{"id":170281,"date":"2023-09-09T09:05:51","date_gmt":"2023-09-09T08:05:51","guid":{"rendered":"https:\/\/liora.io\/en\/?p=170281"},"modified":"2026-02-06T08:59:26","modified_gmt":"2026-02-06T07:59:26","slug":"learn-ai-everything-you-need-to-know","status":"publish","type":"post","link":"https:\/\/liora.io\/en\/learn-ai-everything-you-need-to-know","title":{"rendered":"Learn AI: Everything you need to know"},"content":{"rendered":"

Learn AI: An artificial intelligence, or AI, is a program that seeks to mimic human intelligence through computational algorithms. Its creation enables computers to perform operations and think like a human being. Since 2010, the development of artificial intelligence has been accelerated by big data. In this article, discover everything there is to know about artificial intelligence.<\/strong><\/p>\n

The history of artificial intelligence and how to learn AI<\/h3>\n

The history of learning AI<\/strong> begins in 1943 with the publication of the article “A Logical Calculus of Ideas Immanent in Nervous Activity” by Warren McCullough and Walter Pitts.<\/p>\n

In this document, scientists present the first mathematical model for creating a neural network.<\/p>\n

In 1950, Snarc, the first neural network computer, was created by two Harvard students: Marvin Minsky and Dean Edmonds.<\/p>\n

The same year, Alan Turing published the Turing Test, which is still used to evaluate AIs.<\/p>\n

From this test, the foundations of artificial intelligence<\/strong> emerged, with its vision and goals being to replicate or simulate human intelligence in machines.<\/p>\n

However, it wasn’t until 1956 that the term “learn AI<\/strong>” was first mentioned during the “Dartmouth Summer Research Project on Artificial Intelligence” conference organized by John McCarthy. During this event, researchers presented the goals and vision of AI. Many consider this conference to be the true birth of artificial intelligence as it is known today.<\/p>\n

Several years passed, and work on artificial intelligence continued. In 1959, Arthur Samuel coined the term “Machine Learning”<\/a> while working at IBM. In 1989, the Frenchman Yann Lecun developed the first neural network capable of recognizing handwritten digits, laying the foundation for the development of deep learning.<\/a><\/p>\n

Ten years later, in 1997, a major event marked the history of AI. IBM’s Deep Blue system triumphed over the world chess champion, Gary Kasparov.<\/p>\n

For the first time, a machine had defeated a human.<\/p>\n


\nDiscover our courses
\n<\/a><\/p>\n

What types of artificial intelligence?<\/h3>\n

Thanks to the development of learning AI and discovered technologies like deep learning and machine learning<\/a>, researchers agree on discerning three types of artificial intelligence:<\/p>\n

Learn AI and General Artificial Intelligence<\/h2>\n

General or deep AI<\/strong> is an artificial intelligence capable of performing any cognitive task just as a human or animal would. Still considered hypothetical, some scientists are speculating about GPT-4<\/strong> and the probability that it might represent a preliminary form of general AI. To support this idea, a significant majority of AI researchers believe that humanity possesses the technology needed to create general AI, especially through neural networks.<\/p>\n

Strong Artificial Intelligence<\/h2>\n

We refer to strong AI or superintelligence<\/strong> when a model references philosophical knowledge and exhibits signs of its own consciousness. While resembling a science fiction scenario, AI researchers nonetheless believe that strong AI is currently impossible to create.<\/p>\n

For them, the concept of consciousness and emotions cannot emerge within mathematical systems that manipulate and respond with symbols and calculations.<\/p>\n

Weak Artificial Intelligence<\/h2>\n

The final distinction in artificial intelligence is weak or narrow AI<\/a>. This AI system is capable of performing a single task almost perfectly without the need for human supervision. It is the most widely used and created model to expedite various processes in different sectors of activity.<\/p>\n

Learn AI: What is the purpose of Artificial Intelligence?<\/h3>\n

Artificial intelligence<\/strong> has transformed numerous sectors, including medicine, sciences, finance, automotive, and many others.<\/p>\n

In medicine, AI<\/strong> is used for disease diagnosis and prediction, enabling early detection and swift intervention.<\/p>\n

It is also applied in pharmaceutical research to accelerate drug discovery and improve treatments.<\/p>\n

In scientific research, AI analyzes<\/strong> vast amounts of data and makes discoveries in fields such as astrophysics, genomics, biology, and chemistry. It accelerates scientific progress and opens up new research possibilities.<\/p>\n

With the arrival of GPT-3.5 in November 2022,<\/strong> a powerful language model, the potential of artificial intelligence has multiplied. Now, AI is also used in creative domains such as text generation, image generation, and even in the audiovisual field, thanks to applications like VALL-E, Midjouney, and GEN-2.<\/p>\n


\nDeep Learning Course
\n<\/a><\/p>\n

What are the dangers of Artificial Intelligence?<\/h3>\n

Faced with the massive changes brought about by artificial intelligence, many people are also beginning to question the potential dangers it could pose. Some CEOs, like Sam Altman, the CEO of Open AI<\/strong>, and researchers consider AI as dangerous as the nuclear bomb, and they believe that AI<\/a> could become a threat to humanity.<\/p>\n

Due to its learning and evolving capabilities, AI could one day surpass humans in certain domains and potentially replace them. This is suggested by a study from Goldman Sachs, which claims that over the next few years, more than 300 million jobs could disappear. At the same time, people are concerned about their privacy and personal data.<\/a><\/p>\n

Does AI, in its quest for improvement, gain access to everyone’s personal data under the guise of technological and economic development? In response to this potential catastrophic scenario, Europe and companies like Google are implementing regulations within their systems or through legislation like the AI Act.<\/strong><\/p>\n

However, AI is not the sole potential danger; it also depends on how it is used. Even seemingly harmless AI could be maliciously exploited. This is evident with the rise of “DeepFakes”: fake videos created using Deep Learning<\/a> to depict a person in a compromising situation.<\/p>\n

Artificial intelligence will continue to develop rapidly in the coming years. It is now humanity’s responsibility to regulate it and ensure the development of a healthy and ethical AI.<\/p>\n