31–40 of 279 posts
I wrote about this when llama-3 came out, and this launch confirms it: Meta's goal from the start was to target OpenAI and the other proprietary model players with a "scorched earth" approach by releasing powerful open models to disrupt the competitive landscape. Meta can likely outspend any other AI lab on compute and talent: - OpenAI makes an estimated revenue of $2B and is likely unprofitable. Meta generated a rev…
Classic strategy.
I wrote about this when llama-3 came out, and this launch confirms it: Meta's goal from the start was to target OpenAI and the other proprietary model players with a "scorched earth" approach by releasing powerful open models to disrupt the competitive landscape. Meta can likely outspend any other AI lab on compute and talent: - OpenAI makes an estimated revenue of $2B and is likely unprofitable. Meta generated a rev…
It's pretty clear the base model is a race to the bottom on pricing. There is no defensible moat unless a player truly develops some secret sauce on training. As of now seems that the most meaningful techniques are already widely known and understood. The money will be made on compute and on applications of the base model (that are sufficiently novel/differentiated). Investors will lose big on OpenAI and competitors…
This is why Altman has gone all out pushing for regulation and playing up safety concerns while simultaneously pushing out the people in his company that actually deeply worry about safety. Altman doesn't care about safety, he just wants governments to build him a moat that doesn't naturally exist.
I wrote about this when llama-3 came out, and this launch confirms it: Meta's goal from the start was to target OpenAI and the other proprietary model players with a "scorched earth" approach by releasing powerful open models to disrupt the competitive landscape. Meta can likely outspend any other AI lab on compute and talent: - OpenAI makes an estimated revenue of $2B and is likely unprofitable. Meta generated a rev…
> Open source likely attracts better talent and researchers I work at OpenAI and used to work at meta. Almost every person from meta that I know has asked me for a referral to OpenAI. I don’t know anyone who left OpenAI to go to meta.
Does anyone know why they haven't released any 30B-ish param models? I was expecting that to happen with this release and have been disappointed once more. They also skipped doing a 30B-ish param model for llama2 despite claiming to have trained one.
Is there a way to run this in AWS? Seems like the biggest GPU node they have is the p5.48xlarge @ 640GB (8xH100s). Routing between multiple nodes would be too slow unless there's an InfiniBand fabric you can leverage. Interested to know if anyone else is exploring this.
I wrote about this when llama-3 came out, and this launch confirms it: Meta's goal from the start was to target OpenAI and the other proprietary model players with a "scorched earth" approach by releasing powerful open models to disrupt the competitive landscape. Meta can likely outspend any other AI lab on compute and talent: - OpenAI makes an estimated revenue of $2B and is likely unprofitable. Meta generated a rev…
Is there a way to run this in AWS? Seems like the biggest GPU node they have is the p5.48xlarge @ 640GB (8xH100s). Routing between multiple nodes would be too slow unless there's an InfiniBand fabric you can leverage. Interested to know if anyone else is exploring this.
Is there a way to run this in AWS? Seems like the biggest GPU node they have is the p5.48xlarge @ 640GB (8xH100s). Routing between multiple nodes would be too slow unless there's an InfiniBand fabric you can leverage. Interested to know if anyone else is exploring this.