He took over a failing Dutch tech company and turned it around. Nexperia was on the path to bankruptcy, that’s why it was on the market to be sold back in 2017. His company injected capital and made it profitable. Even last year, his parent company even announced a $200M expansion of Nexperia’s Hamburg plant, which totally goes against the narrative that they were moving production out of Europe.

The Dutch govt is trying to spin this, but they have like 5 different storylines and none of them make sense.

In some dimensions, current day LLMs are already superintelligent. They are extremely good knowledge retrieval engines that can far outperform traditional search engines, once you learn how properly to use them. No, they are not AGIs, because they’re not sentient or self-motivated, but I’m not sure those are desirable or useful dimensions of intellect to work towards anyway.

The kneejerk reaction is gonna be “Meta bad”, but it’s actually a bit more complicated.

Whatever faults Meta has in other areas, it’s been mostly a good player in the AI space. They’re one of the major reasons we have strong open-weight AI models today. Mistral, another maker of open AI models and Europe’s only significant player in AI, has also rejected this code of conduct. By contrast, OpenAI a.k.a. ClosedAI has committed to signing it, probably because they are the incumbents and they think the increased compliance costs will help kill off competitors.

Personally, I think the EU AI regulation efforts are a big missed opportunity. They should have been used to force a greater level of openness and interoperability in the industry. With the current framing, they’re likely to end up entrenching big proprietary AI companies like OpenAI, without doing much to make them accountable at all, while also burying upstarts and open source projects under unsustainable compliance requirements.

The EU AI Act is the thing that imposes the big fines, and it’s pretty big and complicated, so companies have complained that it’s hard to know how to comply. So this voluntary code of conduct was released as a sample procedure for compliance, i.e. “if you do things this way, you (probably) won’t get in trouble with regulators”.

It’s also worth noting that not all the complaints are unreasonable. For example, the code of conduct says that model makers are supposed to take measures to impose restrictions on end-users to prevent copyright infringement, but such usage restrictions are very problematic for open source projects (in some cases, usage restrictions can even disqualify a piece of software as FOSS).

That article is overblown. People need to configure their websites to be more robust against traffic spikes, news at 11.

Disrespecting robots.txt is bad netiquette, but honestly this sort of gentleman’s agreement is always prone to cheating. At the end of the day, when you put something on the net for people to access, you have to assume anyone (or anything) can try to access it.

It’s seldom the same companies, though; there are two camps fighting each other, like Gozilla vs Mothra.

It’s possible to run the big Deepseek model locally for around $15k, not $100k. People have done it with 2x M4 Ultras, or the equivalent.

Though I don’t think it’s a good use of money personally, because the requirements are dropping all the time. We’re starting to see some very promising small models that use a fraction of those resources.

So long as there are big players releasing open weights models, which is true for the foreseeable future, I don’t think this is a big problem. Once those weights are released, they’re free forever, and anyone can fine-tune based on them, or use them to bootstrap new models by distillation or synthetic RL data generation.

Power usage probably won’t be a major issue; the main take-home message of the Deepseek brouhaha is that training and inference can be much more efficiently than we had thought (our estimates had been based on well-funded Western companies that didn’t have to bother with optimization).

AI spam is an annoyance, but it’s not really AI-specific but the continuation of a trend; the Internet was already drowning in human-created slop before LLMs came along. At some point, we will probably all have to rely on AI tools to filter it out. This isn’t something that can be unwound, any more than you can undo computers being able to play chess well.

They released the major components of their training and interference infrastructure code a couple weeks ago.

Deepseek actually released a bunch of their infrastructure code, including the infamous tricks for making training and interference more efficient, a couple of weeks ago.

The strangest twist to this is that Deepseek itself seems to be the only company not trying to cash in on the Deepseek frenzy:

Liang [Deepseek’s founder] has shown little intention to capitalise on DeepSeek’s sudden fame to further commercialise its technology in the near term. The company is instead focusing the majority of its resources on model development…

These people added the independently wealthy founder has also declined to entertain interest from China’s tech giants as well as venture and state-backed funds to invest in the group for the time being. Many have found it difficult to even arrange a meeting with the secluded founder.

“We pulled top-level government connections and only got to sit down with someone from their finance department, who said ‘sorry we are not raising’,” said one investor at a multibillion-dollar Chinese tech fund.

Funny thing is, the price of lidar is dropping like a stone; they are projected to be sub-$200 per unit soon. The technical consensus seems to be settling in on 2 or 3 lidars per car plus optical sensors, and Chinese EV brands are starting to provide self driving in baseline models, with lidars as part of the standard package.

It’s strongly dependent on how you use it. Personally, I started out as a skeptic but by now I’m quite won over by LLM-aided search. For example, I was recently looking for an academic that had published some result I could describe in rough terms, but whose name and affiliation I was drawing a blank on. Several regular web searches yielded nothing, but Deepseek’s web search gave the result first try.

(Though, Google’s own AI search is strangely bad compared to others, so I don’t use that.)

The flip side is that for a lot of routine info that I previously used Google to find, like getting a quick and basic recipe for apple pie crust, the normal search results are now enshittified by ad-optimized slop. So in many cases I find it better to use a non-web-search LLM instead. If it matters, I always have the option of verifying the LLM’s output with a manual search.

Maybe, maybe not – but I’m discounting anything the UK government says on Internet-related issues, so long as they’re trying to insert encryption backdoors into everything. For all we know, this is just an attempt to blackmail Apple and Google over the encryption thing.

Pretty much inevitable. Nowadays there are so many robot vacuum cleaners from different brands, and everyone has more or less figured out the tech so they all work pretty well. (I have a Roborock, and have nothing to say about it other than it keeps the floors clean and doesn’t cause me any grief.) There’s no moat, so consumer market success is purely a matter of manufacturing and cost efficiency, and iRobot obviously would have a huge upfill fight against Samsung, Xiaomi, and a thousand other light consumer goods makers.

I mean, I don’t demand an open source washing machine or dryer either.

Google search results are so terrible that at this point it’s a mercy.

Aside from national pride or security, one issue is that there’s a Taiwan law requiring TSMC to keep latest gen fabs in Taiwan. So if TSMC takes over Intel fabs, Intel’s US operations will never be able to reach latest gen (not that Intel is currently in good shape to achieve this, of course).

Slightly off topic, but the writing on this article is horrible. Optimizing for Google engagement, it seems. Ironically, an AI would probably have produced something vastly more readable.