Machine learning, artificial intelligence (AI), semantic technology and natural language processing (NLP) often get confused with one another and that is understandable as they are in the same “family”. Predictive Analytics World brought this news to us in their article, “Ten Things Everyone Should Know About Machine Learning.”
The author of the article provides a few tips to help you understand, and better yet, explain the differences among these technological functions. There is far more to machine learning than can be explained in a top-10 list, but hopefully it will help the non-experts.
Machine learning may not be as sexy sounding as artificial intelligence, but it means learning from data. Artificial intelligence is intelligence exhibited by machines, rather than humans.
The phrase “garbage in, garbage out” predates machine learning, but it aptly characterizes a key limitation of machine learning. Machine learning can only discover patterns that are present in your training data.
On a lighter note (I think), AI is not going to become self-aware, rise up, and destroy humanity. We should be inspired by science fiction, but not so credulous that we mistake it for reality.
As a wise colleague said, “Artificial intelligence is not magic. In fact, it is very easy to produce stupidity instead of intelligence by overlooking any of the precautions mentioned in the article.”
Melody K. Smith
Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.
