Zababa

This assumes production of food is the bottleneck rather than distribution. If distribution is actually the bottleneck, overstocked food is not a measure of excess in society.

>At their very core, Large Language Models' costs run contrary to basically every model of selling software.

>Consumers and enterprises alike have been trained to pay a monthly fee for a service, and while these services might have limits or strictures, basically nobody buying software expects to have a metered service, let alone one that's both metered and with hard to measure costs.

Has Ed Zitron not heard about the cloud? Unpredictable AWS bills?

Interesting how everyone's favorite language seems to be even better in LLM era, almost like passion, skill level and having LLMs matters more than the language.

Maybe this one will even be successful!

>That decomposition (perfect on templates, regressed on novelty) is the signature of “scaffold-then-internalize” training on genre-specific data, not a general gain in interactive abstract reasoning.

They're smuggling a claim that benchmarks like ARC-AGI measure "interactive abstract reasoning" here, which is what is claimed by the people that make these benchmarks, and also not proven.

>The lack of details to me means this was an intentional marketing ploy to try and demonstrate the power of their models to show their technology can compete with the likes of Anthropic and DeepMind.

DeepMind hasn't been on the frontier for a while, their current best model is behind Anthropic, OpenAI, Moonshot (Kimi k3), xAI (Grok 4.5), Z.AI (GLM 5.2), and even Meta (muse spark). Gemini 3.6 is behind GLM 5.2, released a month earlier, open weights and cheaper.

You can paint the OpenAI story as a way to try to appear as dangerous as Anthropic with all the Mythos stuff.

Train station: :D :D :D <3

Train station, Japan: :D :D :D <3

Transit infrastructure is really cool

The mix of humanizing the LLM, calling it "clanker" and being very aggressive towards it is really weird. I don't think it's a good habit to take, it feels like it could bleed into how you interact with people. Many interactions are through text interfaces these days.

There's also an alternative which is that token prices are already high, downtimes do exist (semi frequent on Claude) or are managed by serving degraded versions/quants (speculation that has never really be proven afaik) or reducing thinking time ("juice" values from open AI), and that free tiers are not used much at all or are a loss leader.

>Resets of the weekly quota for all users must be ludicrously expensive for these companies

Why can't people see the alternative hypothesis, inference has huuuuuge margins?

DeepSeek V3.2 was tried without reasoning and it got 57% on ARC AGI 1. It's a 7 month model, so I'm pretty confident that base LLMs would be able to solve ARC AGI 1 without reasoning/CoT.