So, OpenAI and Anthropic say the Chinese models are only as good because they distill their models. How true is that. I am sure it adds something. But is it more like a marginal 1% improvement or something really significant?
> Claude just gave up and did an HTML/CSS implementation but I insisted on native SwiftUI+Metal.
That sounds very odd and very contrary to my experience. You don’t say which model you actually used, but I never had opus 4.8 (or sonnet for that matter) ignore which language/stack i wanted to use.
I think (but I have no actual insides), they picked 800V dc for datacenter also because that is commonly used for the DC bus in EVs. So, one can share a lot of components across industries. Also, 800V just kind of works well for power transistors like SiC Fets.
> Not a fair comparison. 30-40x population difference.
I've always found that argument puzzling. A population 30 times larger also means roughly 30 times the technicians, funding, and resources etc.
Although, you have a very good point that internet speed is not everywhere good in Europe. Maybe that is what you are getting at? One can pick a place Europe with great internet speed, but one can also find places in Europe with terrible internet speed. In that sense it is a mixed bag just like the US.
Infineon is betting big on the 800V dc power distribution that seems to become the new standard for AI data centers which is directly relevant for the chips that are made in this fab.
Unfortunately it feels close to zero sum to me. I am getting absolutely drowned in AI generated personal sales pitches now. That obviously scraped my name/company online and automated the email. I feel sales becomes even more relient on trade shows and conferences and person to person interaction (Only talking about B2B stuff that I am involved in).
> How does anthropic know my "kernel" project isn't a personal toy and not the Linux kernel?
The Linux Kernel is in its training data. I just tested it. I copied about 20 random lines from the linux kernel and asked which codebase this was from and it could immediately tell.
My understanding is that a lot of AI data centers are still heavily relying on spinning HDDs, which is why seagate, western digital are selling more HDDs than ever before.
When you first built it, were you aware there was market for the data? Or was this something you discovered afterwards? It makes sense, but I wouldn’t have guessed it.
> 2. Talent & compute: due to #1, Silicon Valley can outbid Europe for the best talent and hardware. Watch an OpenAI launch video and listen to all the European accents.
There is definitely a lot of truth to that. Maybe a bit of an arbitrary measure, but these are the nationalites of the people that wrote the "Attention is all you need" paper. Pretty revealing I find:
Absolutely not. My wife could apply for German permanent residency as well as now German citizenship from within Germany. She has been living in Germany for 10 years now and at no point in the process did she have to go through a German consulate (she is a US citizen).
So, I experimented a little bit with smaller models and the problem I faced is that it would simply not call a tool that is available, but instead just describe the tool. Is this something that Forge can help with?
I think it had more to do with the reality of the market. Solar panels have become incredibly cheap and that's because they are mass produced and standardized. Everything in the manufacturing process has been optimized. Now it is technically of course possible to make them other form factors, but artisinal solar panels are simply so much more expensive and cannot compete in any meaningful way with regular panels.
My understanding is that the US doesn’t really have an official category called “medium sized”. So I think the “small business” category is better compared to EU’s SME category (small-medium-enterprise), which is often lumped together.
I have recently played around with lots of data from measurements and one can totally dump everything into context and let Claude try to analyze data that way. It burns through a lot of tokens. It is smarter to save data to disk and let Claude write scripts that handles/analyzes the data. It’s much faster and the results are much better and you save a lot of tokens. But I guess Amazon prefers the first approach.
I have been experimenting on using AI for hardware development. I showed some experiments on HN a couple of weeks ago (https://news.ycombinator.com/item?id=47801255). I am now trying to make my approach a little bit more comprehensive and structured, instead of several disjoint MCP servers, a single platform that connects lab instruments to AI assistants: https://teasel.tools/
As a demo, I repaired an old Philips PM5190 function generator (about 40 years old) and connected it to Claude Code. Lots of fun. Going to post a follow up video the next couple of days.
I am currently working on: teasel.tools