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Ideas to monetize new artifical intelligence

news.ycombinator.com

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Ideas to monetize new artifical intelligence

#1
I've developed a new machine learning algorithm that understands the relationship between its inputs better and outperforms existing algorithms on almost every test I've done, and I'm looking for new ideas as to how to monetize it. Already working on trading commodities with it, which is progressing but still hasn't reached the point where its a money making scheme. Also working on some CAD (computer assisted diagnosis) applications.

Any ideas?

Re: Ideas to monetize new artifical intelligence

#4
Patent and publish it. CAD is not limited by the algorithm so much as a lack new problems. However, if you can generate a little buzz you can become a consultant / start a consultant company.

PS: Many machine learning systems can trade off accuracy for efficiency so you might look into increasing efficiency vs. accuracy for some existing application.

Re: Ideas to monetize new artifical intelligence

#7
I am a tech commercialization consultant for some of the crazy stuff that comes out of the Small Business Innovation Research (SBIR) program. Scientists and engineers make all this cool stuff, but they don't really know what to do with it, and how to package and sell it. That's where I come in.

E-mail me and maybe we can figure out what it would be good for. I'm thinking you should patent the technology, show proof of concept comparison tests, and shop application specific licenses around.

Re: Ideas to monetize new artifical intelligence

#9

How about _proving_ that the algorithm works first. Prove it on something simple and verifiable like symbolic addition http://news.ycombinator.com/item?id=75439 . Here I go again with my own agenda, sorry...

This is a classic example of the saying "When the only tool you have is a hammer, every problem looks like a nail" To a guy with a spam filter, everything looks like mail to be filtered. (it was a cool & very interesting experiment non the less )

Symbolic addition is exactly the wrong kind of problem for this algorithm as the symbols don't have any relationships with each other which is exactly the insight this algorithm adds, and which almost every other dataset has.

I've proven that the algorithm works to my complete satisfaction. I've tested it almost every dataset in UCI machine learning repository and it outperforms the best published results on almost all of them. I've tested it on the data from the KDD 2006 cup a contest in the KDD conference whose goal was to identify Pulmonary Embolism based on data generated from CT scans and it out scored the cup winners by a 50% margin.

I know the algorithm works, I am just not sure how to monetize it...

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