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Trying out ChatGPT. Tried out a few topics from my field (electrical engineering) and it failed to make basic circuits. A couple queries I tried were making a CMOS inverter or a common-source amplifier, which are very simple circuits that most who have done a class could easily draw. Asked it to give the answer in SPICE syntax, because it can't draw things and SPICE is basically a code representation of a circuit. The results were poor; a MOSFET SPICE line is of the format Mxxx nd ng ns nb , chatGPT got the order of the drain/gate/source/bulk terminals wrong several times. It had some justification for how it connected the nodes of each individual device, but almost always failed to connect the outputs (drains) together for eg. an inverter. Also seemed to connect other terminals sort of at random.
FWIW these two circuits consist of 2 lines of code at minimum, 4 lines if you want something self-contained, maybe 8 if you want it to a fully functioning & simulatable netlist. So not asking for much here.
It gives lengthy canned responses explaining the circuit reminiscent of how a textbook would describe a circuit, and they sound good, but it's just wrong. Kind of reminds me of when students would throw out buzzwords in an attempt to explain something they don't know.
With some handholding (or, rather, explicit statements of how to fix the circuits) it can get closer to something functional, but usually in the process screws up something unrelated such that it's never quite right. Trying with anything even slightly more complex it falls apart pretty quickly and it's impossible to reconcile with anything approaching a functional circuit. It does much worse with analog circuits than digital circuits.
Seeing it underperform so much in my field is giving me a sort of Gellmann Amnesia effect for people touting how it can write code on its own. It certainly wrote out the circuit, and that circuit could be simulated, but it wouldn't achieve the desired behaviour of someone using it, so I'm skeptical that it can code well in other domains. That said, the field is kind of niche, and manually writing SPICE circuits slightly more so, so maybe it is just weakly trained for this subject. SPICE is also different from code in that it doesn't run sequentially, it's kind of like a hardware description language in that it's just instantiating elements that interact with eachother through simulation, so the interfaces between them aren't as simple as passing a variable to a function which does some abstracted function step-by-step. Also with how much content is out there for coding python/javascript/c# etc. it probably has a much greater wealth of resources to pull from.
I think at the moment it is essentially just stringing together user tutorials from the internet in a somewhat intelligent manner, I think anything novel or requiring critical thought will difficult for it to achieve. Maybe with some improved pattern recognition from the scraped data it will do better, I don't know.
Has anyone else tested it with things you're knowledgeable about and have any judgements of its usefulness?
Edit: it seems reasonably okay at turning explicitly stated english-language commands into bash commands. Probably well trained from stackoverflow, seems like a viable alternative to pulling information from different stackoverflow responses to do the thing you want to do. Also seems kind of helpful for asking how to do random MS Office stuff like highlighting every other cell in a column. Could be useful for simple stuff like this that is rote, common, and has good documentation but you don't usually remember off-hand, although you probably have to be extra careful when running bash scripts.
There's this thing called advent of code (AoC) going on right now, it's a yearly speed programming challenge. Each day of december, between the 1st and the 25th a new problem is unlocked at midnight NY time. People tried to use chatgpt, as well as more specialized programming language models to participate. ChatGPT started to struggle on day 3, the specialized models failed on day 5. The first week is all very simple problems with long detailed explanations and all you have to do is essentially follow the instructions in the explanation to solve the problem.
Then there's this interaction https://twitter.com/YossiKreinin/status/1600806007911120898, where chatgpt doesn't know what it means for a word to end in i.
Then there's this interaction I had about timezones:
What's interesting to me about chatgpt is that it may help elucidate what it means to be intelligent by being a close enough imitation that is nonetheless completely unintelligent.
Most people I have ever met end up in a no intelligent back and forth like that on some subject if you talk to them enough. I'm genuinly not convinced that (a lot of) human thought isn't just a slightly better tuned verison of what chatgpt is doing tbh.
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I've heard worse from undergraduates in office hours and other people who are just zoned out, including myself, and this latest idea that surely True Intelligence must be hiding in the performance gap between a slightly dull/intoxicated/sleepy human and a well-educated human at the top of their game strikes me as textbook god-of-the-gaps reasoning. At this point I'm not particularly impressed by any statement of the form "all the things AI does are easy and it won't do this hard thing it can't currently do anytime soon", unless the prediction of what exactly the easy and hard thing are was registered like 5 years ago.
ChatGPT's training wasn't based on the pronunciations and its tokenizer does not reflect the alphabetic spelling of words; from the point of view of its representation, the question is almost comparable to what it would be like for you to have to come up with words whose closest Chinese translation's first syllable is in fourth tone. The real problem here is that ChatGPT has not (yet?) been trained to understand what it doesn't know (as I would guess that its training set does not contain an appropriate set of examples of intellectual humility in Q&A), and instead has a general tendency to just confidently answer even if it has to talk out of its ass. This, too, is all too common in humans.
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