Seems like they are quite startled with LLama 2 and Code Llama, and how its rapid adoption is accelerating the AI race to zero. Why have this when Llama 2 and Code Llama exists and brings the cost close to $0?
This sound like a huge waste of money for something that should just be completely on-device or self-hosted if you don't trust cloud-based AI models like ChatGPT Enterprise and want it all private and low cost.
But either way, Meta seems to be already at the finish line in this race and there is more to AI than the LLM hype.
> This sound like a huge waste of money for something that should just be completely on-device or self-hosted
I can imagine this argument being made repeatedly over the past several decades whenever anyone makes a decision to use any paid cloud service. There is a value in self-hosting FOSS services and managing it in house and there is a value in letting someone else manage it for you. Ultimately it depends on the business use case and how much effort / risk you are willing to handle.
If you could offer stable 70B llama API at half the price of ChatGPT API I would pay for it. I know HN likes to believe everything is close to $0, but it is hardly the case.
I get the self-host part, but if you had a dedicated machine would the ram be an issue? Can you run it on a machine with like 128GB of ram or the GPU equivalent?
agreed, and I can't wait for gpt4 to have great competition in terms of ease, price and performance. I was responding to this
> something that should just be completely on-device or self-hosted if you don't trust cloud-based AI models like ChatGPT Enterprise and want it all private and low cost
Less technical companies throw money at problems to solve them. Like mine, sadly... Even if it takes a small amount of effort, companies will throw money for zero effort.
Zero execution risk, rather than zero effort. There’s always a 10% chance that implementation goes on forever and spending some money eliminates that risk.
Maybe, but that's why things like ollama.ai are trying to fill the gap. It's simple, and you don't need all of the heavy weight enterprise crap if nothing ever leaves your system.
This sound like a huge waste of money for something that should just be completely on-device or self-hosted if you don't trust cloud-based AI models like ChatGPT Enterprise and want it all private and low cost.
But either way, Meta seems to be already at the finish line in this race and there is more to AI than the LLM hype.