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Artificial IntelligenceFor all of us artificial intelligence fanboys, Stanford University has something upcoming that will make us all drool. Beginning this fall, Stanford University will be adding a free class called “Introduction to Artificial Intelligence” to its list of free online courses. I’ve gone thru several of the free online courses and have been impressed with everyone of them. So, if this class is anything even close to what the other courses have to offer, I know we’ll all benefit from it. Besides, it’s FREE! So, if you’re interested in getting into the A.I. field, you no longer have any excuses. For more information, head on over to http://www.ai-class.com/. Registration hasn’t begun yet. But, you can enter your name and email address to be contacted when registration becomes available.

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Code Project LogoFrom time to time I like to find an existing project on the web and try my best to either improve the app or to make a better version of my own. I’ve even hosted contests in the past for developers to do the same. During those competitions, I’m almost always asked where do I find applications that are worth checking out.

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The Lights in the TunnelBeing the artificial intelligence and automation fan-boy that I am, I was excited to find that you can now get a copy of Martin Ford’s book “The Light in the Tunnel” for free. “The Light in the Tunnel” is a book that discusses the growing capability of artificial intelligence and robotics to replace workers at all levels of the food chain. It even goes into how a sharp rise in automation may mean for the global economy. Martin Ford believes that without drastic adjustments to the way the market is structured, automation could bring the whole system crumbling down. As a self-proclaimed artificial intelligence researcher, I enjoy reading things such as “The Light in the Tunnel” as they shine light on some of the questions and concerns that plague the AI industry.

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Machine LearningWith the Heritage Health Prize beginning last night, the majority of my time is going to be spent on that for a while. If any of you are participating in the $3 million prize contest, I want to wish you all the best of luck. I know when I began working in the machine learning industry, one of the biggest problems I faced was how and where to obtain a good collection of data to design and test with. For those of you that are not (and those that are) participating in the contest and would like to do some work with algorithms, machine learning, and neural networks and are looking for some good datasets for developing and testing with, I want to share a few of my favorites with you now.

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Another Step Closer to AI

On January 5, 2011, in Artificial Intelligence, by LuCuS

As you already know, I’m big into artificial intelligence research. I believe that by creating an “intelligent” system that is smarter than us, we could have it in turn teach us, turning the student into the teacher. We could also use it for experimentation instead of experimenting on living beings. This morning, I came across 2 articles that I wanted to share with you.

The first article is about a scientist named Henry Markram who is attempting to create a true artificial brain out of silicon, gold, and copper. He says that his artificial mind will be ready to go by 2018. However, his biggest hurdle right now is processing power. Backed by investors like the Swiss government and IBM, Markram is using an IBM Blue Gene supercomputer to do the number crunching. Unfortunately, he says that even with a current fund of around 200 million, his supercomputer still isn’t sufficient enough.

That’s where the second article comes in. Researches at MIT have created a 1000 core processor that is truely 1000x faster than a processor with only 1 core. The processor is faster because it is actually 1% less accurate than the traditional processors. Existing processors require that every individual core must be capable of communicating with all other cores. The MIT processor works by having each core only talk to nearby cores, causing the processor to be less accurate, but significantly faster. Since artificial intelligence isn’t 100% accurate anyways (and never will be), I think that this kind of processor could give researchers the computing power we need to power a true artificial intelligence system.

You can read the full articles here:

Professor Henry Markram
http://www.dailymail.co.uk/sciencetech/article-1240410/The-real-Frankenstein-experiment-One-mans-mission-create-living-mind-inside-machine.html

MIT
http://web.mit.edu/newsoffice/2010/fuzzy-logic-0103.html

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