[CrazyStat]

The premise of the singularity concept was always superhuman intelligence, so it’s not so much a parallel as a renaming of the same thing.

> In Vinge’s analysis, at some point not too far away, innovations in computer power would enable us to design computers more intelligent than we are, and these smarter computers could design computers yet smarter than themselves, and so on, the loop of computers-making-newer-computers accelerating very quickly towards unimaginable levels of intelligence.

[d_silin]

Would never work in reality, you can't optimize algorithms beyond their computation complexity limits.

You can't multiply matrix x matrix (or vector x matrix) faster than O(N^2).

You can't iterate through array faster than O(N).

Search & sort are sub- or near-linear, yes - but any realistic numerical simulations are O(N^3) or worse. Computational chemistry algorithms can be as hard as O(N^7).

And that's all in P class, not even NP.

[direwolf20]

https://en.wikipedia.org/wiki/Computational_complexity_of_ma...

The n in this article is the size of each dimension of the matrix — N=n^2. Lowest known is O(N^1.175...). Most practical is O(N^1.403...). Naive is already O(N^1.5) which, you see, is less than O(N^2).

[dekhn]

We don't need to optimize algorithms beyond their computational complexity limits to improve hardware.

[razodactyl]

You're measuring speed not intelligence. It's a different metric.