For many people, artificial intelligence does not represent a promise of progress, but a source of restlessness and confusion. The accelerated implementation of intelligent systems in areas such as education, employment or health has aroused understandable doubts about their impact on daily life. Often, The lack of clarity about the functioning of these algorithms generates fear of being replaced, monitored or evaluated by machines. This sense of distrust is aggravated by a digital gap that is not only technological, but also cultural and educational. Those who do not have adequate training on the responsible use of these tools are usually excluded or surpassed by a technology that do not fully understand.
The improper use that some companies or individuals make of artificial intelligence, such as the propagation of misinformation, image manipulation or the creation of profiles with biases, has contributed to creating a wrong image of these technologies. Ideas such as artificial intelligence has its own conscience or that is destined to dominate humanity reinforce a rejection that, in many cases, arises more of ignorance than real experiences. Before this panorama, Experts insist on the importance of promoting a critical digital education that allows society to understand what it can and what artificial intelligence cannot do.
And this ignorance, propagated among the detractors of technology, It arises in part because of the inability to understand the functioning of the same. Being something completely unknown, the trend points to the contempt, but, once the foundations on him are known first hand. This happens with AI, while his arrival years ago stretched as the end of the world, in our days it is something much closer and accessible.
How does artificial intelligence collect information?
Diego Halffter, an artificial intelligence specialist, gives an answer to the issue that many wonder, admitting that the key is in the “vector base”. “It is not like a normal database, text is not saved here as we normally write, but as vectors,” says the expert. These elements are lists of numbers that represent the text in question. To exemplify it, Halffter exposes an assumption: “Imagine that you have a list with one hundred internal manuals of your company. Each of the text segments ends up becoming a vector “, he indicates.
In this way, once the user seeks something by asking a question or any incident that he wants to solve, the AI ends up answering with another vector. “Look for the closest paragraphs in meaning, although in the end do not use the same words“, emphasize. Therefore, this is how this kind of systems work, as well as others that combine intelligent models with real information. The information search engine moves by numbers covered with vectors to solve the words we formulate. Therefore, sometimes artificial intelligence does not come to understand 100% the nature of our question, since it associates it to another.
Other uses of vector bases
Vector bases are not only used in terms of AI, since they are fundamental in Graphic computing and video gameswhere they allow to represent and transform objects into three -dimensional environments. Thanks to them, it is possible to make rotations, movements and visual effects with precision. Also in telecommunications, they are used to process signals through combinations of base functions, facilitating their compression and efficient transmission.
In data science, vector bases allow simplifying complex sets of information. Techniques such as the analysis of Main components reduce dimensions maintaining key patterns. In addition, in semantic search systems, they help compare texts through the distance between vectors, offering more precise results.