Current AI is bandaids all the way down; LLMs can’t play nicely with basic tools like databases and knowledge graphs, and you never know what you are going to get.
It’s long time to face facts: LLMs have their uses, but we need a sounder foundation for AI.
which is NOT new; see this quote from 5 years ago.
the fact that all this is still true says a lot.
This was right five years ago, and still is:
“Large scale pretrained models are certainly likely to figure prominently in artificial intelligence for the near future, and play an important role in commercial AI for some time to come. The results that have been achieved with them are certainly intriguing and it is worthwhile pursuing them. But it is unwise to assume that these techniques will suffice for AI in general. It may be an effective short-term research strategy to focus on the immediate challenges that seem to be surmountable, but focusing on the surmountable may not get us to what is most necessary: a firm foundation for reliably integrating statistics and machine learning with reasoning, knowledge, common sense and human values.”
Gary Marcus and Ernest Davis, 2021, “Has AI found a new Foundation?” at http://Gradient.Pub
Current AI is bandaids all the way down; LLMs can’t play nicely with basic tools like databases and knowledge graphs, and you never know what you are going to get.
It’s long time to face facts: LLMs have their uses, but we need a sounder foundation for AI.
Many users dismissed LLM approaches as guesswork and opportunistic bandaids that fail to fix core input issues, while some agreed database-first methods would enable better decisions.