AI vs. machine learning vs. deep learning: Key differences Posted on : Apr 23 - 2020

AI terms are often used interchangeably, but they are not the same. Understand the difference between artificial intelligence, machine learning and deep learning.

Artificial intelligence, machine learning and deep learning are popular terms in enterprise IT, and sometimes used interchangeably, particularly when companies are trying to market their products. The terms, however, are not synonymous -- there are important distinctions. Here is a primer on artificial intelligence vs. machine learning vs. deep learning.

What is artificial intelligence?

The term AI has been around since the 1950s. In short, it depicts our struggle to build machines that can challenge what made humans the dominant lifeform on the planet: our intelligence. However, defining "intelligence" has turned out to be rather tricky, because what we perceive as intelligent changes over time.

Early AIs were rule-based computer programs that could solve somewhat complex problems. Instead of hardcoding every decision the software was supposed to make, the program was divided into a knowledge base and an inference engine. Developers would fill out the knowledge base with facts, and the inference engine would then query those facts to arrive at results.

But this type of AI  was limited, particularly as it leaned heavily on human input. Rule-based systems lack the flexibility to learn and evolve and are hardly considered intelligent anymore.

Modern AI algorithms are capable of learning from historical data, which makes them usable for an array of solutions such as robotics, self-driving cars, power grid optimization and natural language understanding.

While AI sometimes yields superhuman performance in these fields, we still have a long way to go before AI can actually compete with human intelligence.

For now, there is no AI that can learn the way humans do, that is, with just a few examples. AI needs to be trained on mountains of data to understand any topic. We still don't have algorithms that are capable of transferring their understanding of one domain to another. For instance, if we learn a game such as StarCraft, we can play StarCraft II just as quickly. But for AI, it's a whole new world and it must learn each game from scratch.

Human intelligence also possesses the ability to link meanings. For instance, consider the word "human." We can identify humans in pictures and videos, and AI has also gained that capability. But we also know what we should anticipate from humans: We never expect a human to have four wheels and emit carbon like a car. Yet, there is no AI that can even tell what was wrong with the sentence I just wrote. View More