I am a PhD biophysicist working within the field of biological imaging. Professionally, my team (successfully) uses deep learning and GANs for a variety of tasks within the field of imaging, such as segmentation, registration, and predictive protein/transcriptomics. It’s good stuff, a game changer in many ways. In no way however, does it represent generalized AI, and nobody in the field makes this claim even though the output of these algorithms match or out perform humans in cases.

LLMs are no different. Like DL modules that are very good at outputting images that mimic biological signatures, LLMs are very good at outputting texts that eerily mimic human language.

However — and this is a point which programmers are woefully and comically ignorant — human language and reason are two separate things. Tech bros wholly confuse the two however, and thus make outlandish claims we have achieved or are on the brink of achieving — actual AI systems.

In other words, while LLMs and DL in general can perform specific tasks well, they do not represent a breakthrough in artificial intelligence, and thus will have a much narrower application space than actual AI.