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Open source AI must win

opensourceaimustwin.com

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431–440 of 538 posts

Re: Open source AI must win

#431

Post by andai »

mike_hearn wrote: post #328
andai wrote: post #234

Earlier quoted context omitted.

>The communication speeds are untenable. Can it be parallelized or not? If you take a model, make two copies, and fine-tune each one on different data, what happens when you merge them? Does it work if you freeze different layers? I think this works if the steps are small enough. And the transfer should become tenable if the steps are big enough. Where's the cutoff?

Yes it can be parallelized, it already is in real AI datacenters and no it doesn't help you. Like everyone else is saying, an AI datacenter is not just a bunch of gaming GPUs connected via normal ethernet and hasn't been for years. At most a decentralized effort could contribute a little bit to some bigger centralized effort by doing inference and sandboxed CPU work. Modern model training isn't just backprop, it's go…

Kinda sounds like we just need better computers.

Re: Open source AI must win

#432

Post by killerstorm »

WarmWash wrote: post #75

Who is going to fund it? Training is unfathomably expensive. You have either VC funded models looking for a return on investment, or CCP funded models looking to solidify authoritarian "model Chinese society". Maybe there are some university 4B models, but I doubt those will carry far.

It's not only expensive, it's also wasteful - there's no value in using an obsolete model.

Open source AI manifesto demand that "Opensource AI should remain ... economically viable". That's just wishful thinking.

Re: Open source AI must win

#433

Post by baalimago »

> If intelligence becomes something people can only rent from a few closed institutions

Just your your natural born intelligence..? It's worked for the past 10k+ years, I'm sure it will work for some time longer

Re: Open source AI must win

#434

Post by deadbabe »

It sucks how in just a few years the world has decided nothing is worth doing or is just impossible without the use of AI. As if regular human intelligence isn’t enough anymore and it has to be paid for somehow.

Re: Open source AI must win

#435

Post by adamtaylor_13 »

dofm wrote: post #402

It won in my house/my business right from the start. (Well, open weights, at least — which is an uncomfortable nuance.) I have never understood the willingness to make the functioning of or development of a product so completely dependent on the secret sauce of one of two big unprofitable, inscrutable startups. It really defies sensible engineering principles to do that. So I was never going to do it. I'm exploring A…

Interestingly, I've taken a different approach. AI supplements how my business builds and I'd much rather have all my engineers using Opus 4.8 rather than whatever the best open source models are.

I believe open source is important, but for my business I'm just going to use the best tools I have available to me.

Re: Open source AI must win

#436

Post by indigodaddy »

Avicebron wrote: post #410
bilsbie wrote: post #403

Earlier quoted context omitted.

What is that? I can’t seem to figure out what the use case is vs buying off the shelf? I think it’s a great project but the communication isn’t clear to me.

https://tinygrad.org/#tinybox I'm not sure exactly why you would buy through them vs rolling your own if you could afford the equivalent hardware. I'm a firm supporter of local inference though so good on them for doing something

Lol I get nervous when I see a list of products with full specs but no prices

Re: Open source AI must win

#437

Post by CuriouslyC »

dboreham wrote: post #426
CuriouslyC wrote: post #396

Earlier quoted context omitted.

Not true. Big models buy you baked in knowledge and long context cohesion. A model can be trained to use search and knowledge base tools more efficiently to mitigate the former, and harnesses/workflows can be designed to push models into small parallel threads to mitigate the latter. The thing that big models will always bring to the table is the ability to YOLO weak/under-specified prompts, and spend less time in th…

These things sound plausible, but have they actually been demonstrated? Wouldn't anyone who succeeded in making such a small but useful LLM be raking in the money now?

Cursor's composer 2.5 is a perfect example. It's right on the heels of the frontier (for coding only) for an order of magnitude cheaper. As much as I've shit on Cursor in the past, I do think the company is well positioned to pick up people getting sticker shock on Anthropic tokens, if they can get their marketing down.

Re: Open source AI must win

#438

Post by dwa3592 »

Not today, may after the next 3-4 breakthroughs. One thing that people don't realize is that the AI they use today is highly highly subsidized bc of the capex that has gone into it. Even if people collaborated together - will not be able to raise billions of dollars that are needed.

These are still very very (and very) early days of the modern AI and there are so many changes that are gonna happen. It's possible that all the frontier labs of today won't exist in a few years.

Re: Open source AI must win

#439

Post by RandyOrion »

I don't know how open source AI wins. The description is too vague for serious discussions. What I do know is that, once closed source AI groups become anti-you, you should punish them, or help open source groups, or both.

If you really want specific open source {LLM, LMM, research, harness, whatever} groups to win over closed source counterparts, you may show your care by trying open source solutions first when solving problems. And if they're really capable, award them with contributions or something.

Re: Open source AI must win

#440

Post by energy123 »

Folcon wrote: post #333

A question I've got which I've been wondering about, not sure if anyone else has been thinking about it, what actually made Fable so effective? From what I could tell from the very little time that I had to interact with it, it's instruction following seemed more consistent The other thing that comes to mind is a lot of people commented on how driven it was, so I'm wondering whether figuring out how to keep existing…

Probably just a bigger version of Opus if I had to wager, and Opus is just a bigger version of Sonnet. Maybe some small architectural differences baking in an additional few months of ablation studies/research. But the fundamental driver is new pretrain with larger size. Probably corresponding to when some new generation of GPUs/new datacenter came online rather than any major qualitative breakthrough.

Hints: They created a new label instead of version bumping Opus, they didn't deprecate Opus, and it costs more per token.

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