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eicker, eicker@lemmy.world
Instance: lemmy.world
Joined: 3 weeks ago
Posts: 18
Comments: 166
Hi! š Iām Gerrit and in love with the Internet since 1994. š Media ā¹ Communication šØāš¬ Entrepreneur & Consultant at eickerĀ® [iCare] ā» Reinschauen: eicker.TV š² Get in touch! šš©šŖš¬š§ #Fedizen #AI #Tech #Media #Sovereignty
Posts and Comments by eicker, eicker@lemmy.world
technology
europe
Comments by eicker, eicker@lemmy.world
The industry keeps benchmarking against other labs instead of against user needs: If a 3.5GB model answers 95% of everyday questions well enough, the remaining few percent has to justify hundreds of gigabytes of weights, huge energy bills and constant cloud costs.
Stock prices arenāt proof of being right, but they do show investors can change their minds a lot faster than the narratives do.
Appleās marketing deserves skepticism, but the technical argument is separate. Local inference does not eliminate giant training clusters, it mainly cuts inference costs, latency and improves privacy. Apple still uses cloud models when needed.
Cookās biggest product might be expectation management. He rarely promises tomorrowās miracle, which buys Apple room to ship when it suits them instead of when Wall Street gets impatient.
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 thatās not the point: in 80%+ of cases, people wonāt 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.
Heheā¦ š
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.
Iām waiting for the next generation of Mac Mini and Mac Studio.
The present: Open Weight AI, such as Kimiās, is already almost exactly as good as ClosedAI from Anthropic and Ā»OpenAIĀ«.
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. š¤·
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.
Itās easy to underestimate how different these facilities are: Traditional data centres are built to run millions of separate workloads efficiently. AI data centres are engineered to make tens of thousands of GPUs act like one giant supercomputer. The building may look similar, but the power, cooling, networking and economics are almost an entirely different industry.
The market is fragmented across the Member States, each of which conducts its own research. That is precisely what needs to change. Hopefully, this approach will work.
This is a significant step for Europeās AI ambitions. Access to large scale compute has become one of the biggest barriers to building competitive AI models. If executed well, these gigafactories could give European startups, researchers, and companies the infrastructure they need to innovate at home instead of relying almost entirely on US or Chinese providers.
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 itās social media, gaming, or AI. If anything, it would be more surprising if major AI platforms werenāt 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 donāt even want to get started on WhatsAppā¦
The awkward part is that software has a habit of racing toward free once it becomes good enough. If an open weight model delivers 95 percent of the value without recurring API costs, plenty of companies will choose that and spend the savings on integration instead. History keeps rhyming, even if investors hate the tune.
Have you finished school?
Are you still interested in Closed AI?
Thatās not necessary: as the Open Weight AI models from the US are rather poor, nobody wants them anyway. š¤·
And on top of that, itās still saddled with XTwitterās debts.
Iād argue the models and software are the real long term assets. GPUs depreciate like any other hardware, but a better training pipeline, inference stack, proprietary data, and a model with millions of paying users can survive multiple hardware generations. The chips are replaceable. The ecosystem and customer relationships are much harder to replicate.
Perhaps. The difference with regard to OWAI, however, is that US companies have no alternatives to Chinese suppliers.
Maybe, but Ā»excessive investmentĀ« and Ā»failed technologyĀ« arenāt the same thing: Railroads, fiber optics and the dot com era all burned absurd amounts of capital, yet the infrastructure outlived the investors. AI could follow the same pattern: terrible returns for todayās shareholders, enormous value for tomorrowās economy.
Using security as a convenient tool to sideline foreign competition is a slippery slope, especially from companies that built their own success on open research.
OpenAI and Anthropic Lobby Washington to Restrict Chinese Open-Weight AI (implicator.ai)
Funny how every dip was supposed to be a once in a lifetime buying opportunity until people actually bought near the top. SpaceX is still an incredible company, but incredible companies can still be overpriced. Reality eventually sends the invoice, even when the CEO is treated like a prophet.
That assumes demand is fixed. Historically, the biggest technology shifts created entirely new markets that barely existed beforehand. Almost nobody predicted todayās cloud or app economy from early internet revenue. AI spending could still prove excessive, but current demand is a poor ceiling for what future demand might become.
I think thatās probably the most underrated use case. We keep treating LLMs like faster search engines, but their real value may be surfacing relationships humans never think to test.
Wall Street spent years demanding AI investment, then panicked when AI investment showed up on the balance sheet: If Alphabet keeps printing record profits while building the infrastructure for the next decade, this may end up looking more like impatience than prudence. The market loves growth, until it has to pay for it.
Turns out the biggest miracle wasnāt multiplying loaves, it was making authentication disappear. An IDOR this basic on an app handling personal data is embarrassing. š
Itās even worse! SpaceX includes XAi and XTwitter: cash burning nonsense. The only good thing about SpaceX is Starlink.
Iām a huge fan of the Fediverse, but the barriers are so incredibly high that itās unlikely a large number of people - let alone a majority - will find their way here.
Donāt forget his real name: TACO. š¤”
Climate change brings hotter temperatures, drier vegetation and longer heatwaves that turn fires that might have been manageable into disasters that overwhelm entire regions. Europe needs to stop treating these as exceptional summers. Theyāre becoming the new baseline.
Isnāt he just talking to bots there anyway, who canāt buy shares?