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the view of the comments here seems to be quite negative for what meta is doing. Honest question, should they go to the route of openai and closed source + paid access instead? OpenAI or Claude seem to garner more positive views than llama open sourced.
The models are not open source, you're getting the equivalent of a precompiled binary. They are free to use.
And what about the future of social media? This is such devious, but increasingly obvious, narrative crafting by a commercial entity that has proven itself adversarial to an open and decentralized internet / ideas and knowledge economy. The argument goes as follows: - The future of AI is open source and decentralized - We want to win the future of AI instead, become a central leader and player in the collective open-…
And what about the future of social media? This is such devious, but increasingly obvious, narrative crafting by a commercial entity that has proven itself adversarial to an open and decentralized internet / ideas and knowledge economy. The argument goes as follows: - The future of AI is open source and decentralized - We want to win the future of AI instead, become a central leader and player in the collective open-…
It has been clear from the beginning that Meta's supposed desire for an open source AI, is just a coping mechanism for the fact that got beat out of the gate. This is an attempt to commoditize AI and reduce OpenAI/Google/Whoever's advantage. It is effective, not doubt, but all this wankery about how noble they are for creating an open-source AI future is just bullshit.
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Does it actually work? AIUI the current consensus is that you need massive interconnect bandwidth to train big models efficiently, and the internet is nowhere near that. I'm sure the Nvidia DGX boxes have 10x400Gb NICs for a reason.
I have no idea. The idea is certainly interesting but I've never actually understood how to run inference on these models... the people that run it seem to be unable to just talk simply.
Also, this doesn't seem to actually solve the issue of fine tuners needing funding to rent those GPUs? One alternative is something like AI Horde, which pays GPU providers with "labour vouchers" that allow them to get priority next time they want GPU. Requires a central platform to track vouchers and ban those who exchange them. Basically a sort of real-life comparison of mutualism (AI Horde) vs capitalism (bittensor).
And what about the future of social media? This is such devious, but increasingly obvious, narrative crafting by a commercial entity that has proven itself adversarial to an open and decentralized internet / ideas and knowledge economy. The argument goes as follows: - The future of AI is open source and decentralized - We want to win the future of AI instead, become a central leader and player in the collective open-…
Everyone tries this. Apple tried it with lawsuits and patents, Facebook did it under the guise of privacy, OpenAI will do it under the guise of public safety.
There's almost no case where a private company is going to be able to successfully argue "they shouldn't be allowed but we should" I wonder why so many companies these days try. Just hire better people and win outright.
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> Read the terms of use / contract for Meta AI products. If you deploy it, some producer finds the model spits out copyrighted content, knocks on Meta's door, Meta will point to you for the rest of the court case. If that's the future for AI, then it doesn't really matter whether China wins. As much as I hate Facebook, I think that seems pretty… reasonable? These AI tools are just tools. If somebody uses a crayon to…
AI safety is expensive, or even impossible, by releasing your models for local inference (not behind API). Meta AI shifts the responsibility of highly-general highly-capable AI models to smaller developers, putting ethics, safety, legal, and guard-rails responsibility on innovators who want to innovate with AI (without having the knowledge or resources to do so by themselves) as an "open-source" hacking project. Whil…
But, I think in that case the failing is not in not taking the liability for what other people do with their tool. It is in producing the tool in the first place.
Earlier quoted context omitted.
It has been clear from the beginning that Meta's supposed desire for an open source AI, is just a coping mechanism for the fact that got beat out of the gate. This is an attempt to commoditize AI and reduce OpenAI/Google/Whoever's advantage. It is effective, not doubt, but all this wankery about how noble they are for creating an open-source AI future is just bullshit.
I feel the same way. I'm grateful to Meta for releasing libre models, but I also understand that this is simply because they're second in the AI race. The winner always plays dirty, the underdog always plays nice.
In the same way that detectron and Segment anything is an industry standard.
Sure, for LLMs openAI released a product first. but its not unusual for meta to release useful models.
And what about the future of social media? This is such devious, but increasingly obvious, narrative crafting by a commercial entity that has proven itself adversarial to an open and decentralized internet / ideas and knowledge economy. The argument goes as follows: - The future of AI is open source and decentralized - We want to win the future of AI instead, become a central leader and player in the collective open-…
Doesn’t Threads and Fediverse indicate that they are headed that way for social as well?
Earlier quoted context omitted.
There's plenty of open source AI out there that isn't Meta. It's just not as good. The #1 problem is not compute, but data and the manpower required to clean that data up. The main thing you can do is support companies and groups who are releasing open source models. They are usually using their own data.
>The main thing you can do is support companies and groups who are releasing open source models. They are usually using their own data. Alternatively we could create standardized open source training data like wikipedia, wikimedia as well as public domain literature and open courseware. I'm sure that there are many other such free and legal sources of data.
There is a reason why datasets are private and the model weights aren't.
the view of the comments here seems to be quite negative for what meta is doing. Honest question, should they go to the route of openai and closed source + paid access instead? OpenAI or Claude seem to garner more positive views than llama open sourced.