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  • Apple has always been unusually willing to sacrifice short term hype for long term positioning. That does not guarantee they are right, but it is a very different bet from spending hundreds of billions assuming demand will eventually justify the buildout. If AI demand disappoints, discipline suddenly looks a lot more valuable than scale.

  • About 4+ maxed M4 Studios, I guess. But that‘s not the point: in 80%+ of cases, people won’t need that kind of AI model to solve their problems.

  • Raw capability is only one metric: A local model probably will not beat the best cloud model any time soon, but it does not need to. If it handles 80 to 90% of everyday tasks instantly, privately and at near zero marginal cost, that is a huge win. Reserve the cloud for the genuinely hard requests, not every prompt.

  • Hehe… 😈

  • Absolutely. Looking forward to seeing the next generation of Macs.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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?

  • Technology @lemmy.world

    How OpenAI’s human mistake led to the AI-powered hack on Hugging Face

    techcrunch.com /2026/07/22/how-an-openais-human-mistake-led-to-the-ai-powered-hack-on-hugging-face/
  • Technology @lemmy.world

    If you pay a hacker’s ransom, chances are that they’ll come back for more

    techcrunch.com /2026/07/22/if-you-pay-a-hackers-ransom-chances-are-that-theyll-come-back-for-more/
  • Technology @lemmy.world

    Bessent says U.S. could sanction China over AI model ‘theft’

    www.cnbc.com /2026/07/21/bessent-china-ai-sanctions.html
  • Technology @lemmy.world

    China considers tighter export controls on AI models and chips

    www.reuters.com /world/asia-pacific/china-considers-tighter-export-controls-ai-models-chips-ft-reports-2026-07-21/
  • Technology @lemmy.world

    Trump administration reportedly builds a slow-motion ban on Chinese AI models through sanctions and soft pressure

    the-decoder.com /trump-administration-reportedly-builds-a-slow-motion-ban-on-chinese-ai-models-through-sanctions-and-soft-pressure/