Artificial Intelligence Terminology You Need to Know
Artificial intelligence is a large and varied field with many sub-fields and lots of confusing terminology. But as artificial intelligence becomes more mainstream and begins to have more of a role in our day-to-day lives, it’s going to become more important to have a general understanding of it. Here are some AI terminology basics you need to know.
Artificial intelligence is actually a sub-field of computer science tasked with creating computers that can perform tasks usually relegated to humans. Computers can do many things that humans can’t but there are many things that humans can do that computers can’t, and AI is about changing that.
Weak and Strong AI
Weak AI refers to AI applications that perform a single task very well and there are already many weak AI programs out there. Strong AI is still science fiction at this point; it’s an AI system that can do virtually anything that a human could do.
The term “machine learning” is often uses interchangeably with artificial intelligence though it’s actually a sub-field of AI. Machine learning is concerned with programming machines to learn how to perform a task themselves as opposed to having to be programmed to do that task.
Natural language processing (NLP)
This is another sub-field of AI though the term is sometimes used interchangeably. NLP a branch of AI that focuses solely on language whether written or spoken. A crucial obstacle that must be overcome in developing strong AI is the inability of computers to comprehend written and spoken speech.
Deep learning is a sub-field of machine learning and is focused on programming machines to “think” in a way similar to the human brain: that is on multiple levels simultaneously.
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