100%, AI moves in cycles related to scientific research, same as most other tech innovation funding hype boom/bust cycles.
Incremental scientific research delivers new possible features -> funding hype to be first to market -> engineering builds products based on new tech -> people learn what it can and cannot do through use -> hype dies and funding dries up (you are here for LLMs) -> less funding stops engineering new products and research continues incremental changes until repeat.
It’s been that way for AI since the 80s with expert systems, then deep nets, and now LLMs. I suspect a lot of layoffs over the past year have been related to over committing to commercial office space and AI solutions not delivering projected ROIs.
Incremental scientific research delivers new possible features -> funding hype to be first to market -> engineering builds products based on new tech -> people learn what it can and cannot do through use -> hype dies and funding dries up (you are here for LLMs) -> less funding stops engineering new products and research continues incremental changes until repeat.
100%, AI moves in cycles related to scientific research, same as most other tech innovation funding hype boom/bust cycles.
Incremental scientific research delivers new possible features -> funding hype to be first to market -> engineering builds products based on new tech -> people learn what it can and cannot do through use -> hype dies and funding dries up (you are here for LLMs) -> less funding stops engineering new products and research continues incremental changes until repeat.
It’s been that way for AI since the 80s with expert systems, then deep nets, and now LLMs. I suspect a lot of layoffs over the past year have been related to over committing to commercial office space and AI solutions not delivering projected ROIs.
TLDR: AI works on goverment funding.