mamp
Joined 15 years ago
Joined 15 years ago
The main barrier to scaling was workflow integration due to lack of electronic data, and if it was available, interoperability (as it is today). The other barriers were problems with maintenance and performance monitoring, which are still issues today in healthcare and other industries.
I do agree the 5th Generation project never made sense, but as you point out they had developed hardware to accelerate Prolog and wanted to show it off and overused the tech. Hmmm, sounds familiar...
BTW the ad hoc treatment of uncertainty in Mycin (certainty factors) motivated the work of Bayesian network.
Gemini doesn't seem to be as keen to agree with me so I find it makes small improvements where Claude and OpenAI will go along with initial suggestions until specifically asked to make improvements.
My understanding is the goal is to prime the LLM with context that it will use when generating answers, rather than hoping it will infer connections in the feed forward layers when generating answers based on a sparse prompt.