The big thing was huge progress in natural language understanding. 2023 was the year the Turing test was smashed.
Seeing computers win games, drive cars, optimize systems, even design things wasn’t as subjectively impressive to most of us as being able to talk to them. This was the year we first saw AI that could sort of communicate with us the way we can with each other.
One problem with the Turing Test we might have predicted: if people have context on how models have improved, they narrow their expectations to match.
But I suppose the Strong Turing Test is when a model is so much smarter than us, that it can convincingly hide its differences and superiority, even when we have good reason to suspect it’s an AI.
- Acting as a lossy text decompressor (harmful)
- Acting as a lossy text compressor (mostly trying and failing to undo the damage from above)
- Acting as an outright bullshit generator (harmful)
- Acting as a poor substitute for a search engine with a propensity for trying to bullshit you (harmful)
- Acting as a poor substitute for a parser (which, even if it worked would be dumb because it doesn't understand structured output, so now you have two parsing problems)
- Generating broken and/or extremely poorly factored code (harmful)
- Hiding plagiarism (harmful)
GPT (and the AI hype in general) is the wrong solution to the wrong problem. Look at the effort that Google wasted on Duplex instead of OpenTable.