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Local AI needs to be the norm

unix.foo

51–60 of 804 posts

Re: Local AI needs to be the norm

#51

Yet there is another post a few rows down where people are losing their shit that Chrome has a local LLM model that uses a couple of GB of space for local-inference. Damned if they do, damned if they don't.

Maybe don't use gigabytes of bandwidth and storage space, without asking.

Re: Local AI needs to be the norm

#52

Yet there is another post a few rows down where people are losing their shit that Chrome has a local LLM model that uses a couple of GB of space for local-inference. Damned if they do, damned if they don't.

This is a weird take. If its not opt in or you’re shoe horning it into a browser, then that sucks. Nobody is getting enraged that an app for running local LLMs downloads data to do so.

Re: Local AI needs to be the norm

#53

Yet there is another post a few rows down where people are losing their shit that Chrome has a local LLM model that uses a couple of GB of space for local-inference. Damned if they do, damned if they don't.

You don't understand the difference between "I run a local LLM because I chose to" vs "The browser chose to run a local LLM and I have no say"? You don't understand?

Not to mention that the LLM that I choose to run requires a monster machine and is infinitely more capable than whatever google chose to put on their browser?

I mean, none of this affects me because I don't use chrome, obviously, but you don't see the difference? Bewildering.

Re: Local AI needs to be the norm

#54
post #27

Earlier quoted context omitted.

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

> What is the business model of open weight AI? This is what I do not understand as well and advertising the knowledge and more advanced model is also the only thing that comes to my mind. Since a month I am using gemma4 locally successfully on a MBP M2 for many search queries (wikipedia style questions) and it is really good, fast enough (30-40t/s) and feels nice as it keeps these queries private. But I don't unders…

Why would you want to try to support all users simple queries on your ai data center if they could run it on their own computer?

It builds good will also. it also shows research prowess.

For China it's different. They need to show Americans who don't trust them at all because of propaganda that they have no tricks up their sleeve. It also doesn't hurt when Chinese companies drop models for free people can run at home that are about as good as sonnet. Serious mic drop.

Re: Local AI needs to be the norm

#55
post #27

Earlier quoted context omitted.

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

> What is the business model of open weight AI? This is what I do not understand as well and advertising the knowledge and more advanced model is also the only thing that comes to my mind. Since a month I am using gemma4 locally successfully on a MBP M2 for many search queries (wikipedia style questions) and it is really good, fast enough (30-40t/s) and feels nice as it keeps these queries private. But I don't unders…

[deleted]

Re: Local AI needs to be the norm

#56
post #27

Earlier quoted context omitted.

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

It should be feasible to crowd fund training runs right?

A training run costs somewhere in the neighborhood of a billion dollars. That’s a thousand millions.

How many crowdfunded projects do you know that have raised even one percent of that? Who’s going to be in charge of collecting that scale of money? Perhaps some sort of company formed for the benefit of humanity, which will promise to be a non-profit? Some sort of “Open” AI?

Oh, wait.

Re: Local AI needs to be the norm

#58

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.

Not the whole thing, at least with current technology, but LoRAs are really good at fine tuning, and can be generated in a few hours on high-end gaming computers, so as long as the base model is in your language, you likely have enough spate computing power, in whatever electronics you own, to train a few LoRAs a month.

In the future, when regular home computers have the capabilities of modern servers, we'll be able to train the entire LLM at home.

Re: Local AI needs to be the norm

#59
post #6

It feels like we're one technological breakthrough away from all of these data centers going up to be deemed irrelevant.

The cynical take is getting more and more to be the only rational one: The promised mega-data center deals are meant to boost valuations today, not serve tons of customers three years from now.

It seems pretty clearly inline with the dotcom bubble to me. Every company claims to be a leading AI company, those building infrastructure are promising the moon and getting 1/3 of the way there, and no one knows how to monetize it justify the hype or expense.

Re: Local AI needs to be the norm

#60

Earlier quoted context omitted.

> What is the business model of open weight AI? This is what I do not understand as well and advertising the knowledge and more advanced model is also the only thing that comes to my mind. Since a month I am using gemma4 locally successfully on a MBP M2 for many search queries (wikipedia style questions) and it is really good, fast enough (30-40t/s) and feels nice as it keeps these queries private. But I don't unders…

Why would you want to try to support all users simple queries on your ai data center if they could run it on their own computer? It builds good will also. it also shows research prowess. For China it's different. They need to show Americans who don't trust them at all because of propaganda that they have no tricks up their sleeve. It also doesn't hurt when Chinese companies drop models for free people can run at home…

Indeed cost can be another factor. Maybe also the main reason why Chrome added an offline model.
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