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> If you've been using each new step is very noticeable and so have the mindshare. Around Sonnet 3.7 Claude Code-style coding became usable

Yet I vividly remember the complaints about how 3.7 was a regression compared to 3.5 with people advising to stay on 3.5.

Conversely, Sonnet 4 was well received so it's not just a story about how complainers make the most noise.


https://www.cnbc.com/2026/02/12/anthropic-gives-20-million-t...

Now you see where you dollars are going.

(I'm pretty sure all AI tech company want regulatory capture, but Dario has been by far the most vocal lobbyist against competition).


> how good the results are for consumers.

Only if you take consummer electronics out of the equation, because this AI arm race has wrecked havoc in the market for consumer GPUs, RAM, SSD and HDD.

If you take the arm race externalities into account, I'm very much unconvinced that we're better off than last year.


> A lot of people aren't, and the AI legitimately writes better.

It may write “objectively better”, but the very distinct feel of all AI generated prose makes it immediately recognizable as artificial and unbearable as a result.


> I spent about 500 dollars and 16 hours of conversation to get an MVP static marketplace

If I wasn't already convinced that agentic tools were slot machines, here's a very strong argument in favor of that theory…


It doesn't need to, during inference there's little data exchange between one chip and another (just a single embedding vector per token).

It's completely different during training because of the backward pass and weight update, which put a lot of strain on the inter-chip communication, but during inference even x4 PCIe4.0 is enough to connect GPUs together and not lose speed.


How do you think that works?!

With the exception of diffusion language models that don't work this way, but are very niche, language models are autoregressive, which means you indeed need to process token in order.

And that's why model speed is such a big deal, you can't just throw more hardware at the problem because the problem is latency, not compute.


Kvark was leading the engineering effort for wgpu while he was at Mozilla.

But he was doing that on his work time and did so collaborating with other Mozilla engineers, whereas AFAIK blade has been more of a personal side project.


And made almost zero impact, it was just a bigger version of Deepseek V2 and when mostly unnoticed because its performances weren't particularly notable especially for its size.

It was R1 with its RL-training that made the news and crashed the srock market.


And the author completely misses the point thinking it's somehow mandatory in plaster walls, when it's just a convenience thing that avoids making holes in the plaster…

I do appreciate why people want to avoid that, plaster does crumble pretty easily. Combined with 100+ year old lath that is as hard as iron, it can be a mild pain in the ass to hang a picture without doing more damage to the plaster than you want.

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