The deadliest weapons in existence had been developed without sophisticated computers or software. Even the fastest computer in the 50s had less processing power and memory than a Palm Pilot.
You are confused about the difference between the
neural net as a mathematical model and its computer implementation.
Mathematically speaking neural network is a function with certsain parameters. Learning is a way to adjust the parameters to fit the function to the actual data.
Just as with people there is a difference between performing a certain task and learning to do it.
Why are we so enthusiastic about developing intelligent computers, given that this fate is inevitable?
We should keep computers in their place as simple but fast Turing Machines, and not allow them to step up the ladder to sentience.
Why are we so enthusiastic about educating intelligent humans, given that this fate is not inevitable? We should keep humans in their place as simple but not so fast human beings and not allow them to step up the ladder to sentience.
Integer performance is a lot more important for compilers, etc rather than floating point.
OSes are unlikely to benefit much from SSE optimization. And Athlon is quite a bit faster in integer performance.
It seems that the only well-designed unit in P4 is its SSE engine. On the other hand it might be more
related to high latency of the Rambus memore than to processor design.
What is scary is how many people agree with the author of the original message (it got moderated to 5).
So far there has een no demonstrable ill effects from genetically engineered plants. There was that business with butterflies in England, but
there is no agreement on it either.
And how is genetically engineered food different from hevily engineered foods of the past? They used mutagens, radiations and what not to try to find beneficial mutations in the last 50 years.
But not when researchers finally do hove some idea on how to look for them, people are crying frankenfoods...
Unfortunately, giving up on x86 binary compatability is still considered to big a risk for PC/MB producers.
Why is it unfortunate? It would be a huge error to waste billions of lines of code written for x86 just in order to get some theoretical improvement in speed.
And in any case if you really need serious performance why not get an Alpha? Few people do actual computations and for most it is really unimportant whether the architecture is x86 or not.
Looks like AMD did bring the dual board in at the right time.
What do you mean by that? AMD still does not have dual support for Athlon and will not have an MP chipset (according to what they say at least) until Q2 2001.
Furthermore, scientists seek agreement between their models and the behaviour of reality only because that makes their theories useful as
opposed to being merely mathematically interesting.
Useful for what purpose? You mean, if the theory were not "useful" scientists would not seek agreements between the theory and reality?
It is somewhat surprising that someone who is so
thouroughly bored with Kubrick movies took time to watch so many of them.
You call Kubrick cruel? Nobody is but yourself is forcing his films on you. But if you choose to watch them anyway, that is perhaps you find them worth watching.
Granted they are slow, but in movies as in a lot of other things, the patience is often rewarded.
Why? Hm... I guess it makes sense to compare new technologies to the best that is available and not to the average because there are already plenty of things that are better then average.
Suppose there were already monitors with 10 mln pixels, then this news would not have been newsorthy at all.
Slashdot Mirror
make the hull thicker
make the hull more reflective
use plenty of decoys
I am pretty up-to-date on that. I think you are mistaken about that. Factoring is NP, of course, but whether it is NP-complete is not known.
Give a reference to prove me wrong
However it is not know whther P=NP in terms of quantum computers as factorisation is not known to be NP.
Also there is no reason to think that quantum computers will be faster or indeed more suitable for most problems than ordinary computers.
Mathematically speaking neural network is a function with certsain parameters. Learning is a way to adjust the parameters to fit the function to the actual data.
Just as with people there is a difference between performing a certain task and learning to do it.
Have you heard about backpropagation learning for recurrent neural nets?
Owned by the government means not regulated? Interesting.
Only American pigs need apply.
Yes, simplistic web for simple people!
Not nearly as much resources have been spent on it but I think fairly decent algorithms do exist.
Why are we so enthusiastic about educating intelligent humans, given that this fate is not inevitable? We should keep humans in their place as simple but not so fast human beings and not allow them to step up the ladder to sentience.
OSes are unlikely to benefit much from SSE optimization. And Athlon is quite a bit faster in integer performance.
It seems that the only well-designed unit in P4 is its SSE engine. On the other hand it might be more related to high latency of the Rambus memore than to processor design.
What is scary is how many people agree with the author of the original message (it got moderated to 5).
So far there has een no demonstrable ill effects from genetically engineered plants. There was that business with butterflies in England, but there is no agreement on it either.
And how is genetically engineered food different from hevily engineered foods of the past? They used mutagens, radiations and what not to try to find beneficial mutations in the last 50 years. But not when researchers finally do hove some idea on how to look for them, people are crying frankenfoods...
Why is it unfortunate? It would be a huge error to waste billions of lines of code written for x86 just in order to get some theoretical improvement in speed.
And in any case if you really need serious performance why not get an Alpha? Few people do actual computations and for most it is really unimportant whether the architecture is x86 or not.
266 Mhz front side bus does not make much difference in terms of performance however. Mostly the increas is due to DDR memory.
Your numerical program in all likelihood take advantage of neither.
Also don't forget that Intel has far greater resources to make sure all the compilers, etc are fully optimized.
What do you mean by that? AMD still does not have dual support for Athlon and will not have an MP chipset (according to what they say at least) until Q2 2001.
Useful for what purpose? You mean, if the theory were not "useful" scientists would not seek agreements between the theory and reality?
You call Kubrick cruel? Nobody is but yourself is forcing his films on you. But if you choose to watch them anyway, that is perhaps you find them worth watching.
Granted they are slow, but in movies as in a lot of other things, the patience is often rewarded.
Actually attributing it to Galileo would probably be more correct. He had pretty good understanding of basic physical concepts.
I am not sure what you call "an actual science", but I would argue that is comes from the Greeks.
Suppose there were already monitors with 10 mln pixels, then this news would not have been newsorthy at all.
True, but you should compare the new technology to the best that is available now, not to the average.
I am sure these labs that are purchasing the monitors are not using 1024x728 either.
If the resolution is 2000x1500, then you have 3x10^6 pixels.
9x10^6 / 3x10^6 = 3
convincing?
Not even 4 times sharper as a matter of fact!
People who write these articles need to take some remedial math classes.
The resolution is something like 3500x2500. Best commercially available displays have something like 2000x1500. 3 or 4 times sharper is more like it.