21–30 of 106 posts
You could try to find a good pilot customer who has valuable data and is willing to work with you to adapt the algorithm to their particular problem. What you want as an outcome is a story like this: "Math Whizzes Turbocharge An Online Retailer's Sales" ( http://www.informationweek.com/showArticle.jhtml?articleID=2... )
I'll put it this way: if you can consistently beat the market by a few percentage points, you can be a billionaire.
Build a public web API to use your technology for a fee. Make it dead simple to incorporate AI into any application.
Thats an awesome idea. Integration is pretty simple, as you can use it almost as a drop in replacement for a backprop neural network.
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.
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Thats an awesome idea. Integration is pretty simple, as you can use it almost as a drop in replacement for a backprop neural network.
Uhm? The latency as a public api will render it useless for most applications.
Netflix challenge? No recurring revenue, but, hey, a million dollars. You'll have to disclose the algorithm to accept the prize.
Thats the problem disclosing the algorithm is something I'd rather avoid. I don't mind sharing it with a company for a licensing fee as long as I don't have to public domain it.
You're really wasting your time with the stock market though. Technical analysis is just silly.
I don't believe you.
I don't mind being tested.
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Uhm? The latency as a public api will render it useless for most applications.
Most AI application aren't realtime (although some of them in the chemical industry for example are ). A doctor doesn't care if his cancer diagnosis takes another 20 milliseconds so long as its a bit more accurate. And a bank trying to analyze if a credit card transaction is fraud or not doesn't care about the short delays either.
I'm not sure I buy the web service idea, either: wouldn't typical applications require a lot of input data (training set + test set) in order to be effective? Uploading all that data could be annoying, compared with just running the algorithm locally at the customer's site.
Earlier quoted context omitted.
Uhm? The latency as a public api will render it useless for most applications.
Most AI application aren't realtime (although some of them in the chemical industry for example are ). A doctor doesn't care if his cancer diagnosis takes another 20 milliseconds so long as its a bit more accurate. 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.