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The decentralised operation of LLMs would also be significantly simpler and cheaper for the use of decentralised renewable energy sources.

I’m waiting for the next generation of Mac Mini and Mac Studio.

The present: Open Weight AI, such as Kimi’s, is already almost exactly as good as ClosedAI from Anthropic and »OpenAI«.

It would seem so. On the other hand, it is puzzling that they did not also allocate the necessary resources to the development of LLMs. 🤷

The interesting part is not whether Apple wins the biggest model race, but whether it changes the economics: If enough AI runs locally, every token avoided is cloud capacity nobody has to build. That is a very different business model from selling ever more cloud compute.

Tim Cook sees Apple’s hybrid AI strategy as a ‘competitive weapon’: Apple emphasizes that much of its AI suite — Apple Intelligence — can be run on the devices themselves.

This is exactly how the DSA is supposed to work: Once a platform reaches sufficient scale and societal impact, it faces higher transparency and accountability requirements regardless of whether it’s social media, gaming, or AI. If anything, it would be more surprising if major AI platforms weren’t eventually included.

ChatGPT and Roblox will be subject to tighter rules in the EU. They will be added to the EU’s ‘very large online platform’ VLOP list, subjecting them to stricter rules under the Digital Services Act.

These are purely paper profits.

Unfortunately, it is highly likely to take decades before Meta loses its relevance: the network effects are enormous, and the vast majority of people over 35 will probably only leave Instagram and (from the age of 60) Facebook completely in exceptional circumstances. And I don’t even want to get started on WhatsApp…

Meta can absolutely pivot to renting compute for whatever model wins, but calling that an automatic death spiral feels premature: Companies with billions of users can survive technical setbacks for years. Betting against distribution has humbled plenty of investors before.

What strikes me as particularly risky at Meta is the sheer amount of power Zuckerberg wields: ultimately, it’s the same problem as with Musk, even though Zuck has behaved much more moderately so far.

Interesting that Microsoft is effectively running a portfolio strategy instead of betting on a single lab. Anthropic is already paying off on paper while OpenAI looks much more volatile. That alone suggests the AI race is far less settled than the headlines usually imply, even for the company funding both sides. And now the Chinese Open Weight AI models are coming onto the scene too, offering almost the same quality.

Microsoft logs $3.2B from Anthropic investment, but OpenAI was a mixed bag

Pragmatic, but revealing. If Meta truly believed Llama would stay ahead, it would not be preparing for a future where competitors power its products. It also makes business sense for Meta because it already rents out compute capacity instead of using it for its own models: supporting multiple leading models could attract more customers to its infrastructure.

Mark Zuckerberg Says US Should Not Ban Chinese AI Models, Warns of Regulatory Capture. The Trump administration is expected to announce a voluntary testing framework.

That’s a more realistic ask than hoping everyone slows down: If alignment methods can be made accessible to engineers without deep math, more people can stress test, critique and improve them. Knowledge spreads far more easily than voluntary restraint, especially when geopolitical incentives point the other way.

Interestingly, China doesn’t need this computing power, yet Kimi has now unveiled a competitive model all the same. I wonder how this will pan out?

So have they been getting better and better?

How much more effective have the large models become for you over the last three years? Do you think development might come to a halt in China, for example, if US providers were indeed to stop developing or releasing them?

Absolutely. At the very least, everything of relevance, that is, anything that has been catalogued in libraries, for example, should be almost entirely digitised. We may well find out soon whether AI companies can still uncover anything of relevance amongst the other books, i.e. those that have not been widely published or catalogued. en.wikipedia.org/wiki/Book_scanning