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Local AI needs to be the norm

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Re: Local AI needs to be the norm

#191

Post by throwyawayyyy »

giobox wrote: post #155
apublicfrog wrote: post #147

Earlier quoted context omitted.

> 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 ti…

> they don't have a used by date For quite a lot of use cases, the current systems arguably do get worse over time if not continually updated. The knowledge cutoff date will start to hurt more and more as the weights age in a hypothetical scenario where you are stuck with them forever. Coding, one of the most popular usescases today, would not be great if it say only understood java to a version from years ago etc. h…

One solution is not to advance anything of course. I'm not even joking, is there going to be a successor to React? I suspect not, with the vast amount of training data for React now, it's going to look silly to move to something else with less support. What is the last new popular programming language, rust? Will there be another one? I suspect not. Same reasoning. The irony of all this AI acceleration talk is it'll work best if we don't accelerate the underlying tech at all.

Re: Local AI needs to be the norm

#193

Post by woah »

timeattack wrote: post #9

My problem with LLMs (apart from philosophical aspects and economical impact) is that it would be unlikely for any of us to be able to train something functional locally (toy-like LLMs -- sure, but something really useful -- no). Apart from that it requires immense computing power, it also requires a dataset which is for the most part is obtained illegally.

Can you make your own CPU, locally?

Re: Local AI needs to be the norm

#195

Post by robot-wrangler »

dakolli wrote: post #121
nullc wrote: post #114

Earlier quoted context omitted.

> two 4090s is not consumer grade I think that is a very narrow perspective. Enormous numbers of consumers own $50,000 cars, but a pair of $2000 GPUs is "not consumer"? I agree with your view that cheap tokens on SOTA are a trap-- people should use local AI or no AI.

I would still question what usefulness there is with a local model even with 10k in GPUs. I certainly haven't seen any great uses myself from these smaller models (<500 parameters) except claims from people who are totally enamored with AI and basically anything output from an LLM impresses them like a toddler who's entertained by the sound their velcro shoes makes.

Probably you're focused on coding agents? I bet someone could use that kind of hardware to filter snarky comments

Re: Local AI needs to be the norm

#197

Post by lxgr »

apublicfrog wrote: post #147
TheJCDenton wrote: post #20

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 f…

> 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 ti…

They’re really not good enough, unless you consider 64 GB of memory or more consumer grade.

Re: Local AI needs to be the norm

#198

Post by simonkagedal »

daishi55 wrote: post #98

> We are building applications that stop working the moment the server crashes or a credit card expires Isn’t this true of any application that accesses anything not running on your computer? This is just describing what it means to add an API call to your app. Nothing to do with AI (?)

Furthermore, for the example given, it would have made a lot of sense to me to generate those article summaries on the backend. Once and for all, no need to burden each client device (which are going to need to download the content anyway), no need to tie yourself to a specific provider (Apple in this case), can have the same experience everywhere. Of course, the backend could use a local (to itself) model.

Not saying it’s _wrong_ either – maybe it doesn’t use a backend of its own (the client downloads content directly from some predefined set of sites), maybe there is functionality to adjust how the summaries work that benefit from doing it on device, etc. Just doesn’t convince me that ”local AI should be the norm”.

Re: Local AI needs to be the norm

#199

Post by try-working »

oytis wrote: post #27
TheJCDenton wrote: post #20

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 f…

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

Open sourcing models is a marketing strategy. Chinese labs and small international labs have no awareness or distribution, so unless they become a hot topic for a while, nobody is going to bother trying out their models. Open source gets them that, and is essentially a tax on newcomers. When you start out you simply have no other option but to open source your models.

So, the business model of open models is the same as closed models: Sell inference. Open source is marketing for that inference.

https://try.works/#why-chinese-ai-labs-went-open-and-will-re...

Re: Local AI needs to be the norm

#200

Post by try-working »

2ndorderthought wrote: post #106
wood_spirit wrote: post #65

Earlier quoted context omitted.

Meta released Llama just when OpenAI was so hot and its valuation was going through the roof. Speculating, but Meta probably thought the model not competitive enough to keep as a secret weapon but well good enough to commercially damage OpenAI who were a sudden competitor for most-valued-company? In the same way you can imagine the Chinese government pushing the release of deepseek etc to make sure no one thinks the…

I disagree. I think deepseek, qwen, and kimi earn a lot of trust open sourcing their models. While still profiting. Effectively they are saying "yea don't crowd our data centers with small queries, go ahead and send your frontier questions to our frontier models. Oh btw those us models? You can run something about as good for free from us if you want hah." It's a power and marketing move. It's also insanely smart to…

Correct. Open source is a PR and marketing strategy for new labs, regardless of origin.

https://try.works/#why-chinese-ai-labs-went-open-and-will-re...

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