2,957 karma · joined September 15, 2020
Haiku/Sonnet 4.5 on GitHub Copilot is not a valid comparison whatsoever.
You need to benchmark against Claude Code running Opus. I mean, being revolutionary is a big claim to fame.
Why are you posting this on your company's site, littered with ads for the company's product?
Post it on a personal blog, or just say that these indeed are the company's beliefs.
DeepMind has already has had real impact on science with the same foundational architecture as LLMs, for protein folding. They won a Nobel prize for it.
Has this been just pure lack of funding and infra?
Not really distillation, just synthetic training data.
The cheap tokens are the product.
The big thing there is, that he already was a professional musician and completely inside a creative scene before leaving for the cabin. (DeYarmond Edison was the band he was in before Bon Iver.)
But yes, things were going way sideways for him, liver issues with mono, so he went to process whatever was going on and had been going on in complete isolation. (Although for the next album, he actually set up a whole "creative commune", a new band around Bon Iver instead of it being just himself, and so on. And I think you can hear the colors he wanted back in the music from it directly.)
A lot of examples of artists going into bouts of isolation, but almost always coming into it from an intense experience. So, the two don't have to be day to day intertwined, although for Techno specifically it's usually the case.
Paired with an obsessive work ethic in the studio.
If it's only obsession in the studio, things come out dry, uninspired. If there's no surge of energy running through your bones when making the music, why would anyone else feel anything? Mixing and the music sounding "professional" is completely secondary. Even detrimental a lot of the time, to be honest.
Applies to many other things than music as well. I don't any great technology comes out and about without that loop, either.
Maybe it's a tune of the base model that works especially well with the subagent loop?
[0]: https://openai.com/index/openai-broadcom-jalapeno-inference-...
My view is that there are people capable of vetting LLM generated code, and people who are not capable of it, based on their previous track record of vetting non-LLM generated code and the quality of their own non-LLM generated code.
For example: I would trust the capability of John Carmack to vet an LLM generated bug fix, to his own game engine. Even if it was LLM generated by him, and vetted by him.
This doesn't match at all with what the author described in the article.
> Anyone trying to say "but my slop isn't slop, I vetted it" clearly is not in possession of the necessary critical thinking skills to differentiate between slop and non-slop.
This is called a Kafkatrap. It works in any direction, in any situation, making the disagreement moot. Also not considered good faith rhetoric.
> Limited data retention and review as part of our safety work. Prompts submitted to, and outputs generated by, Mythos-class models are retained for 30 days for trust and safety purposes, on every platform where these models are offered.
> Change applies to organizations that have set up workspaces with zero data retention (ZDR) in Claude Console, use Claude Code with ZDR in Claude Enterprise, or access Claude through AWS Bedrock, Google Cloud Agent Platform, or Microsoft Foundry with ZDR.
https://support.claude.com/en/articles/15425996-data-retenti...
What computers "are" has been ebbing and flowing decade after decade. They've been repurposed to something that they initially weren't. It was originally niche, and not at all the norm.
Then, there was a brief period when counter culture was pop culture. That was reflected in everything in the 90's, from music to computers.
> Pages is a lot of app. TextEdit tops out at bold and italic. Others are too single-minded.
> So I built my own. It does what I need, nothing I don’t, and it never asks me to log in.
https://world.org/blog/foundational-topics/thesimpleplan
> 1. Build a private proof of human
> 2. Launch and bootstrap the network through token ownership
> 3. Reach critical scale and initial utility
> 4. Scale further through utility and decentralize
> 5. Reach global scale and help ensure AGI benefits every human