Discovery Loop

When they say experiments, do they mean using physics simulators?

"The speed of light in a vacuum used to be about 35 mph. Then Jeff Dean spent a weekend optimizing physics."

Computation is not the hard part of discovery.

Jesus, he left Google to do what everyone else is already trying to do? He must be so insulated he doesn’t realize what the real world is actually up to. I mean, organizations started on this exact same mission three or four years ago. Or longer. I suppose it’s better to wake up later than never.

So Ralph Wiggum in a suit?

I am available for hire.

I smell vapor.

nice

Another way to see this is: a bunch of renowned google engineers realized they can grab some of the VC pie for themselves

https://www.geekwire.com/2026/the-startup-idea-that-convince...

Not through conscience.

The AI designed italics on thin font is hard to not see as slop.

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I wish them well, but this firm will likely fail miserably. The reason is that the value is in having access to real world hardware platforms that AI can control, not in the harness that controls them. There exist plenty of harnesses already. These people couldn't even get Google to build a top LLM. Before you dismiss and downvote, I dare you to counter it.

Is this a joke? Site is not loading for me.

> Imagine a future where a handful of people can conduct scientific research and engineering tasks much more rapidly, and with higher quality, than massive teams of scientists and engineers do today.

Imagine a future where only the anointed few elite minds can participate in science and engineering. Btw we’re hiring.

Great message!

As LLM coding agents plateau— at least for the average engineer without tens of thousands of dollars or swarms of agents to run —I’d say that, from here on it’s going to be about ASICs, specialized LoRA/or-equivalent models, or a Ruby on Rails for LLM context engineering and orchestration, which LangChain and others seems well position, including Google as they own the entire stack. LLM free lunch has been over for a while, perhaps since the ReAct loop, and has been official since Ilya mentioned it at NeurIPS.

I feel the most exciting development these days is self-evolving agents. Especially if you have a way to verify their outputs with a formal system, or with a system developed since the 60s by armies of PhDs.

DeepMinds Gnome is a good example, where they use DFT to verify outputs. Approximating NP-problems is always fun for those who dare.

I am also building in this space. Its a mix between HPC, AI, and hard science. Pretty fun compared to waking everyday to LLM news that seem more like marketing stunts.