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Although artificial intelligence or related concepts such as machine learning or deep learning have been talked about for years , it has been in the last two years, and especially in 2022, when the general public has seen what we are dealing with when we talk about intelligence. artificial. And how much it can do for us . In practically any field.
But as with all new technology, it’s easy to fall for mistakes, commonplaces, or to confuse similar but not identical concepts. And one of those examples is the difficulty in discerning what is artificial intelligence and what is machine learning . Actually, they are very close to each other.
Briefly, artificial intelligence is a broader field of study that includes machine learning . What in English we know as machine learning . But machine learning is a specific subcategory within artificial intelligence. Let’s see how different they are.
Artificial intelligence versus machine learning
Wikipedia says that artificial intelligence is, in computer science , the discipline that tries to replicate and develop intelligence and its implicit processes through computers. Or put another way. It is about creating systems that can perform tasks that normally require human intelligence , such as pattern recognition, machine learning, or decision making.
For its part, machine learning or automatic learning is the subfield of computer science and a branch of artificial intelligence. Their goal, according to Wikipedia , is to develop techniques that allow computers to learn. For this, algorithms and systems are developed that can learn and improve from experience without being explicitly programmed. Machine learning is based on the idea that a system can improve its performance by acquiring knowledge from data. This is achieved through the use of specific algorithms such as supervised, unsupervised and reinforced learning.
Behind artificial intelligence is the idea of automating complex processes . We have managed to automate certain tasks and actions practically completely to the point of not needing human supervision. Or that this is minimal. But there is still a lengthy way to go in tasks that require making decisions beyond a series of previously programmed reactions.
It’s easy to confuse machine learning and artificial intelligence
In reality, confusing both concepts is easy because they are often related. For example, we may employ artificial intelligence to collect and analyze data . But precisely this AI uses algorithms and models based on machine learning that detect and interpret patterns that humans would not see or would take much longer to find.
Another similar case is that of chatbots based on natural language processing . One of the most popular last year and this one is ChatGPT . We are talking about artificial intelligence. But also machine learning. Since this AI learns as we introduce texts and interact with it .
In part, we could say that artificial intelligence solves problems based on previously introduced rules. And machine learning helps that AI evolve . Or rather, learn as you encounter new situations . Some of them were not foreseen when the algorithm or program on duty was programmed.
The part for the whole, the whole for the part
Thanks to automatic learning or machine learning we are advancing rapidly in many areas. We are already enjoying many of its benefits without knowing that they are due to this branch of artificial intelligence. For example, recommendations in music or video streaming services, recommendations in online shopping stores, text and audio translation , fraud detection, merchandise stock predictions , image recognition …
On the other hand, artificial intelligence is also part of our day to day. Virtual assistants, domestic robots, more realistic video games, data analysis, scientific research, personalized medicine, smart mobility. In short, artificial intelligence, and partly its combination with machine learning, will give much of itself in the coming years as already We have seen if we look back.
Machines, devices and applications that reason and solve problems that can be very simple but can also be complex. And through machine learning , they will learn for themselves thanks to the parameters set and the data and interactions they receive as they work for us. And here is the fine line that separates , if possible, deep learning from artificial intelligence.
