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Some Articles that Explain Machine Learning

Here are a few articles that will explain AI in detail. There is so much misinformation out there but these are articles will explain the nuts and bolts of AI.




What is machine learning? Everything you need to know

This guide explains what machine learning is, how it is related to artificial intelligence, how it works and why it matters.


Click for ZDNET article

Written by Nick Heath, Contributor on Dec. 16, 2020

What is the difference between AI and machine learning?
Machine learning may have enjoyed enormous success of late, but it is just one method for achieving artificial intelligence.
At the birth of the field of AI in the 1950s, AI was defined as any machine capable of performing a task that would typically require human intelligence.
AI systems will generally demonstrate at least some of the following traits: planning, learning, reasoning, problem solving, knowledge representation, perception, motion, and manipulation and, to a lesser extent, social intelligence and creativity.
Alongside machine learning, there are various other approaches used to build AI systems, including evolutionary computation, where algorithms undergo random mutations and combinations between generations in an attempt to "evolve" optimal solutions, and expert systems, where computers are programmed with rules that allow them to mimic the behavior of a human expert in a specific domain, for example an autopilot system flying a plane.



Computers Already Learn From Us. But Can They Teach Themselves?

Click for this New York Times Article


By Craig S. Smith Published April 8, 2020Updated July 16, 2021


This article is part of our latest Artificial Intelligence special report, which focuses on how the technology continues to evolve and affect our lives. Artificial intelligence seems to be everywhere, but what we are really witnessing is a supervised-learning revolution: We teach computers to see patterns, much as we teach children to read. But the future of A.I. depends on computer systems that learn on their own, without supervision, researchers say.
When a mother points to a dog and tells her baby, “Look at the doggy,” the child learns what to call the furry four-legged friends. That is supervised learning. But when that baby stands and stumbles, again and again, until she can walk, that is something else.
Computers are the same. Just as humans learn mostly through observation or trial and error, computers will have to go beyond supervised learning to reach the holy grail of human-level intelligence.
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