By Richard Arneson
His name might not carry the same weight as Abner Doubleday’s, who is credited with inventing baseball in the early- to mid-1800’s, but Walter Camp is the person widely regarded as the creator of America’s most popular current sport―football. It’s impossible to know exactly what Camp envisioned for football, his amalgamation of soccer and rugby that he invented roughly fifty (50) years after Doubleday’s, but this much is certain―he never imagined it would be used as an analogy to describe Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL).
Artificial Intelligence―the game
Given the fact that it came before ML, which came before DL, AI, like football, has no predecessor.To borrow from mathematics, AI is the superset of subsets ML and DL. And like Camp’s invention, pinpointing the creation date of AI is next to impossible. While the use of the name Artificial Intelligence is widely attributed to John McCarthy, who used it during a Dartmouth academic conference in 1956, its actual invention is up for debate.
However, here’s what is widely agreed upon―AI sets out to utilize a machine to mimic human thinking. For years―decades in fact―the public’s understanding of AI took was largely the result of science fiction writers, who penned, among countless other sci-fi films, 2001: A Space Odyssey, Westworld and Bladerunner. Presently, AI is taking it on the chin because it’s feared that it will take jobs from people and that those smart devices are covertly gathering way, way too much information about its users.
Today AI is utilized by too many applications and appliances to name, but the most common are Netflix, Amazon’s Alexa, Apple’s Siri and Nest, the learning thermostat that Google purchased four (4) years ago. While some might argue that those hardly represent the benefits of AI, there are certainly examples of how it can deliver to humans a better qualify of life. For instance, there are new AI platforms capable of providing health advice, including specific diagnoses, to people who can’t afford medical care or access medical facilities.
Machine Learning―the players and the plays they run
Machine Learning (ML) takes AI to the next level. It’s not uncommon to hear ML and AI used interchangeably―they shouldn’t, they’re different. Football isn’t players, but the game in which they play. While AI addresses “If A happens, then B needs to happen”, ML, instead, determines that “If A happens, then I’ll learn what should happen next.” Yes, the machine, as the name suggests, thinks. In the case of Amazon.com, ML algorithms gather the type of movie, book or song that you enjoy, then look to see what others who share your same interests are into.
Deep Learning―the dekes, fakes and cuts
To remain with the football analogy, if AI is the game and ML represents the thinking players utilize to carry out the plays, DL is what allows a player to improvise in the event a defender stands between them and the goal line. DL attempts to enable machines to draw conclusions. Deep Learning is a type of Machine Learning, just its next evolution.
In the event this comes up in Trivial Pursuit, the word Deep in DL is borrowed from deep artificial neuron networks, which is another way of referencing DL. When, or if, you ever hear deep artificial neuron networks, you’ve just heard a synonym for DL. And in case you’re wondering, neuron refers to the interactions and interconnections that exist between the neurons in the human brain. Yes, the thinking human brain.
The best part about AI, ML and DL
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