Nowadays, new technologies are giving way to a technological impulse called Big Data, which provides information in large amounts. Volumes, to a large Speed, with a large Variety and Variability. The market has entered the era of Digital Transformation. We find ourselves, among others, with a discipline that is in widespread demand in practically all sectors of the economy. It is the IA, o Artificial Intelligence.
Since the 1950s, Artificial Intelligence (IA) has been a science used mainly for behavioral analysis and predictions, in its beginnings at the laboratory level. After all the evolution that has taken place, we can say that today we can say that today IA means analyzing the massive amount of information provided by the new technologies (Big Data) and returning it with an accurate and accurate actionable intelligence for various purposes. Therefore, the Artificial intelligence and robotics are two of the fastest growing factors in 2017.
The importance of AI in the industrial sector
But the great contribution, today, in the field of IA is the ability to apprenticeship. An algorithm is being developed that allows us to ask the self-learning machines, We have come a long way in the ability of machines to learn from their own experience (self-programming) from the data they ingest, without having to program rules for the infinite combinations of data provided by the new technological capabilities of the real world. We have come a long way in the ability of machines to learn from their own experience (self-programming) from the data they ingest. This discipline is called Machine Learning (ML, also known as machine learning), and it is a sub-field of IA.
In short, new technologies (Big Data, IoT, Omnichannel, etc.) have allowed us to develop a new discipline (ML) that allows machines to learn automatically, through learning algorithms. Learning algorithms have a behavior similar to that used by nature to develop learning in children: behaviors that are rewarded tend to increase their probability of occurrence, while behaviors that are punished tend to disappear. It is about supervised learning: “what is right - what is wrong”. At Machine Learning, This supervision is performed by algorithmic experts, who spend a great deal of time training the machines; generalize behaviors based on information they provide in the form of an example.
Machines and learning without humans
Machines are learning to “behave”, to detect objects, to interpret words. Their market penetration is growing at high speed thanks to new dissemination channels, such as Cloud Systems: Amazon Machine Learning or Azure Machine Learning.
Advances are unstoppable (in algorithmic, Big Data, IoT, etc.) and supervised learning is being replaced by the automatic learningAlgorithms learn without human intervention. A major breakthrough called Deep Learning (DL, a branch of the Machine Learning), allows us to get closer and closer to the way the human nervous system works.
The algorithms of Deep Learning are capable of processing millions of unstructured data and establishing almost imperceptible connections between them. This is what happens, for example, in agricultural plantations where the aim is to optimize the production method. Agricultural robots are capable of analyzing the crop and monitoring its growth, taking into account variables such as the amount of fertilizer needed, the liters of water required at any given moment or whether the plantation will be able to overcome the pests in the area.
Controlling electricity and water consumption Deep Learning provides many advantages, such as:
- Creates much more intelligent systems, because it analyzes large amounts of data and establishes almost imperceptible relationships between them.
- Much faster, because it analyzes and responds in seconds.
- Much more accurate, because it always finds the best solution, with the minimum possible error.
- Much cheaper than consulting external sources or developing it manually, with fewer errors being made.
- Automatically learns from your data, improves predictions and gives you the answer you are looking for, easily.
Machine learning will gradually incorporate new functions close to human intelligence, e.g. reasoning, motivation, emotion, etc.
*Summary based on the article by Dr. Raúl Arrabales Moreno, Accenture Advanced Analytics and SOLVER Machine Learning S.L. articles.