The Difference Between Artificial Intelligence, Machine Learning, and Deep Learning - Deepstash
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Artificial Intelligence

First coined in 1956 by John McCarthy, AI involves machines that can perform tasks that are characteristic of human intelligence.

  • General AI would have all of the characteristics of human intelligence, including the capacities mentioned above. 
  • Narrow AI exhibits some facet (s) of human intelligence, and can do that facet (s) extremely well, but is lacking in other areas. A machine that’s great at recognizing images, but nothing else, would be an example of narrow AI

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Machine Learning

At its core, machine learning is simply a way of achieving AI. Arthur Samuel coined the phrase not too long after AI, in 1959, defining it as, “the ability to learn without being explicitly programmed.”

So instead of hard-coding software routines with specific instructions to accomplish a particular task, machine learning is a way of “training” an algorithm so that it can learn how. “Training” involves feeding huge amounts of data to the algorithm and allowing the algorithm to adjust itself and improve.

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Deep Learning

Deep learning is one of many approaches to machine learning. Other approaches include decision tree learning, inductive logic programming, clustering, reinforcement learning, and Bayesian networks, among others.

Deep learning was inspired by the structure and function of the brain, namely the interconnecting of many neurons. Artificial Neural Networks (ANNs) are algorithms that mimic the biological structure of the brain.

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AI and IoT

  • Machine learning and deep learning have led to huge leaps for AI in recent years. As mentioned above, machine learning and deep learning require massive amounts of data to work, and this data is being collected by the billions of sensors that are continuing to come online in the Internet of Things. IoT makes better AI.
  • Improving AI will also drive the adoption of the Internet of Things, creating a virtuous cycle in which both areas will accelerate drastically. That’s because AI makes IoT useful.

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