Why AI Learns from Human Writing, Not Human Thought
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Artificial intelligence (AI) systems are becoming more powerful, but a new discussion asks an important question: do these machines really think? According to an article from Stuff South Africa, today's AI mostly learns from the products of thinking, such as text, articles and images that people have created. It does not learn from the thinking process itself. This difference matters for the future of machines and for the people who use them.
Large language models, the technology behind many popular AI chatbots, work by predicting which words are likely to come next. They are trained on huge amounts of written material. The article explains that newer systems, known as agentic systems, come slightly closer to real thinking. In these systems, a software "harness" surrounds the language model and runs a loop. The system produces a result, feeds that result back into itself, and then tries again. This repeated process allows the AI to check its own work and take several steps to complete a task.
However, the article suggests that these systems still have clear limits. Feeding results back into a loop is not the same as understanding why an answer is right or wrong. The machine may appear to reason, but it is still working with patterns found in human-made content. This raises concerns about accuracy, trust and how much people should rely on AI for important decisions. The article presents these questions as a challenge both for machine developers and for ordinary users.
In conclusion, AI has made remarkable progress, but its ability to think remains uncertain. Understanding how these systems learn helps people use them more carefully. As AI tools become more common in South Africa, in workplaces, schools and homes, it is useful for readers to know what these tools can do and where their limits lie.
Sources: Stuff South Africa
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