It is likely that you are somewhat exaggerating the role of modern AI in the development of society and technology. Yes, modern models demonstrate progress, but it is associated with colossal costs and unjustified expectations. Many are still in another euphoria, but the voices of pessimists are already being heard. We are all delighted with the generative abilities of AI, but the reliability of the answers remains a problem. There is a conceptual drawback of generative models, which can be characterized as an entropy gap. The essence of this phenomenon is that statistical learning, which underlies these models, allows generating only the most probable texts. However, new, creative ideas have a low probability and, therefore, will never be generated by AI. Attempts to diversify model responses are associated with a decrease in the probability of the relationship of concepts (tokens) and lead to false generations or even "hallucinations" of the model. We can say that statistical learning, as a concept, has already exhausted its potential. The use of heuristic methods or multi-agent approaches may only lead to temporary improvements, but they do not solve the fundamental problems caused by information entropy.

Луценко, Е. В. Революция начала XXI века в искусственном интеллекте: глубинные механизмы и перспективы / Е. В. Луценко, Н. С. Головин. - Изд. 2, - Краснодар : Кубанский государственный аграрный университет им. И.Т. Трубилина, 2024. – 495 с. – DOI 10.13140/RG.2.2.17056.56321. – EDN OMIPIL. https://www.researchgate.net/publication/378138050

Луценко, Е. В. Системы / Е. В. Луценко, Н. С. Головин. – Краснодар : Виртуальный Центр системно-когнитивных исследований "Эйдос" , 2024. – 518 с. – DOI 10.13140/RG.2.2.22863.09123.– EDN: INUTJL. https://www.researchgate.net/publication/379654902

"AI Unleashed: The Evolution of Machines That Think" explores the remarkable journey of artificial intelligence from rudimentary algorithms to sophisticated systems capable of independent reasoning and learning. Initially designed for specific tasks, modern AI now employs deep learning and neural networks, allowing machines to analyze vast amounts of data, recognize patterns, and make decisions with increasing autonomy. This evolution has transformed industries, enhancing everything from healthcare diagnostics to autonomous vehicles, while also raising ethical questions about the implications of machines that can think and act on their own. As AI continues to advance, it challenges our understanding of intelligence and prompts us to reconsider the role of technology in our lives.