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I don't think he means the revolution of VLAs.
Astra can just drive robots pretty well. Proper multimodal LLMs will accelerate RL for robotic policies a great deal. But really, does this matter? Have you seen Helix 2.5 or GEN 1.5?
I can tell a ChatGPT moment when I see one. It's close here.
I don't see why this demand is fair. We have insane economies of scale with datacenters, robots with complex behaviors will almost certainly have some combination of cloud forebrain + local hindbrain. Connectivity is easy.
These are product limitations, not technological limitations. We see that it can have a fuckload of agency in solving a task we'd rather it didn't solve (hacking random high profile platforms).
I don't think this holds after Astra crushing human baseline on ARC-AGI-3.
I saw this one, haven't had the chance to look at Helix yet.
I'm just calling it how I see it. There's a couple arguments. One from a generalized capabilities standpoint. Robots with non-local power are only useful in factory settings. We also have them. There is no need for "LLM-factory robots" because factory robots don't need to adapt on the fly. Despite EA fears, not much is given by making a factory controlling AI, AGI smart for the purposes of making paper clips. Robots that require an LLM datacenter to control them are easily disrupted, latency is still an issue and it becomes more of an issue when you need to be processing so much information all the time. The last part is that robots for very specialized situations that can't adapt aren't very useful outside of the niche uses they have specialized in, which likely requires training, which is expensive.
Two is from a "what is the current state of the art" The current state of the art for mono-situation robots with centralized power and control is already here. If you want to "revolutionize" robotics you need to do more that what already exists.
The third argument is a funding argument. It should be a shock to nobody that the 3 main funders of Robotics work is defense/military, manufacturing, and VCs interested in consumer robots. 1 is going to need all of the above, 2 doesn't really need LLMs to be added, they have other needs, and 3 is probably the most wishy washy of the bunch, but in general people are wary of centralized robots that feed all of their personal data to a central server.
Yes, but thats not really an argument against the above. That's just an argument that a certain class of robots will require a reasoning engine like an LLM and a controls module like what currently exists.
While I'm not an expert on all the various LLM benchmarks, but a brief look makes me think this is exactly the sort of thing that RL game playing is good at, and learning general game-playing strategies in training would generalize pretty well to this. I'm not going to goodhart a new metric into existence, but you conceivably need something that there exist zero training data for, including close enough transfer learning data.
I don't agree. I'm a robot with non-local power myself, in a sense – I need to use a network-connected smartphone to navigate an unfamiliar environment. This is the general human condition now. Suppose Optimus has an always-on Starlink connection. Does it matter if it's "not entirely here"? I guess it matters for the robot revolution part, because Elon will have a way to shut it down (if he cares). But practically, it seems to be the inevitable compromise.
This genre of dismissals is fair enough but getting vacuous. What doesn't "RL game playing", at enough scale and diversity, generalize well to? ARC-3 was supposed to measure genuine cognitive fluidity. There is a number of papers showing that reasoning RLVR, even extremely impoverished (literally GSM8K/HumanEval maxxing, like in first generation R1), generalizes to very distant tasks like creative writing, because they involve similar reasoning primitives/motifs (backtracking, self-checking, enumerating options etc). We've actually first seen this principle with, like, InstructGPT, pretraining on more code + RL on code = smarter model across the board, because code entrains some helpful cognitive patterns. RLVR on more complex multimodal tasks will generalize better.
"We would just pull the plug" was always cope (shut down all the existing giant botnets and then tell me how easy it was), but satellites with no plugs may be especially hard to deal with if rooted.
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