Which to me means, what's the Big o of this entire venture?
Ultimately, what they need to do is add nines of reliability. I guess I could argue that what they are producing now is like two nines: 99% accuracy.
Of course, that depends on how you measure it and yada yada yada. So for things like self-driving, I could see how people could argue that the accuracy rate is 99.9% on a minute by minute basis.
But how many nines do you need? Especially for self-driving five more? What's the computational cost to achieve that? Is it just five times? Is it 25 times? Is it two to the five power?
That's completely possible if the development of LLMs follow an S-curve (sigmoidal). At the beginning of the curve it will look exponential, then linear, and finally logarithmic. For different tasks, LLMs could be on different points on the curve, which would explain why some people perceive the improvements as exponential and others perceive them as logarithmic - they are simply working on different things and so experience different gradients.
Ultimately, what they need to do is add nines of reliability. I guess I could argue that what they are producing now is like two nines: 99% accuracy.
Of course, that depends on how you measure it and yada yada yada. So for things like self-driving, I could see how people could argue that the accuracy rate is 99.9% on a minute by minute basis.
But how many nines do you need? Especially for self-driving five more? What's the computational cost to achieve that? Is it just five times? Is it 25 times? Is it two to the five power?