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Local AI needs to be the norm

unix.foo

531–540 of 804 posts

Re: Local AI needs to be the norm

#531
it's not going to happen with LLMs unless ram + storage gets several orders of magnitude cheaper like, yesterday

informatics aren't magic, you'll never be able to compress """knowledge""" into a small model in a way equivalent to the 1.5 TB model

Re: Local AI needs to be the norm

#532
post #212

Earlier quoted context omitted.

> They will be, and that moment is not that far off. It's here, right now. I'm running quantized Qwen and Gemma on a decent, but three years old gaming rig (think RTX 3080 12GB and 32 GB RAM). Yes, it's slow, it has a small context window. But it can (given a proper harness) run through my trip photos and categorize them. It can OCR receipts and summarize spendings. It can answer simple questions, analyze code and ev…

I'm sorry to spoil it for you, but Perl script was able to do all of that like ... 10 years ago? The out-of-the-box Shotwell manages photos quite well without any intelligence. The problem, as people mentioned above, is SOTA models cognitive and tooling abilities. Also, have you noticed as top-end Mac Studios got downgraded recently? They don't want you to have access to frontier models. And you will not have it. See…

Do we even have decent OCR nowadays? Any free solutions?

Re: Local AI needs to be the norm

#533
We need better GUI and OS integrations with sandboxed local LLMs, before this is thrust on everyone and rolled out as the default in commercial OSes. Here in Berlin, I was functionally surrounded and hounded out of a local meetup, due to confrontation over the naive pushing of OS-level and network access agentic AI, done in the mode of mystical powers and artistic possibilities, which due to recent experiences, comes off as string-pulling, to produce a threat or danger that then must be observed and kept tabs on, according to Goodhart's Law.

Re: Local AI needs to be the norm

#534
post #212

Earlier quoted context omitted.

> They will be, and that moment is not that far off. It's here, right now. I'm running quantized Qwen and Gemma on a decent, but three years old gaming rig (think RTX 3080 12GB and 32 GB RAM). Yes, it's slow, it has a small context window. But it can (given a proper harness) run through my trip photos and categorize them. It can OCR receipts and summarize spendings. It can answer simple questions, analyze code and ev…

I'm sorry to spoil it for you, but Perl script was able to do all of that like ... 10 years ago? The out-of-the-box Shotwell manages photos quite well without any intelligence. The problem, as people mentioned above, is SOTA models cognitive and tooling abilities. Also, have you noticed as top-end Mac Studios got downgraded recently? They don't want you to have access to frontier models. And you will not have it. See…

The Mac Studio's disappearance is related to the fact that people now want them for the purpose of running local models. Supply and demand. That plus Apple doesn't shift prices for released products, and it essentially became underpriced when large RAM quantities exploded in price. For the price of 512GB of RAM alone you could get an M3 Ultra with 512GB of unified memory in a nice, quiet, and power efficient package. With the RAM you still need to spend a few thousand more on CPU/GPU, power supplies, storage and case.

Also the fact that an M5 version will be coming, and they likely know they are going to sell out on day one (I expect we'll see a price correction from Apple for higher end configs of M5 studios, base price will probably stay the same), so they need to build up stock reserves.

Re: Local AI needs to be the norm

#535

it's not going to happen with LLMs unless ram + storage gets several orders of magnitude cheaper like, yesterday informatics aren't magic, you'll never be able to compress """knowledge""" into a small model in a way equivalent to the 1.5 TB model

This will happen, but reconfiguring the infrastructure of the entire planet to train LLMs and run them over networks might be the "bubble", the megalomania.

Re: Local AI needs to be the norm

#536

Earlier quoted context omitted.

Users do not have an existing $80k of hardware, are not going to buy $80k of hardware for worse performance than paying $100/month, and models are continuing to grow in size while memory grows in price.

> paying $100/month There will not ever be a monthly subscription for LLM tokens. The economics isn't there. Local tokens will always be cheaper.

What's the basis for saying local tokens will always be cheaper? As others have outlined, LLMs serving one user at a time are pretty expensive, but concurrent users become much more cost-effective (assuming there's enough RAM for the contexts). If "local" to you means ~10 hours daily use by a team of employees, the company still has to balance against cloud services that can amortize non-recurring costs over 24 hours of service per day.

Re: Local AI needs to be the norm

#537

Here's some things you can do right now with local models on a consumer device: - text-to-speech - speech-to-text - dictionary - encyclopedia - help troubleshooting errors - generate common recipes and nutritional facts - proofread emails, blog posts - search a large trove of documents, find information, summarize it (RAG) - manipulate your terminal/browser/etc - analyze a picture or video - generate a picture or vid…

RAG on every machine, and the means for corporations / shadowy powers to query it.

Re: Local AI needs to be the norm

#539

it's not going to happen with LLMs unless ram + storage gets several orders of magnitude cheaper like, yesterday informatics aren't magic, you'll never be able to compress """knowledge""" into a small model in a way equivalent to the 1.5 TB model

I agree. But I also think the future is some kind of hybrid approach where agents run locally, what they can, and then call out to the cloud for what they can't.

Re: Local AI needs to be the norm

#540
post #212

Earlier quoted context omitted.

> They will be, and that moment is not that far off. It's here, right now. I'm running quantized Qwen and Gemma on a decent, but three years old gaming rig (think RTX 3080 12GB and 32 GB RAM). Yes, it's slow, it has a small context window. But it can (given a proper harness) run through my trip photos and categorize them. It can OCR receipts and summarize spendings. It can answer simple questions, analyze code and ev…

I'm sorry to spoil it for you, but Perl script was able to do all of that like ... 10 years ago? The out-of-the-box Shotwell manages photos quite well without any intelligence. The problem, as people mentioned above, is SOTA models cognitive and tooling abilities. Also, have you noticed as top-end Mac Studios got downgraded recently? They don't want you to have access to frontier models. And you will not have it. See…

You think Apple doesn't want you to use local models?

That's an interesting way to view the world. I mean, utterly stupid as it is, but interesting.

But the previous sentence is even stupider (a Perl script 10 years ago could write code like Qwen does now?), so I guess at least it's consistent.

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