If you want a specific example of why many researchers in machine learning and natural language processing find the idea that LLMs like ChatGPT or Claude are "intelligent" or "conscious" is laughable, this article describes one:
https://news.mit.edu/2025/shortcoming-makes-llms-less-reliable-1126
#LLM
#ChatGPT
#Claude
#MachineLearning
#NaturalLanguageProcessing
#ML
#AI
#NLP
@hosford42 "colorless green ideas sleep furiously!"
There are quite a few examples of this sort of problem already documented in image processing. Examples include the neural network that learn to recognize *not* the thing they are being trained to recognize, but instead the background, setting, camera, lighting, or presence of markings like watermarks or logos.
It comes as no surprise at all that the same problems can be observed in language models.
