For LLMs, I think every business is currently throwing things at the wall and seeing what sticks. Nothing wrong with a phase of experimentation for a new techno

For LLMs, I think every business is currently throwing things at the wall and seeing what sticks. Nothing wrong with a phase of experimentation for a new technology, and I prefer the $200M spent on training GPT-4 to the $500M spent on advertising the mobile app Monopoly Go, but I could see an eventual contraction in this activity and number of start-ups. I feel as though the challenges of intelligence and non-shallow reasoning may be more of a slow chipping away with incremental progress, fighting against diminishing returns, rather than exponential improvement or a "hard takeoff" that some are expecting. Generally though, deep learning on large data is undeniably a very useful technique. We've seen huge advances in areas like language translation, voice transcription, OCR, visual defect detection, etc. and will doubtlessly continue to see it applied to a wide range of tasks. If the public and investors sour on "AI", it'll just go by another name as it did before.