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Apple M7 Ultra Chip Planned With Up to 1.5 TB of Unified Memory (www.techpowerup.com)
submitted 2 months ago* by to c/technology@lemmy.world
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[–] 96 points 2 months ago (15 children)

One can only hope that it totally breaks the AI/LLM at industrial scale, so businesses can run their own AI systems with their own data sets.

No more of this fucking datacanter horseshit.

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  • [+] -17 points 2 months ago (12 children)

    Local LLMs are cool but also pretty slow compared to cloud. If you have to wait half an hour for your Feature while coding you might still opt for the cloud agent.

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  • [–] 26 points 2 months ago (2 children)

    Yes, they are slower. However, I think that the pricing we’re going to see from the cloud providers might be enough to deter quite a lot of people. At least I hope so:

    The fact that we’re already used to blazing speed generation kinda sucks. Local models are a much more sustainable way of unlocking the benefits of LLMs than giant ecosystem- and community-destroying data centers.

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  • [–] 3 points 2 months ago (1 child)

    I also hope that don’t get me wrong, but as I said: Waiting for the LLM agent to finish coding is currently a bottleneck in software development, they don’t pay high salaries for watching the AI code, they will prefer faster agents even if they are expensive, because they are not only paying the AI Company but also the software engineer overseeing them.

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  • [–] 7 points 2 months ago

    I think that is only going to last as long as the AI providers are willing to operate at a loss. The issue is even with the newer higher price points rolled out this year, they're still losing money. The slower AI machines may be the answer once the REAL profit earning price for the use tokens hits the market. I forsee lots of alternative work going on while the small LLM's are cooking the data. We will have to see once these machines start to roll out, what the use for LLMs will be and how it's applied. I am hopeful.

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  • [–] 12 points 2 months ago (4 children)

    Have you tried running a local model on a M series Mac?

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  • [–] 3 points 2 months ago (3 children)

    Yes ofc I ran Gemma 4 for example, but compare that to the speed of Gemini in the cloud the difference is massive.

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  • [–] 11 points 2 months ago (2 children)

    How much RAM do you have and which version of the model did you run?

    Local LLMs can be just as fast as long your device clears the requirements. If you noticed a huge difference, there’s a really good chance that you tried to use a model that requires more RAM than you have

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  • [–] 4 points 2 months ago (1 child)

    I ran Gemma 4 31 B quantized so it fits in my RAM. The decoding speed was decent, but if you look at the newest models for example Gemini flash 3.5 they have a decoding speed of 280 token per second, they generate an entire page before my Mac locally generates a sentence.

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  • [–] 3 points 2 months ago* (2 children)

    Yeah. But they're slow because most of us are GPU peasants. If someone were willing to drop $3-5K on a rig, they could probably run decent, dense models at greater than cloud speeds. Hell, with enough black magic, they could do it with less, but they'd have to go deep into the weeds.

    OTOH, $3-5K buys you a shit ton on Open Router, Claude, Chat, Lumo etc.

    The game is entirely rigged for "you will own nothing and be happy about it".

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  • [–] 1 point 2 months ago (1 child)

    If I buy a rig I might as well host it on the internet to get back some of the investment and sell the compute to others … wait a minute that’s cloud!

    It’s always cheaper to have the same hardware serve multiple people than just one.

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  • [–] 1 point 2 months ago

    Yes. People occasionally talk about pooling resources / creating a co-op to buy something like this. Easier to split $200K purchase (and probably $10k/month electricity costs) if 200-2000 people chip in. But then...that's just the cloud with extra steps.

    Can't says I've ever seen a co-op like that work but ICBW

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