zyroth | 18 years ago | on: Production Languages and Toy Languages
zyroth's comments
zyroth | 18 years ago | on: Steve Jobs keynote speech leaked?
That's why he was talking about the macpro and not the macbook pro.
zyroth | 18 years ago | on: Converting Pi to binary: Don't do it!
Anything related to the concept of infinity tends to be hardly understandable in an "emotional" or "intuitive" way. We can just apply the rules of logic and accept.
zyroth | 18 years ago | on: Here's the basic problem: you're writing a text editor. Stop doing that. It's 2007.
and planned economy is superior, too.
zyroth | 18 years ago | on: Converting Pi to binary: Don't do it!
Since pi is not random, we cannot say that every finite string is in it. (If it was, the probability P[s in binary representation] would be 1 for every finite s)
Actually, there is no proof and no counter proof that every finite string comes up in pi. (...that I know of)
zyroth | 18 years ago | on: Converting Pi to binary: Don't do it!
> There are an uncountably many number of non-normal real numbers like this, even though the infinite amount of normal real numbers is bigger.
How sure are you with that one? Mind to supply a proof?
zyroth | 18 years ago | on: Converting Pi to binary: Don't do it!
Yes, I can:
01001000100001...
Guess what? There are uncountable ones.
zyroth | 18 years ago | on: Converting Pi to binary: Don't do it!
Actually it is not guaranteed that every string of bits will at some point be a substring of pi. Bad joke, since wrong.
zyroth | 18 years ago | on: The Next Generation of Neural Networks [Google Tech Talk]
Search for 'deep belief hinton' on google.
zyroth | 18 years ago | on: Mac OS X Leopard: 200+ Productivity Booster Keyboard Shortcuts
> Shift-F11 Hide all windows in slow motion
Productivity Booster, right.
zyroth | 18 years ago | on: Ask YC: What new technologies are you exploring?
Machine Learning, especially Reinforcement Learning
zyroth | 18 years ago | on: Ideas to monetize new artifical intelligence
fincancial fraud detection bottlenecks are typically between ram and the processor. Thousands of snychronously incoming transactions have to be examined simultanously, because they correlate heavily.
It is not like "here is one transaction, is it a fraud?" but "here are 2^20 transactions, what are the frauds?".
You could do this by pipelining, but I guess Banks want a zero downtime system and I personally would not trust an API in terms of reliability.
Another point is, that banks will not give you the original data. They will have to "pseudonymize" several entries, such as credit card numbers, names, ... This would force them to preprocess the data which gives every transaction a very little + O(n) and which might decrease the speed even more.
(I'm not saying it's technically impossible, but I'd say there are better ways, such as releasing it closed source or just using it to predict financial data - which as we all know is possible and being done by hedge fonds, so this should be the best way IF you have that algorithm ;)
zyroth | 18 years ago | on: Ideas to monetize new artifical intelligence
There are a lot of different fields in ML. I don't believe that you have an algorithm that beats all algorithms out there , even if those are specialized on a specific setting.
zyroth | 18 years ago | on: Ideas to monetize new artifical intelligence
> And a bank trying to analyze if a credit card transaction is fraud or not doesn't care about the short delays either.
Oh yes, they do. That I do know.
zyroth | 18 years ago | on: Ideas to monetize new artifical intelligence
I don't believe you.
zyroth | 18 years ago | on: Ideas to monetize new artifical intelligence
Uhm? The latency as a public api will render it useless for most applications.
zyroth | 18 years ago | on: Norvig - new world's longest palindrome
Those things are useful. :)
zyroth | 18 years ago | on: How to teach a Bayesian spam filter to play chess
If you want them to learn a specific concept that we know, they can learn it, yes.
zyroth | 18 years ago | on: How to teach a Bayesian spam filter to play chess
Training examples.
zyroth | 18 years ago | on: How to teach a Bayesian spam filter to play chess
No, I'm saying that a neural network can learn addition.
See, a bayesian cannot really understand that there are relations between two numbers (like "is bigger than" or "is the following number of"), but a neural network can, since addition is part of a NN.
My personal recommendation on machine learning is 'Pattern Recognition and Machine Learning' by Chris Bishop. But you definately do need a solid mathematical background for that.
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I think you get used to every Syntax. The point is, Lisp et al are much more compact, which makes the concepts easier to grasp.
I get a (mapcar #'f '(1 2 3)) much quicker than a
x = {1, 2, 3}; for (int i = 1; i < 4; i++) { x[i] *= 2; }