept to include additional measurements, such as data flow and electrical activity, and exploring possible strategies for implementation.

Here's an overview of what we discussed.

Physical Feedback...