3 ms·
I recall some company or project in the late 70s or 80s putting together a massive database of concepts and how they relate to each other, i.e. a semantic word
by the_biot 4y ago
I recall some company or project in the late 70s or 80s putting together a massive database of concepts and how they relate to each other, i.e. a semantic word database. Wish I could remember the name, I know it's on wikipedia somewhere.
I always thought the effort must have been related to code like this. This simple language interpreter can do lots of things, but only in its small world of boxes and pyramids. It follows that if you teach it a bunch of things and how they relate to each other, you'd create an intelligent computer.
Instead that whole field was dropped, presumably because it didn't work, and eventually neural networks started to be thought of as the next generation of soon-to-be-AI systems. But it's pretty apparent by now that things like GPT-3 are hollow shells, good at emulating some very specific things humans can do, but there's nothing remotely like intelligence behind it.
I wonder if in 20 years we'll look back at this as another dead end on the road to AI.
- handojin 4y agoCyc? It's still a going concern - www.cyc.com
- JPLeRouzic 4y agoThere were also Thought Treasure. In some aspects it is similar, only a bit more modern (1990'): https://en.wikipedia.org/wiki/ThoughtTreasure https://en.wikipedia.org/wiki/ThoughtTreasure
- the_biot 4y agoProjects like this one and Cyc really appeal to my inner hoarder and programmer both. It must be so satisfying (if pointless) to create datasets like this. But I suspect the next time somebody tackles a project like this it'll use natural language parsing to derive its dataset from all the world's written text, automatically. Wikipedia will tell you a pea is green, if you can read it.