A recent overview clarifies several widespread myths about artificial intelligence. It explains that AI models process statistical patterns rather than think like humans, lack true understanding, and cannot read users' unspoken intentions. The piece also highlights that AI inherits biases from its training data and is not inherently objective. Ongoing human involvement remains essential for training, oversight, and improvement. Finally, it stresses that current AI, including large language models, is far from achieving general intelligence and should be viewed as sophisticated autocomplete tools rather than superintelligent systems. Leer más →