trenchgun

>The MWI has no explanation for how this other infinity of possible states disappears into just two states. You still wind up with the collapse of the wave function--involving a lot of hand-waving or appealing to some nebulous property of consciousness.

The real issue here is the preferred basis problem, not an infinity of worlds: a single state vector can be decomposed many ways, and the bare math doesn't say which decomposition counts as "the branches." Decoherence picks it out: once the cat is entangled with its environment, the alive/dead decomposition becomes effectively unique and stable, through ordinary unitary dynamics. No collapse, no consciousness (that's von Neumann–Wigner, not Everett). MWI does have an open problem, but it's a different one: the Born rule, i.e. why |c|^2 should count as probability when every branch is real. Also, the normalization is |c1|^2 + |c2|^2 = 1.

Scummy benchmaxxed model https://x.com/dummerspast39/status/2112273501390549081?s=46

Lost completely trust to MiniMax after the latest benchmaxxing evidence.

Open source models are objectively dangerous. You are delusional if you think otherwise. I am not really arguing for banning them (seems impossible to enforce), but also denialism of the real dangers involved is pretty naive.

This is a theoretical computer science paper. This is what they are like! Post sucks.

Do not bet against airplanes.

You said: >I'd say if you know and like Rust, then Gleam should be easy to pick up but otherwise I'd try Elixir.

This is way too strong and narrow statement. Gleam is statically typed garbage collected language, closer to OCaml than Rust. Elixir if you like dynamically typed instead.

If you read the paper, they had a solution for this.

They hacked the JFrog artifactory package they were all using, thats why it was a natual communication channel.

The public frontier is not the frontier. Actual frontier models are too expensive to serve to public, and also risk distillation by competitors.

Do you think Chinese lab researchers have not read Yudkovsky, or are not AGI pilled? Hate to break it to you, but they are racing to AGI with pretty same reasoning as western labs.

Just recently DeepSeek researcher in his post was saying that they need to get to AGI first, because if Anthropic gets there first then that brings a dystopia. Exact same argument was used to justify launching OpenAI (against DeepMind), and Anthropic (against OpenAI)

Yep. As is "can't know".

You do not even need a subscription. Even ChatGPT free account has some quota for Codex/Work use.

Why delete comments! Constrained grammar! Make invalid state unrepresentable.

Interesting, so they shipped slop? Succumbed to their own AI psychosis?

I did write small programs myself, but mostly with Claude Code. It was very pleasant to work in it with Claude Code. Implemented a shell and 40 of coreutils. Did not really get very far with proving properties of them, but had working programs. Reading Lean4 is pretty nice. Nicer to read than OCaml, almost as nice as Haskell.

Lean4 is a general purpose programming language.

CMD+F "reward hacking" -> 0 hits.

Fail.

They are already proven false through Jacobian conjecture having been proved false.

Yes, assuming the stuff it depends on is already formalized.

This is a product I have wanted to exist for quite a while, and tried to create myself, but lack the skill.

Thank you for building this!

Then it is really not about language design... I would rather recommend https://www.plai.org/

I think mass deportation of people with wrong skin color goes beyond "stricter view on immigration"

>large scale remigration https://en.wikipedia.org/wiki/Remigration

>But when people think of decentralized training, they don’t first think of gigantic datacenters, owned by the same company, training models across large distances. Instead, they imagine thousands of small datacenters, or individual consumers, pooling their spare compute over the internet to orchestrate a training run larger than any single actor could manage alone. Many companies are pursuing this vision: Pluralis Research, Prime Intellect and Nous Research have already successfully decentrally trained models at scale. But in practice, training decentrally over the internet has lagged far behind more centralized training. Even their largest models (Pluralis’ 8B Protocol Model, Prime Intellect’s INTELLECT-1, and Nous’ Consilience 40B) have been trained with 1,000x less compute than today’s frontier models (such as xAI’s Grok 4). https://epoch.ai/gradient-updates/how-far-can-decentralized-...

Yes, and then you need to have the datacenter. Do you get a permit? How long does it take to build it?

This pattern reads heavily LLM in style, but also... that is spot on.

So... you did not read it, or did not understand what you read.

Where?

But everything else still works fine, right?