2 ms·

I doubt it, recreating what they've done in a short span of time only requires a small amount of capital. All the big players probably have teams working on thi

I doubt it, recreating what they've done in a short span of time only requires a small amount of capital. All the big players probably have teams working on this internally, and there are probably dozens of stealth startups gathering money to compete. I just don't see OpenAI scaling to the moon when the moat around their product is so shallow and disruptable. What is their long-term play besides having an API that can be replaced with by changing a POST request URL?

briHass 4y ago
How do you define 'small amount of capital'? Assuming you have to buy the processing from one of the big 3 (likely not possible to own the hardware outright), you're looking at 10s of millions of dollars per training run. It's certainly not outside reality for the well-known software companies to have divisions working on it, but I don't think we're quite at the point where garage startups can afford the compute.
- smoldesu 4y ago
  > likely not possible to own the hardware outright Why not? The majority of these models are running on fairly ubiquitous datacenter GPUs. They're being trained on highly available hardware. You're right that there's a compute barrier, but you get around that by throwing money at the problem. If someone was sufficiently motivated, they could probably dethrone OpenAI in 2 months with enough funding.
  - jonnyreiss 4y ago
    > If someone was sufficiently motivated, they could probably dethrone OpenAI in 2 months with enough funding. I'd argue Google is sufficiently motivated to dethrone OpenAI --- so why haven't they? They have plenty of money to throw at the problem as well.
yijuwarp 4y ago
they've put themselves in a extremely interesting position, the only way they stay on top is through innovation. there definitely is a spot for a gigantic AI company.

2 ms·

I doubt it, recreating what they've done in a short span of time only requires a small amount of capital. All the big players probably have teams working on thi

by smoldesu 4y ago

briHass 4y ago
How do you define 'small amount of capital'? Assuming you have to buy the processing from one of the big 3 (likely not possible to own the hardware outright), you're looking at 10s of millions of dollars per training run. It's certainly not outside reality for the well-known software companies to have divisions working on it, but I don't think we're quite at the point where garage startups can afford the compute.
- smoldesu 4y ago
  > likely not possible to own the hardware outright Why not? The majority of these models are running on fairly ubiquitous datacenter GPUs. They're being trained on highly available hardware. You're right that there's a compute barrier, but you get around that by throwing money at the problem. If someone was sufficiently motivated, they could probably dethrone OpenAI in 2 months with enough funding.
  - jonnyreiss 4y ago
    > If someone was sufficiently motivated, they could probably dethrone OpenAI in 2 months with enough funding. I'd argue Google is sufficiently motivated to dethrone OpenAI --- so why haven't they? They have plenty of money to throw at the problem as well.
yijuwarp 4y ago
they've put themselves in a extremely interesting position, the only way they stay on top is through innovation. there definitely is a spot for a gigantic AI company.