541–550 of 936 posts
I hate how the moment it's too late will be, by design, closed doors.
The big winners of this: devs and AI startups - No more vendor lock-in - Instead of just wrapping proprietary API endpoints, developers can now integrate AI deeply into their products in a very cost-effective and performant way - Price race to the bottom with near-instant LLM responses at very low prices are on the horizon As a founder, it feels like a very exciting time to build a startup as your product automatical…
- Price race to the bottom with near-instant LLM responses at very low prices are on the horizon Maybe a big price war while the market majors fight out for positioning but they still need to make money off their investments so someone is going to have to raise prices at some point and youll be locked into their system if you build on it.
There are going to be loads of providers for these open models. Openrouter already has 3 providers for the new 405B model within hours.
They are positioning themselves as champions of AI open source mostly because they were blindsided by OpenAI, are not in the infra game, and want to commoditize their complements as much as possible. This is not altruism although it's still great for devs and startups. All FB GPU investments is primarily for new AI products "friends", recommendations and selling ads. https://www.joelonsoftware.com/2002/06/12/strategy…
Given the mountain of GPUs they bought at precisely the right moment I don't think that's entirely accurate
They are positioning themselves as champions of AI open source mostly because they were blindsided by OpenAI, are not in the infra game, and want to commoditize their complements as much as possible. This is not altruism although it's still great for devs and startups. All FB GPU investments is primarily for new AI products "friends", recommendations and selling ads. https://www.joelonsoftware.com/2002/06/12/strategy…
Earlier quoted context omitted.
I'm just a lowly outsider to the AI space, but calling these open source models seems kind of like calling a compiled binary open source. If you don't have a way to replicate what they did to create the model, it seems more like freeware than open source.
> If you don't have a way to replicate what they did to create the model, it seems more like freeware Isn't that a bit like arguing that a linux kernel driver isn't open source if I just give you a bunch of GPL-licensed source code that speaks to my device, but no documentation how my device works? If you take away the source code you have no way to recreate it. But so far that never caused anyone to call the code no…
> We’re releasing Llama 3.1 405B, the first frontier-level open source AI model, as well as new and improved Llama 3.1 70B and 8B models. Bravo! While I don't agree with Zuck's views and actions on many fronts, on this occasion I think he and the AI folks at Meta deserve our praise and gratitude. With this release, they have brought the cost of pretraining a frontier 400B+ parameter model to ZERO for pretty much ever…
Makes me wonder why he's really doing this. Zuckerberg being Zuckerberg, it can't be out of any genuine sense of altruism. Probably just wants to crush all competitors before he monetizes the next generation of Meta AI.
> We’re releasing Llama 3.1 405B, the first frontier-level open source AI model, as well as new and improved Llama 3.1 70B and 8B models. Bravo! While I don't agree with Zuck's views and actions on many fronts, on this occasion I think he and the AI folks at Meta deserve our praise and gratitude. With this release, they have brought the cost of pretraining a frontier 400B+ parameter model to ZERO for pretty much ever…
> We’re releasing Llama 3.1 405B Is it possible to run this with ollama?
Earlier quoted context omitted.
> better that the government removes IP on such technology for public use, like drugs got generics You want to punish NVIDIA for calling its shots correctly? You don't see the many ways that backfires?
No. But I do want to limit the amount we reward NVIDIA for calling the shots correctly to maximize the benefit to society. For instance by reducing the duration of the government granted monopolies on chip technology that is obsolete well before the default duration of 20 years is over. That said, it strikes me that the actual limiting factor is fab capacity not nvidia's designs and we probably need to lift the monop…
Lol it's not "monopolies" limiting fab capacity. Existing fab companies can barely manage to stand-up a new fab in different cities. Fabs are impossibly complex and beyond risky to fund.
It's the kind of thing you'd put government money to making but it's so risky government really don't want to spend billions and fail so they give existing companies billions so if they fail it's not the governments fault.
How are smaller models distilled from large models, I know of LoRA, quantization like technique; but does distilling also mean generating new datasets for conversing with smaller models entirely from the big models for many simpler tasks?