Difference Between Artificial Intelligence (AI) And Machine Learning
Let’s clear out what each of them means and what’s the difference between them
With exceptional emergence and implementation of big data and analytics, both Artificial intelligence (AI) and machine learning are hot buzzwords right now. We talk about artificial intelligence, robots, and machine learning as if they’re coming soon, or are just some tech pipe dream. They’re not. They’re here today.
While these two terms sometimes are used interchangeably, they shouldn’t be seen as one thing. In fact there are some distinct differences.
Artificial Intelligence is usually divided into two categories. Weak, and Strong AI. Weak AI is a system or computer program that can solve a narrow set of problems with some level of perceived intelligence. An example could be a system that plays chess or Jeopardy! at or above human expert level, or that can categorize images of different kinds of objects really well. There are plenty of examples of this today.
The other category, Strong AI, is a system that is of superhuman intelligence in a broad range of tasks, or ultimately, in every aspect. When will the machines have this level of intelligence? Some believe it might be possible in 20–30 years time, others say 50, and some say it will not be achievable in less than a 100 years.
On the other hand Machine learning is a type of AI where computer systems can actually learn, improve, and “evolve” when exposed to new and additional data. They don’t need to be programmed in the traditional sense. They discern new information using existing knowledge, make connections, combine ideas, and following a train of thought just as humans do.
One simple way to describe Machine Learning is letting artificially intelligent machines pick up information by themselves. It’s a bit like leaving a person alone with a set of Lego: give them the bricks and come back later to see what they come up with.
By the way, Deep learning will be discussed in detail in future posts!
The term “machine learning” was first coined by Artur Samuel, an American pioneer in computer gaming and artificial intelligence, back in 1959. Samuel defined it as: “ The Field of study that gives computers the ability to learn without being explicitly programmed”.
Machine learning lets computers recognize patterns in enormous datasets and act on them.
Artificial intelligence is a broad term that represents the general concept of machines being able to carry out smart tasks, and machine learning is a specific subset of algorithms for AI.
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