Tuesday, January 10, 2012

What is Elementary?

What is "machine learning"?
Machine learning is when a computer has a large enough and reliable enough basic set of data and examples that it can determine mathematically what a newly introduced stimulus is.

How did the IBM team employ that concept in the development of Watson's AI? What advantage did that provide over previous attempts at "intelligence"?
The machine learning was used as the basis of the ability to answer: a huge amount of old jeopardy questions, along with saved files of databases, allows Watson to take a question and reference it to all the documents in his memory, then statistically determine which keywords are important, and what the correct final answer is. This allowed Watson to react to new questions by determining the correct formulas and algorithms to find an answer.


I've often mentioned the term "Empirical Scepticism". What does that mean? How does that relate to the concept of Machine Learning? How does this relate to your life?
Empirical skepticism is separating true fact from opinion. This means that whenever we receive information, even if we feel it is from a reliable source, it probably has the feelings of an individual externally effecting it. Machine learning's strategy of intelligence retrieval seems to be a way to overcome this: by examining so much evidence, it is possible to determine only the truest of true facts about any given thing.

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