Artificial intelligence is all the rage, but how much do we know about it? Many applications or products are presented as artificial intelligence, but it is not very clear how far that term covers. There is no doubt that it is a complex term to define. In this post we tell you a little more about AI, its scope and its limitations.

What is AI?

The term artificial intelligence was adopted in 1956, but it has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage. Artificial intelligence could be defined as the ability of a computer or a machine to think by itself and to simulate the behaviour of a human mind.

This leads us to wonder how smart machines can get today? Can machines be smarter than humans? At the moment, although carrying out complex mathematical calculations, which could be difficult for a person, is simple for a machine, other daily actions, motor and perceptual skills, are really difficult to carry out by a machine.

All these questions have led to the creation of two terms that differentiate between the type of intelligence that allows us to carry out daily tasks and that resembles the human mind and the intelligence that allows us to carry out specific tasks based on learning from real data.

Strong intelligence vs weak intelligence

Strong intelligence is that which refers to machines that can perform intellectual activities just like human beings. This is still fiction and we have only seen it in the cinema. People are capable of reasoning, planning, solving problems, thinking abstractly, and machines are not yet at that level of intelligence since they are not capable of performing all these actions.

Weak intelligence is the concept we now know as artificial intelligence and it is the artificial intelligence that is currently being developed. AI specializes only in one task; machines can only perform the tasks for which they were programmed. This does not mean that artificial intelligence is not useful, on the contrary, thanks to it, problems that until now would have been unthinkable have been solved. Within weak intelligence, we can consider applications such as image or character recognition, voice recognition or autonomous driving systems.

Where are the limits of AI?

As we have told you, nowadays, we are able to program a machine to carry out specific tasks with very good results, such as, for example, winning the best player in the world of Go or chess. However, a machine cannot be in a medium that it does not know (about which it has no previous data) and adapt to it. This leads us to think, what are the limits that artificial intelligence presents right now.

AI is not capable of multitasking; it is specific and can only be proficient in a single task at a time. In turn, the way to learn to perform these tasks is from real data, which needs to be stored and processed. It requires huge amounts of data to “learn”, hence the new need to collect as much data as possible, to be able to use it as training for this type of algorithm. As you can imagine, managing all this data requires very specific hardware with high processing capacity. The continuous increase in computational capacity is essential for the evolution and improvement of artificial intelligence algorithms.

With all this, the important thing is to know what are the problems are AI can help us solve.

Aplicattions of AI in industry

Although, as we have seen, artificial intelligence has limits at the moment, it is a very useful tool that allows improving and optimizing production processes, although it is also possible to apply it in education, marketing, health, etc.

AI software solutions allow dealing with large volumes of data, this is the main advantage of artificial intelligence. The treatment of this data allows us to identify trends or patterns that will be used to optimize processes and make them more efficient. Algorithms learn from this data and allow obtaining models that predict and improve behaviors. Thanks to them you can make better decisions, predict the failure of a machine or even predict the purchasing needs of potential customers. Some of the applications in which artificial intelligence is applied in the industry are:

  • Data analysis, IoT in production plants to optimize processes and increase performance.
  • Quality systems with computer vision and artificial intelligence that allow inspection of parts and verification of assemblies in a automatic.
  • Predictive maintenance, uses artificial intelligence algorithms to anticipate possible incidents or failures, based on the historical data of a machine.
  • With robotics, artificial intelligence makes applications more flexible, allowing interaction between operators, components and robots. It enables robots to make decisions based on interaction with their environment.

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