Author: Marcelo Hernandez

A seasoned tech enthusiast with over 35 years of experience in the IT industry, spanning more than seven countries across two continents. With a strong foundation in Data Warehousing and Business Intelligence, and hands-on exposure to the evolving realms of Data Science and AI, Marcelo brings a global perspective and deep technical insight to every post. Passionate about innovation, transformation, and the stories behind the code.

As automation dismantles traditional labor markets, the future of economic survival may hinge not on working but on ownership. By acquiring AI Units of Work—the digital engines replacing jobs—individuals can reclaim lost wages and preserve purchasing power. This radical shift reframes workers as investors in machine labor, a dystopian yet practical strategy for stability in an economy dominated by artificial intelligence.

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In the not-so-distant past, the idea of having a digital friend, confidant, or even lover existed only in science fiction. Today, AI companions are marketed as chatbots, avatars, and virtual assistants, blurring the line between software utility and simulated emotional presence. But the question remains: are they real, or merely illusions of companionship wrapped in code?

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Artificial intelligence is no longer just about crunching numbers, recognizing patterns, or generating text. Increasingly, AI systems are being designed to detect, interpret, and respond to human emotions—a field often called affective computing or emotion-aware AI. From customer service chatbots that “sense” frustration, to cars that monitor driver fatigue, to education platforms that adapt to student engagement, the ability of machines to read emotions promises powerful new capabilities.

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Cognitive computing—broadly referring to AI systems designed to simulate aspects of human thought such as learning, reasoning, and decision-making—has advanced significantly in recent years. However, it also carries fundamental limitations that arise from its lack of true real-world perception and incomplete grasp of human nuance

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