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TheJCDentonyesterday at 8:15 PM10 repliesview on HN

For the mainstream audience, the sentiment around local ai today is the same that they had around open source a few decades ago. For a few products, some paid solutions were so much more advanced that open source were very often completely overlooked. Why bother ? And the like. Then we had captive SaaS and other plateforms and now it's obviously wrong for most of us.

The dependency we have with anthropic and openai for coding for instance is insane. Most accept it because either they don't care, or they just hope chinese will never stop open weights. The business model of open weights is very new, include some power play between countries and labs, and move an absurd amount of money without any concrete oversight from most people.

It's a very dangerous gamble. Today incredible value is available for nearly everyone. But it may stop without any warning, for reason outside our control.


Replies

apublicfrogyesterday at 9:58 PM

> It's a very dangerous gamble. Today incredible value is available for nearly everyone. But it may stop without any warning, for reason outside our control.

What stops you from running the best open weighted LLMs currently available on consumer grade hardware for the rest of time? They're good enough for 95% of use cases, and they don't have a used by date. From what I can see, the "danger" is not having the next tier that comes out, but the impact of that is very low.

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oytisyesterday at 8:21 PM

What is the business model of open weight AI? I don't think there is any. At best it can serve as an advertisement for the more advanced models you sell.

The huge difference to open source is that you can't just train an LLM with free time and motivation. You need lots of data and a lot of compute.

I sure want to be wrong on that, I definitely like the open-weight version of the future more

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ios-contractoryesterday at 11:15 PM

I don't think it should be local vs cloud AI. I think local AI should be treated as a separate product. local ai should do things that really don't need cloud AI, then cloud AI should be used as a fallback. That would reduce a lot of costs

slicktuxyesterday at 9:52 PM

I’m just waiting for the US Government to implement their own local AI. Which will eventually lead to them open sourcing it because it’s tax payer funded and being that the NSA has decades worth of internet data they can train on; open weights would be just as good as any companies…

aabhayyesterday at 8:38 PM

Disagree with this. When cost becomes an important factor or the free but worse option becomes compelling and accessible (i.e. on device agent via apple style UX), there has been significant user behavior towards local. Think about stuff like removing backgrounds from photos, OCR on PDFs, who uses paid services for casual usage of these things?

furyofantaresyesterday at 10:27 PM

What's the gamble here exactly? What agency do we have in it right now?

iLoveOncallyesterday at 9:44 PM

The mainstream audience does not have the faintest idea that "local AI" is even a thing.

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irishcoffeeyesterday at 10:01 PM

I own 2 5070TI cards in a rig I would gladly donate time to for a distributed training model effort. The kicker is the training data. I would want to gate the data to anything before 2022. I don’t know how to coordinate that, but I would really like to be involved in something like this. SETI, for LLMs.

michaeljeyesterday at 10:32 PM

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RataNovayesterday at 9:47 PM

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