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New research paper attempts to quantify which professions have to most to lose from the introduction of GPTs into the larger world. From the abstract:
The results vary by models but mathematics and math-related industries like accounting have the highest risk. The researchers overall found that "information processing industries (4-digits NAICS) exhibit high exposure, while manufacturing, agriculture, and mining demonstrate low exposure" (pg 15) and "programming and writing skills...are more susceptible to being influenced by language models."
I find myself wondering if "learn to code" from however long back will shortly become "learn to farm" or some such.
Accounting? This seems unreasonable. GPT is a great bullshit artist, but when it comes to precision, forget about it. Something like GPT would be likely to just make up the numbers.
(Insert Sam-Bankman Fried joke here)
I'm assuming you didn't watch the GPT-4 announcement video, where one of the demos featured it doing exactly that: reading the tax code, answering a technical question about it, then actually computing how much tax a couple owed. I imagine you'll still want to check its work, but (unless you want to argue the demo was faked) GPT-4 is significantly better than ChatGPT at math. Your intuition about the limits of AI is 4 months old, which in 2023-AI-timescale terms is basically forever. :)
The GPTs have all followed the same pattern, some surface "wow" and some serious problems when you start pressing them. There's more surface with each iteration, such that GPT-3 does a very good impression of your average Redditor, but nothing's fundamentally changed.
And yeah, any sufficiently advanced technology is indistinguishable from a rigged demo.
VERY strong disagree. You're so badly wrong on this that I half suspect that when the robots start knocking on your door to take you to the CPU mines, you'll still be arguing "but but but you haven't solved the Riemann Hypothesis yet!" Back in the distant past of, oh, the 2010s, we used to wonder if the insanely hard task of making an AI as smart as "your average Redditor" would be attainable by 2050. So that's definitely not the own you think it is.
We've spent decades talking to trained parrots and thinking that was the best we could hope for, and now we suddenly have programs with genuine, unfakeable human-level understanding of language. I've been using ChatGPT to help me with work, discussing bugs and code with it in plain English just like a fellow programmer. If that's not a "fundamental change", what in the world would qualify? The fact that there are still a few kinds of intellectual task left that it can't do doesn't make it less shocking that we're now in a post-Turing Test world.
What code is it? It certainly sucks at the stuff that I work on, to my dismay, and that's weird because my area of expertise is all very much solved and there's a bunch of reference books on it.
It's also very convincing but makes very bad mistakes when talking about philosophy (such as inverting Kant's position on a particular issue, doing the common misreading of Popper's paradox of intolerance or plain hallucinating sources for connections that don't exist).
In my experience it's a very advanced rubber duck and a crutch for boilerplate, but anything beyond that it's just plain bad at.
All you've done is start to believe that sufficiently advanced parrots are human. But they're not on close inspection, and that's only okay in some circumstances.
I don't ask it to write code then plunk it into my projects - I agree that it sometimes gets things wrong there (although you can point out errors and it'll acknowledge and often fix them). What I use it for is to talk through my problems (it's not a rubber duck, because it's replying with knowledge I didn't have before). It uses its vast breadth of knowledge to help me with things like syntax, library functions, simplifying code, debugging a compile error, etc. ChatGPT is bit rougher, but Bing AI has even been smart enough to challenge me when I'm giving it mistaken information, asking follow-up questions that get me to the root of my problem (like a coworker would).
So, I don't want really want to argue the Chinese Room philosophy of when language understanding starts to "count". All I know is what my lying eyes are telling me: I'm now conversing with my computer in completely natural language, and it hasn't once failed to understand me. (Its reply hasn't always been helpful or right, but it's always made sense.) It's important to resist the cynicism of finding ways to break the LLM and going "oh, it's lame after all". Even if LLMs somehow never get any smarter, even if they're not on the critical path to AGI, just the capabilities we've already seen are enough for them to change the world.
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