Where the AI market is talking

Greg Abbott says data centers:'basically dug their own grave'

https://www.anthropic.com/news/covering-electricity-price-in... I think that they tried to?

I were 17, I'd learn how to build LLMs from scratch

"...and then train..." and those dummies in openai and google wasting billions, while all they need is some 17 year old and few pizzas

OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

> The fact that AI models can be so easily distilled and replicated is such a stroke of luck. Sort of. It means the country on the verge of monopolizing all aspects of hardware production (China) doesn't need to rely on outsiders for the software. So while that weakens one monopoly it strengthens another.

India Country Brief: The Anthropic Economic Index

I were 17, I'd learn how to build LLMs from scratch

> there’s no way to “crack open” an LLM and see precisely where each skill or tendency lives Mechanistic Interpretability has entered the chat. For a classic example, see https://www.anthropic.com/research/tracing-thoughts-language... The spirit of your point stands, though. This kind of research is interesting to read about, but it's very hard, more like neuroscience or biology than computer science ("LLMs are grown, not made"). You're dealing with a lot of extremely _messy_ complexity, for which organic life is really the only good point of comparison. Most of us here are't really equipped for that kind of work; it's not at all like, say, reverse-engineering a piece of software written by humans. And of course the only people who can do it on frontier models from …

OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

They will just slow down the models even further. Anthropic is not up to this race.

Anthropic Could Aim to Raise $100B in Blockbuster IPO, Valuing It at $2T

https://www.nytimes.com/2026/08/21/technology/anthropic-ipo-...

Anthropic Could Aim to Raise $100B in Blockbuster IPO, Valuing It at $2T

A Claude Code skill that recovers export-blocked Kindle highlights

Doesn't this skill only work up until Anthropic tweaks weights or the system prompt(s) to not allow it?

OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

It's a mistake to think only OpenAI and Anthropic are actually spending the big bucks on pretrain, and the others just distill that. The Chinese models are pretrained on large clusters just like OpenAI ones are. Yes, they use outputs of the frontier models to further improve the final model, but even without those outputs they'd still have very strong models. It's not like in a world without distillation things would be much different as you claim.

OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

It's a mistake to think only OpenAI and Anthropic are actually spending the big bucks on pretrain, and the others just distill that. The Chinese models are pretrained on large clusters just like OpenAI ones are. Yes, they use outputs of the frontier models to further improve the final model, but even without those outputs they'd still have very strong models. It's not like in a world without distillation things would be much different as you claim.

Anna's Archive Owes $340 Million, Lost Several Domains, but It's Still Online

GPT-2 was trained using data scraped from the web ( https://cdn.openai.com/better-language-models/language_model... section 2.1), i.e. copyrighted data provided free of charge to anyone with an internet connection.

OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

Was it not obvious that the value and advantage was going to be in AI-adjacent services? The quality of the harness UX, and random fun crap like Sora, it's a shame that OpenAI killed that so soon, and also Group Chats in ChatGPT.. they risk running a Googlelike reputation at this rate Maybe ultimately whomever can be the "Apple of AI" will win

OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

To be precise, the distillation mentioned in this paper is not the distillation used by other model companies. In the one mentioned in the paper, your teacher and student model typically have similar architectures - and you typically need access to the full logits. What happens here instead is motivated by the fact that these companies don't have access to the training data and compute that anthropic/openai have. The distillation they do basically amounts to using traces from ant/oai models trained on much more data with a lot more compute (in many cases including the hidden intermediate tokens! turns out there were many ways to coax it out) and then either directly training on it or using it in many ways in post training pipelines. It falls under imitation learning, IMO.

OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

To be precise, the distillation mentioned in this paper is not the distillation used by other model companies. In the one mentioned in the paper, your teacher and student model typically have similar architectures - and you typically need access to the full logits. What happens here instead is motivated by the fact that these companies don't have access to the training data and compute that anthropic/openai have. The distillation they do basically amounts to using traces from ant/oai models trained on much more data with a lot more compute (in many cases including the hidden intermediate tokens! turns out there were many ways to coax it out) and then either directly training on it or using it in many ways in post training pipelines. It falls under imitation learning, IMO.

Coding expertise is going to collapse from AI reliance

What puzzles me is this: research means that we are exploring something that has not done before, yet using Claude to generate code means slicing and dicing what has been done many times before. So, I'm not sure how to make sense of both at the same time: Anthropic is pushing the boundary of AI, yet all the knowledge and engineering in form of code can be generated from the previous work?

Anthropic's best AI model struggles to attract users as cheaper tools thrive

I just don't like Anthropic's 5.0 models. When I tried Fable and Opus 5.0, they were super-slow and gave me sub-par results. I went back to Opus 4.8, and then switched to GPT 5.6 Luna. It's cheaper and better than Fable. This is just a case of competition working: Fable (and Opus 5.0) just aren't as good as Anthropic believes, and there's no switching cost, so everyone's moving away.

OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

The evidence is Anthropic's own reporting [1]. You may doubt that they're telling the truth, but that's what they're reporting. [1] https://www.anthropic.com/news/detecting-and-preventing-dist...

Anthropic's best AI model struggles to attract users as cheaper tools thrive

I'm with you on this. We have Claude at work and I get exhausted from using it just a bit. I've recently seen it say "let me verify the most load-bearing claims". I couldn't imagine anyone using "load-bearing", let alone "most load-bearing". Doesn't "load-bearing" alone imply "most"? I have so many questions for Anthropic about how they came up with this style.

Xiaomi: New CPU matches Apple cores single threaded, much faster multithreaded

I think describing what's happening "other countries seem to sit on their hands and happily outsource every bit of manufacturing to a single country" is disingenuous. It's been dubbed China Shock 2.0 and it's being taken very seriously by the EU. The US admin is a joke and too busy shooting itself in both feet to have coherent policy https://en.wikipedia.org/wiki/China_Shock_2.0