peri-cl

> "How many companies are building datacenter commons and sharing with other companies to optimize resource usage?"

They're all sharing with each other. Anthropic's S-1, for instance, shows $100 billion+ commitments each to renting datacenter space from AWS, xAI, and Google (two of whom compete with Anthropic on AI). None of theme are idly sitting on unused depreciating hardware for no reason.

I've never heard anyone accuse FAANG's of not trying hard enough to optimize their own resource usage.

Introducing: HNN (Hacker non-news): a list of web domains *not* currently under apocalyptic AI attack. Shorter and more parsimonious.

- Tell HNN: pets.com was *not* owned today

- Tell HNN: about:blank was safe, too

- Show HNN: my new gopher protocol project—no currently known CVE 10's

Sure, but reallocating those to their AI competitors would offset those competitors' demand for AI GPU's and HBM RAM. Which frees up the TSMC, Samsung, Micron fabs to shift back to consumer production. Displaced demand.

Sure. I'm still curious about consumer alternatives with small, cheap LLM models controlling things.

These problems don't really need extremely powerful hardware, and extremely large and expensive frontier AI agent swarms. I'm certain a good engineer could get away with a lot less than the OP, working with care under hard budget constraints (i.e., no 50x Sol); optimizing things thoughtfully and deliberately from first principles.

I get a sense, reading OP, reading in between the lines, that: one, those agents really, just, suck at playing Minecraft. And, two: that's not a limitation of "Sol 6.1 is too weak an AI" (hah!); or some hard CS problem of scaling and coordinating agent swarms (though that is a thing); but it's that their harness and tooling setup is bad. You can see all over the logs agents struggling with absolute basics of how to handle their tool calls[0], and how to interact with their world; fundamental basics that could easily be fixed, but weren't.

I think if you're passionate about something related to this, and you want to make a real product (not a one-off slop demo) and are willing to put in your serious-engineer effort into it, you could do way better than this demo, on way smaller hardware. (HN has lost sight of some fundamentals I can't now articulate in words. The AI burnout is clouding our eyes).

[0] e.g.: [B_Wren → B_Theo] "Failure was automatic tool selection with enchanted sword held" [B_Esme · private reasoning] "I could buy shears for 20, but that's pointless since breaking is bugged anyway"

or: [R_Cleo/memory.md] "Died chasing B_Theo off island edge. Use max_distance ~6 when attacking on base... Died AGAIN: attack chase pulled me onto south wool bridge (-40,-10), fell. Use chase=false or max_distance 3."

> "they deserve bankruptcy"

Chapter 7, please! I would like them to *liquidate* Smaug's GPU hoard; and I would like them to do that all at once, in a swift and efficient fire sale.

Wonder if you could glue together deep networks such that there's a big reasoning LLM model, and high-speed small network of a different type, and they share a subset of their activations. High bandwidth vector communication. You train them together.

edit to add: Seems this is a well-known idea in ML / robotics already.