AI, or artificial intelligence, is a broad field of computer science that refers to the creation of technology that is capable of learning, problem-solving, and input interpretation.
ML, or “machine learning,” refers to the application of that AI.
The term AI was first used in 1956 at a lecture by John McCarthy, a computer scientist considered one of the field’s forefathers. McCarthy would later define AI in 2004, stating that AI is “the science and engineering of making intelligent machines, especially intelligent computer programs.”
While the field of AI is extremely diverse and complex, it can sometimes help to understand what the field is fundamentally trying to achieve. That is computers that are capable of solving problems.
Generally speaking, AI can be broken down into two categories: “weak AI” and “strong AI.”
Strong AI refers to a specific subtype of artificial intelligence that has been designed to interpret vast data sets and formulate complex responses. This is often referred to as “artificial general intelligence” (AGI) or “artificial super-intelligence.” (ASI)
This type of AI is much closer to what we imagine when we imagine science fiction AI. These systems hope to be able to interpret complex problems, apply complex data sets, and truly create intelligent solutions.
While the field of artificial intelligence has advanced a lot in the last few years, AGIs or ASIs are still largely the stuff of science fiction, and we remain a long way away from HAL.
Weak AI is the more common and grounded version of artificial intelligence and is already a part of many people’s lives.
This type of artificial intelligence is sometimes called “narrow AI,” in that the intelligence within the software has a very narrow range of information from which to solve problems. Often, “narrow AI” is used as a way to refer to the vast majority of programs that can solve and perform very simple tasks but cannot innovate or even emulate consciousness.
An example of these kinds of AI is the home-based Alexa or Siri. Still very clever in its linguistic abilities and capacity to form answers to questions, but limited in terms of application.