Data Mining Used to Create New Materials

Roland Piquepaille writes "MIT researchers have successfully integrated data mining tools and modern methods of quantum mechanics. They've designed software which can help predict the crystal structures of materials. To simplify, they say they've used methods used by online sales sites to suggest books to customers. And it seems to work: they claim they can determine in days the properties of atomic structures that might have taken months before. Read more for additional references and pictures."

Comments

Principles of the universe

[suv4x4]

There are two surprisingly simple and "dumb" principles that exist in our world.

The first is called evolution (random mutation, breeding of the fittest) the result of which is basically everything around us, and it has resurfaced in computer programming as genetic programming, which essentially uses random processes and selection to create new inventions, mechanisms and even intelligent virtual creatures.

The second I'll call "intelligent observation". It's basically how animals and people learn everything they know, by observing and applying "what seems to make sense" in other areas of our lives, even without understanding the underlying mechanisms (and how we discovered fire, or tools by observing similar nature mechanisms/animals). This has resurfaced in computer programming as data mining.

Data mining and genetic programming: these two beat any patent, any existing algorithm, because they are not crippled by our limited brain capacity to understand the world around us. Expect a lot more of both in computer science and our lives in the following years.

Re:Principles of the universe

[greg_barton]

Following years? How about now?

http://www.genetic-programming.com/humancompetitiv e.html

http://www.human-competitive.org/

(2006 results aren't posted yet...)

I was at the GECCO06 conference (Genetic and Evolutionary Computation COnference) when the Human Competitive awards were handed out. The first place winner went to a guy whu evolved an oscillator that used HALF as many capacitors and resistors than the industry standard one. The second place winner evolved input parameters to Schrodinger's equations that enabled him to model a certain chemical reaction 10 and in some cases 1000 times faster than the earlier best result in the literature. And the rest of the entries were fascinating as well.

http://www.genetic-programming.org/hc2006/entrants _table.html

The 1st and 2nd place entries were #5 and #6 respectively.

Re:Principles of the universe

[GeffDE]

Your view on genetic algorithms is just plain wrong.

One of the reasons that "Intelligent Design" is so palatable to so many people is that nature and life are so damn complex. There is a textbook called Molecular Biology of the Cell; this book's aim is to precisely define the chemical pathways and biological structures that constitute a living cell, and it is roughly 2000 pages long. It is still outrageously incomplete. This massive tome is looking at something that is so incredibly minute that you are formed by trillions of them. It takes a 2000 page book to incompletely describe the simplest part of you. What is mind-boggling to many people (and simply awe-inspiring to the rest) is that such a simple rule as "survival of the fittest/random mutation" could create so complex a system. The fact is, such complexity is inherent in the system, and that complexity arises out of simplicity. A great tutorial on that is Cellular Automata.

Now, you do bring up an interesting point about the positive feedback loop that our brains have created with technology. But if you extend your scenario to a few years after "The Almighty CAD Program" is designed, you may indeed reach that technological singularity, where a machine can design another machine inside a CAD program, and, a few years later, might be able to either make that machine with the automated robots already used for assembly, or even emulate it with its own hardware. Now you have reached the point where "genetic algorithms" are doing exactly what you have claimed they cannot. Genetic algorithms only tackle problems in a simple problem state because they have not been allowed to evolve enough. Bacteria are much simpler than humans, and they also first came around billions of years ago. After nature had time to evolve from the bacteria, it got more and more complex. So too will genetic algorithms.

Sounds like AI

[RalphTheWonderLlama]

This sounds a bit like Computer Learning/ AI to me. Give it a zillion past cases to learn from and then let it predict the next one. I did some things along those lines in my AI class for machine problems (perceptron comes to mind), though not nearly as complicated. That was a fun CS class.

I'm not sure it's that advanced

[Colin Smith]

I mean, regression to match candidates against an existing body of data, we have dating web sites which do that these days. Nice way of quickly sorting the candidates but Nature material?

Quantum Modeling isn't new...

[purduephotog]

... I worked on it when I was employed by Eastman Kodak back in 2000. We had/have any number of sophisticated ways of modeling parameters based upon previous research- but it wasn't called data mining.

One of the companies that has supplied hardware (or is known in the industry to do so) is PQS- http://www.pqs-chem.com/. They 'sell' hardware and software, but their software is pretty darn slick for setting up large jobs.

Since I did mostly dye research, I'm supposing the big difference is these are more interested in metalic properties than what we were- light, colour, mp, etc- all things that might be useful for film or OLEDs.

But still, if it's getting positive press, maybe it's time to put it back on the resume...

Re:Lame name.

[shadowbearer]

  So wouldn't patents on methods in data mining be the same thing as patenting mathematical methods, specifically stastistical methods?

  (It's an honest question)

SB