Where the AI market is talking

K2 Horizon: A connected fleet of six open models

But that would be impossible due copyrights laws. If the law would apply Anthropic and OpenAI executives would be in jail

K2 Horizon: A connected fleet of six open models

But that would be impossible due copyrights laws. If the law would apply Anthropic and OpenAI executives would be in jail

GPT-6 Astra

Cool. Being sole proprietor of AGI 15 years ago should result in monuments and religions devoted to you today. Cancer should be cured, and we should be a post-quantum interstellar fusion-powered civilization. I wish the AGI crowd would finally shut up now that it's clear no one is even trying for AGI (OpenAI revised that to "$100B in profit") What we're getting is incredible, where we're headed is incredible, but some people have such a fetish for futuretelling they can't just shut up and enjoy the ride.

OpenAI begins rolling out GPT-6 Astra

Why would you put it on ultra high thinking and let it run all night to do a simple task it makes no sense the error is the users. And of course OpenAI is gonna let you burn as many tokens as you want doing this.

GPT-6 Astra

ARC leaderboard has results from semi-private data for frontier models, they have another competition for private data. It is described in their methodology: https://arcprize.org/policy It makes sense, since once OpenAI API receive task, it is not private anymore but leaked to OpenAI.

GPT-6 Astra

Well signing a contract is more about bearing responsibility, even if you granted LLMs "personhood" they cant' meaningfully bear responsibility. So unless OpenAI is ok with having their C-suite face every consequence for what their agents do, including jail time, fines etc, then it doesn't matter.

GPT-6 Astra

“there is no moat”, even though openai and anthropic both have paused development and are working off internal models that are like yet another revision ahead of what has even been released. and open source models only ever catch up to what is already publicly released because all they do is distill openai and antropic models. but yeah: “no moat”.

Prime Gaps at Most 186

blegh, both the code comments and readme reek of verbose claude puke. > The registered Lean build passed without errors or warnings. thanks. i like it when my proofs do not error. Edit: just saw this was published under openai, yikes.

GPT-6 Astra

The official ARC-AGI 3 score—-without OpenAI’s custom harness—-can be found here: https://arcprize.org/leaderboard . Astra scores 62.7% at max reasoning for the low-low price of 26,000 dollars.

GPT 6 is way behind Anthropic on Artificial Analysis

OpenAI begins rolling out GPT-6 Astra

The defaults are bad, but these models are highly steerable. For simple scripts adding to the prompt something like "do not over engineer, do not gold plate, no CLI args, keep it simple" does wonders. For whole projects, I have a 3 page anti-bloat.md which describes what not to do, stuff like: > Minimize lines of code, number of files, classes, protocols, factories, wrappers, and dependency-injection objects. Prefer a coherent implementation that is easy to trace end-to-end. > Use concrete dependencies directly. Do not create protocols, abstract base classes, or adapters unless there are already two real implementations. > Use direct state fields or a small state dataclass; do not introduce generic lifecycle, state-machine, observer, snapshot, or event framework classes. The funn…

GPT-6 Astra

Yes, the very explicit plan of both OpenAI and Anthropic is to use the not particularly efficient LLMs to automate their own AI engineering. That seems to be going well - on coding front and model tuning front so far. They have more planned. And then use those to find fundamentally better new architectures for AI - that perhaps are as efficient as the human brain. It might not work, but I didn't think it'd solve maths problems... So it might work. And if it happens, they'd use the data centres to run millions of instances of it. It's scary, TBH.

GPT-6 Astra

From what I've seen it only made people mad, not hyped, so the person that thought it was a good idea miscalculated a bit. Now waiting for Anthropic's post about their usage promo or something similar to redirect people to them.

GPT-6 Astra

The benchmarks do looks good (I mean: they literally spank the latest Anthropic benchmarks of two days ago in every single benchmark) but the promotional vid is so cheesy. They decided to use the iconic Herman Miller Eames chair if I'm not mistaken: https://youtu.be/s5zyhGMMPKs And that's basically 50% of the vid looking "classy". I don't know if it's farcical but at this point --maybe I'm jaded-- I'm expecting more than a kid rocketship I can print on my Bambu Lab A1. Now I'd say the promotional vid is actually good. But it's marketing: so it's a good vid, but cheesy good. Doesn't mean GPT-6 Astra is good or bad: looks solid from the numbers.

Which tools do Claude, Codex and Cursor choose? We measured 17k runs to find out

Hey! Disclaimer: I am a Co-Founder of Armature (YC P26) which sells growth services to dev tools. This study is part of our broader work on how to influence coding agents choices and get products picked. To understand how agents pick tools we measured close to 17k sessions on an environment where agents run exactly like in the real world, on various repositories, talking to different personas (vibe-coder, junior or senior engineers) in different sizes of companies. All the results are now public and we'd love to know what findings surprise you the most, here are a few we found interesting: - Claude Code rarely searches the web while Codex almost always does it and Cursor sits in the middle. - Coding agents disagree more frequently than they agree. - Some players (LangChain, Supabase, Netl…

GPT-6 Astra

Overall I have to say it feels like a very incredible comeback from OpenAI, after focusing on Sora and stuff like that and losing so much ground to Anthropic in enterprise revenue. I hop models at will, and have done 90% of my work on OpenAI models since sol came out.

Dutch central bank moves 86 tonnes of gold from US citing 'geopolitical unrest'

10 characters had to be removed to fit under the title length limit. “and Canada” was the only real option that maintained coherence. There were no editorial motives behind that selection.

Any Human Ever – One life, drawn at random from all who have ever lived

I don't follow what your point is here. If you're not aware, Anthropic pirated many books via libgen and similar tools for use during the training process[1]. Maybe you are not aware of this, or do not consider it theft? [1] https://www.reuters.com/world/us-judge-approves-anthropics-1...

US gov sides with OpenAI on issue of training LLMs on copyrighted material

My position is it's totally coherent to say that "training" is analogous to "reading" and inference is not analogous to "redistributing rips" and that it's a reasonable position for fair use law to operate that way. I think this benefits society.

Nvidia to acquire Hugging Face

This is the most compelling case I've come across: https://www.decodingdiscontinuity.com/p/nvidia-hugging-face-... tldr; Acquisition is an option on Hugging Face becoming the distribution and data-creation infrastructure for open physical AI.