[101008]

LLM will become like web frameworks in the future, in the sense that they will be free, open source, and everybody will be able to build on them. Sure, there will be paid options, such as there are paid web frameworks, but most of the time free options will be more than good enough for most of the jobs.

[smokel]

What is your argumentation for that? It seems that building LLMs is very costly, and that will probably remain so for quite some time.

I think it is equally likely that LLMs will perform worse in the future, because of copyright reasons and increased privacy awareness, leading to less diverse data sets to train on.

[nl]

> building LLMs is very costly, and that will probably remain so for quite some time.

Building LLMs is dropping in cost quickly. Back in mid 2023 training an 7B model had already dropped to $30K and it's even cheaper now.

> I think it is equally likely that LLMs will perform worse in the future, because of copyright reasons and increased privacy awareness, leading to less diverse data sets to train on.

I'll bet a lot of money this won't happen.

Firstly copyright isn't settled on this. Secondly people understand a lot more now about how to use less, higher quality data and how to use synthetic data (eg MS Phi series, Persona dataset etc and of course the upcoming OpenAI Strawberry and Orion models which use synthetic data heavily). Thirdly the knowledge about how to use multi-modal data in your LLM is much more widely spread, which means that video and code can both be used to improve LLM performance.

[1] https://arize.com/resource/mosaicml/

[bboygravity]

Existing free to use (offline) models are already really really good and open a ton of possibilities for new apps.

The only barrier right now is that laptop/phone hardware can't run them (inference and/or training) fast enough. That's a problem that won't really exist 3 to 10 years from now.

That's ignoring the fact that creation of new much much better models is going full steam ahead.

[jrm4]

I am genuinely baffled at how someone could come up with this take? I suppose it's because I went ahead and copped a $500 card about a month ago, and I can already literally do more than the big paid models presently can. I lack some of the bells and whistles, but I think more importantly, they lack uncensored models.

"AI" as we're calling it is aggressively defacto open-source, and I can see in no way how that competition doesn't drive down prices.

[smokel]

Training and inference are two different things. The incentive to make some model open is unrelated to hardware cost.

Perhaps you are missing something in my arguments that I can clear up?

[jrm4]

No, what I'm saying is -- it's kind of like Linux.

Yes, it would cost kabillions to recreate Linux from scratch. But no one has to anymore because it's here and anyone can just grab it.

Same with the models. What I can download right now from Huggingface is going to be 90% or more already there, and I can tweak them at home, despite how much it may have cost to make them in the first place.

[nativeit]

The balance may also shift towards more highly specific data that tunes local models towards the individual user. If that ultimately becomes more useful than, say, purchasing rights to some large archive of copyrighted materials, then things may lean farther towards a shared foundation upon which most day-to-day applications are developed. It will likely depend on the application and its specific focus, I don’t know that things will settle into an either/or situation, rather than a both/and.

[smokel]

I see. But what about adding new knowledge to the models?

To be useful in practice, one must train with new data, say every year or so. Who is going to pay for harvesting and cleaning all that data? And as I understand it, some form of RLHF is also required, which involves some manual labour as well.

Perhaps some day this will all be very cheap, and it might even be done by AI systems instead of humans, but I wouldn't bet my horse on it.

[jrm4]

I mean, given that I've literally done some version of it at home with RAG and it wasn't terrible, it's hard to think that it will be super difficult?

As in, I may not be able to do "general knowledge," but who will pay for that anyway (e.g. instead of baking it in to their Google killer?)

[101008]

Building software was very costly and hard 30 years ago. Things get cheaper and simpler with time. LLM will become a tool to use in your work, such as frameworks or libraries. Some people will, other people won't (mostly those to maintain projects without them).

I hope to be right or I will be jobless lol

[bubaumba]

> Building software was very costly and hard 30 years ago. Things get cheaper and simpler with time

No, it's just as complex as it was 30, 50 years ago. Because complexity is limited by developers' brains. As there was no noticeable evolution in last years the humans abilities stay the same. But there are many more humans involved in development. This makes the total complexity much higher.

> LLM will become a tool to use in your work

Not sure where you live, it's already very useful at work. Saves a lot of time. The effect is like from the internet with search engines. It doesn't make the work easier or lower the requirements. It makes developers, in this case, more productive.

[dartos]

So… just open source?

[samdung]

I really hope this becomes the norm.

[darepublic]

There are no paid web frameworks of note that I'm aware of

[aldanor]

The difference being, inference is not cheap at all.