A new study challenges the idea that AI models like those from OpenAI and Google can truly “reason” like humans. Researchers tested 20 of these models, giving them over 8,000 simple math problems. But to avoid AI cheating by remembering answers, they changed the names, numbers, and even added unnecessary details to the questions. The AI’s performance dropped, with some models making up to 65% more mistakes when faced with irrelevant info. The study shows that, instead of really understanding the problems, AI models are just matching patterns and often get confused when the details are changed.
GreyMatterz Thought
It’s eye-opening to see that AI models still rely heavily on pattern recognition rather than true understanding. This study highlights the gap between human reasoning and machine learning, especially when small changes can throw the models off so easily.
Source: https://shorturl.at/ByvUn
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