How is this still up -_-
Show HN: GET Together – A social network where you don't need POST to Post
61–66 of 66 posts
Re: Show HN: GET Together – A social network where you don't need POST to Post
#62[dead]
Re: Show HN: GET Together – A social network where you don't need POST to Post
#63Earlier quoted context omitted.
That's not my site. But I have a question. At what point did you predict the following? "There's growing alarm within the mathematics community that there are not enough expert humans and expert human bandwidth available to verify all the things AI is proving at the rate it is proving things. Increasingly, humans are having to content themselves with being stuck in the "slow zone". It is hard for the human brain to k…
> That's not my site. You brought the figure as an argument, so I assumed that was your argument? If not, what was your argument then? I see a (super)exponential fit, but I don't see why that's better than a logarithmic fit on these axes (which would imply linearity). For covid we know well about infection disease dynamics. We do not have good models for AI because we do not have prior experience. Even the data point…
>I see a (super)exponential fit, but I don't see why that's better than a logarithmic fit on these axes (which would imply linearity).
A linear fit on a logarithmic y-axis implies exponential growth.
I myself don't have a strong view on ordinary exponential vs super-exponential for that graph.
COVID was only ordinary exponential, so super-exponential is not needed for the COVID analogy to be valid.
My point about mathematics was not about humans "losing control" of math. It was simply to ask if this was an outcome which you predicted.
Re: Show HN: GET Together – A social network where you don't need POST to Post
#64This takes me back to early 2000s when HTML forms were submitted using GET request. Fun times.
Re: Show HN: GET Together – A social network where you don't need POST to Post
#65Re: Show HN: GET Together – A social network where you don't need POST to Post
#66Earlier quoted context omitted.
> That's not my site. You brought the figure as an argument, so I assumed that was your argument? If not, what was your argument then? I see a (super)exponential fit, but I don't see why that's better than a logarithmic fit on these axes (which would imply linearity). For covid we know well about infection disease dynamics. We do not have good models for AI because we do not have prior experience. Even the data point…
>I see a (super)exponential fit, but I don't see why that's better than a logarithmic fit on these axes (which would imply linearity). A linear fit on a logarithmic y-axis implies exponential growth. I myself don't have a strong view on ordinary exponential vs super-exponential for that graph. COVID was only ordinary exponential, so super-exponential is not needed for the COVID analogy to be valid. My point about mat…
> A linear fit on a logarithmic y-axis implies exponential growth.
The fit on the graph is exponential, which makes it exp(exp(x)) growth. But it is not clear why it should be that, or linear, or logarithmic, which is what I meant.
Covid was exponential growth because the rate of infection (assuming a large enough population) is proportional to the current number of actively infected people. What is the analogy here? Is there a similarly widely accepted theory for why the models will improve exponentially rather than linearly? I am not sure recursive self-improvement is that clear to be going on, for instance.
I told you which outcomes I talk about. Even in a scenario where models improve exponentially, you still cannot have exponential growth in the long run in the same way that you cannot have that in the covid19 case either: you saturate the population. In the covid case a significant amount of the population has gotten infected so there are less people to infect, in the math case the problems to solve are gonna run out. Then, the bottleneck is how to pose new problems/set new directions of research, which was already not an easy problem to solve. The growth of covid was actually a logistic function, not an exponential one.