2 ms·

I do AI. I used to live by McCarthy's quote that "Real AI was probably possible on the computers from 30 years ago, if only we'd known how to program them". So

by ced 18y ago

I do AI. I used to live by McCarthy's quote that "Real AI was probably possible on the computers from 30 years ago, if only we'd known how to program them". So I bought my latest computer thinking: I've got 1000 times more processing power than necessary, so why buy a top-of-the-line computer? Why care about the mere factor of 2 that I could get for an extra 2000 bucks? What happens is this: today I had to solve software mini-problem #403 to put in experiment #14. I coded the naive O(n^2) algorithm, and damn it, it started paging, and performance crashes. I can't finish the experiment, unless I spend a few days looking up the right way to do it, O(log(n)); implementation, debugging, screams. Then I'll throw away the whole thing when I see that it doesn't work. Ah, I think, if only I'd have a 64 bit Common-Lisp.

jderick 18y ago
Sbcl and Ccl both have 64 bit implementations. I guess you just need a 64 bit machine?
- ced 18y ago
  Arh, I was hoping this wasn't true... I'm already using SBCL. The point is: software and hardware constraints limit your flexibility, and Naggum's argument that "a good engineer works around those constraints" is true if you have a fixed problem to solve and a lot of time, but it's not when rapid prototyping, which is what most of us should be doing. He says that no one should need a 64-bit CL (in 2002); I took his line back to make a crummy newspapery punchline, which turns out to be false as well. Stupid penchant for the dramatic.
  - omouse 18y ago
    Naggum's argument is that if you're working with a large dataset, it must have taken you a lot of time/money to obtain it and so you should be able to afford custom hardware and software to deal with it.
    - ced 18y ago
      I say that naive, brute force methods on modest datasets will generate huge memory and CPU requirements. The solution is either: waste some programmer time coding a better solution, or get better hardware/operating system. There's a tradeoff. Modern programming is super wasteful by the standards of 30 years ago. We traded computer ressources for programming convenience. There's still a lot of that to be done before we have all the convenience we want. Computers will be fast enough when I can do arithmetic with Church numerals.
Eliezer 18y ago
And do you think you know how to program them? If not, you're missing the premise of the syllogism.

by ced 18y ago

jderick 18y ago

Sbcl and Ccl both have 64 bit implementations. I guess you just need a 64 bit machine?

ced 18y ago
Arh, I was hoping this wasn't true... I'm already using SBCL. The point is: software and hardware constraints limit your flexibility, and Naggum's argument that "a good engineer works around those constraints" is true if you have a fixed problem to solve and a lot of time, but it's not when rapid prototyping, which is what most of us should be doing. He says that no one should need a 64-bit CL (in 2002); I took his line back to make a crummy newspapery punchline, which turns out to be false as well. Stupid penchant for the dramatic.
- omouse 18y ago
  Naggum's argument is that if you're working with a large dataset, it must have taken you a lot of time/money to obtain it and so you should be able to afford custom hardware and software to deal with it.
  - ced 18y ago
    I say that naive, brute force methods on modest datasets will generate huge memory and CPU requirements. The solution is either: waste some programmer time coding a better solution, or get better hardware/operating system. There's a tradeoff. Modern programming is super wasteful by the standards of 30 years ago. We traded computer ressources for programming convenience. There's still a lot of that to be done before we have all the convenience we want. Computers will be fast enough when I can do arithmetic with Church numerals.

Eliezer 18y ago

And do you think you know how to program them? If not, you're missing the premise of the syllogism.