Silicon Chip Survival of the Fittest

0b1 writes "A scientist has created a Microproccessor that can distinguish between a few words, by just letting it "Mutate", and mixing the Different designs that worked, while eliminating those that didn't. Read the full article if you like. " People are doing a lot of this stuff right now; anyone else wonder where it will end up?

Comments

But...

[Anonymous Coward]

...will these chips work in Kansas?

Get a life.

[binarybits]

Why do half a dozen people have to point it out every time an article is a repeat. Yes, it's a repeat. Who cares? If you've seen it before, just ignore it. And if you haven't seen it before, then it's not a problem.

If you must point it out, send email to Rob or Hemos. That way you know they'll actually see the message. But posting a message about it is just a waste of everyone's time. Rob and Hemos don't have time to read every post on every story, but a lot of the rest of us will waste time reading it. We don't need to be impressed by how good your memory is.

Evolvable Hardware Conference

[Tekmage]

The First NASA/DOD Workshop on Evolvable Hardware - lots of abstracts; full text if you have IEEE membership. Took place 19-21 July, 1999.

Genetic algorithms in signal routing

[Tekmage]

Circuit evolution raises yields on GHz chips - something of a more recent vintage. :-)

Genetic algorithms

[Kaa]

Genetic algorithms by now is old (heh) and a decently understood techology. Essentially this is nothing but a general-purpose global optimization method. So the guy applied that optimization technique to FPGAs and got something. Big deal. People have done much more interesting things with genetic algorithms.

Besides, it is just me, or the whole genetic algorithm thing is getting blown all out of proportion by the media, somewhat similar to what happened to neural nets several years ago?

And the article is quite clueless. It implies that software is too limiting (only 0s and 1s, after all), so playing with FPGAs will open wider horizons. And the researcher speaks of not understanding what's going on like it is a good thing...

Kaa

Re:Genetic algorithms

[Kaa]

The point was that they are developing chips that will allow the GA to have access to more analog info.

And the point of this being..? So far they've only managed to make their solution very fragile.

Besides, it's not like you couldn't simulate analog conditions in software.

GA's are not all that well understood. They have been relatively widelly applied, but on a theoretical level we don't have much more aparatus than the schema theorem (Holland) at our disposal.

Well, we are probably talking about different things here. You are talking about understading in terms of proving theorems about. I am talking understanding in a more practical way -- having an idea what usually works, what never works, and what has never been tried yet. Compared to 4-5 years ago we understand much more about GAs, their uses and limitations.

Neural networks have received quite a lot of hype and are generally poorly understood by people who proclaim their utility.

It has been my personal experience that people who proclaim NNs as a general solution to all problems do not understand them at all.

However we are just scratching the surface of what can be done with Genetic algorithms and genetic programming.

On the one hand, yes. On the other hand, they are still nothing more than a general-purpose global optimization technique, not a magic wand. Granted, reasonable global optimizers are very hard to come by, but it's still nothing but search in parameter space.

Kaa

Re:Genetic algorithms

[Kaa]

The thing is without proof of convergence, the solution you find using GA may very likely be something you hadn't thought of, and even be a better one at that too, but not the optimal one!

One, I think that there is proof of convergence -- albeit in infinite time :(

Two, for non-trivial problems you cannot guarantee the global optimum without exhaustive search which is infeasible most of the time. The great majority of problems will settle for something reasonably close to the global optimum, "reasonably" being defined by the specific problem you are trying to solve.

I'd rather use a more expensive, but garanteed, method instead. But those are hard to come by too.

There are no guaranteed global optimizations (in the general case) with the exception of exhaustive search. If you can afford an exhaustive search, by all means run it and get your precise global optimum. Unfortunately, for most real-life problem the exhaustive search is so far out of the realm of feasability, it's not even funny. How about finding me a global minimum of a nonlinear function of, say, 15 real-valued variables? You use GAs in situations where you don't have much choice -- you either do a local search with all its disadvantages, or pick an imprecise and "semi-random" solution (GA or, say, simulated annealing). Sometimes the local search is the right way to go, sometimes not.

Kaa

Re:Genetic algorithms

[jacobm]

And the article is quite clueless. It implies that software is too limiting (only 0s and 1s, after all), so playing with FPGAs will open wider horizons. And the researcher speaks of not understanding what's going on like it is a good thing...

I think you missed the cool part of the research- Thompson didn't understand what was going on because what was going on was fundamentally different from how the electrical engineers do things. In the Discover article, they went into more detail on that point. Apparently, some of the designs that the GA evolved contained components that were entirely unconnected to the main circuitry, but that couldn't be taken out without making the chip stop working.

And the point about software being too limiting: they're talking about efficiency. If you want to solve the problem using software, think about all the gates you have to use! It's not that it can't be done, but if you can do it with 100 gates in hardware, that's probably better than a 10,000+ gate software solution. Particularly when no one has ever been able to do it with less than 1,000 gates using traditional techniques.

Re:Circuits that know who to sue.

[MindStalker]

Hmm hey guys, why don't we use these new evolved chips in our missle command centers.

Sure that sounds great.

evolved chip: "hehe they still don't even know how I work, I've passed all their safty 'test' hehehe if they only knew if they only knew"

I'm sorry I couldn't resist. Would be funny though, if we accidently evolved thinking machines and didn't even know it.

Re:Circuits that know who to sue.

[MindStalker]

Hmm, as always I like that picture of the future better. P.S. I'm generally not a negative future seerer I was just in a negative mood I guess :)

Evolving Sprite Behaviour

[Priestess]

Anyone else ever actually try to build something and let it evolve? About six years ago I wrote a little DOS program (I can Email it to anyone who asks in a few days but i'm offline at home right now so I'd have to fetch it on a disk and it's the weekend in a couple of hours) to try and evolve the behaviour of some little sprites wondering all over the screen.

It used a decision tree to decide what to do given inputs like what's standing in front and what's to the sides and what have you. They could decide to move forward or turn or attack the square in front. Their 'energy' level was tracked and attacking each other or the 'grass' that grew around randomly replenished it. When they were all dead the last few to die got to spawn the next generation. I was interested to see how hard it would be to evolve some better AI for games.

They did, quite quickly, evolve what looked like the same algo as the tree I built by hand to test the code (move forward unless theres a wall in front in which case turn left - oh and if there's food in front then eat it) but the tree was a mess. Couln't tell what was going on inside the code. They never really got any farther though.

What I found interesting was that trying to evolve from my test tree was impossible. My delicately constructed tree was completely screwed as soon as you changed one byte of it - the poor critters just died. The algo that evolved though was WAY more robust, upping the mutation rate to crazy levels still left the critters doing something better than standing still in confusion.

I did start work on a new version that would let the inputs evolve as well. Rather than just seeing to the sides and two squares in front the viewable square's locations themselves could evolve. I got distracted and moved onto something else before I ever finished it though. Story of my life

Pre.......

Circuits that know who to sue.

[SirSlud]

"How acceptable is a safety-critical component of a system if it has been artificially evolved and nobody knows how it works?" he asks. "Will an expert in a white coat give a guarantee? And who can be sued if it fails?"

This is the funniest thing I have ever read (well, today.) Yeah! Who can be sued when it fails? What good is human existance without somebody or some organization to blame things on? Using one of these circuits and then suing the maker if it fails is like drinking until you sustain braindamage, and then suing the beer company. Is there no such thing as personal accountability anymore? Doesn't anyone take respocibility for their own actions? For that matter, why don't they just 'evolve' a circuit that always knows who to sue? (Although, when when that breaks down, /then/ who do you sue?)