OC below by @HaraldvonBlauzahn@feddit.org
What called my attention is that assessments of AI are becoming polarized and somewhat a matter of belief.
Some people firmly believe LLMs are helpful. But programming is a logical task and LLMs can’t think - only generate statistically plausible patterns.
The author of the article explains that this creates the same psychological hazards like astrology or tarot cards, psychological traps that have been exploited by psychics for centuries - and even very intelligent people can fall prey to these.
Finally what should cause alarm is that on top that LLMs can’t think, but people behave as if they do, there is no objective scientifically sound examination whether AI models can create any working software faster. Given that there are multi-billion dollar investments, and there was more than enough time to carry through controlled experiments, this should raise loud alarm bells.
Ah still rolling out the old “stochastic parrot” nonsense I see.
Anyway on to the actual article… I was hoping it wouldn’t make these basic mistakes:
Yes we do. Frankly if you’ve used it it’s so obviously better than regular JavaScript you probably don’t need more evidence (it’s like looking for “evidence” that film stars are more attractive than average people). But anyway we do have great papers like this one.
Anyway that’s slightly beside the point. I think the article is right that smart people are not invulnerable to manipulation or falling for “obviously” stupid ideas. I know plenty of very smart religious people for example.
However I think using this to dismiss LLMs is dumb, in the same way that his dismissal of Typescript is. LLMs aren’t homeopathy or religion.
I have used LLMs to get some work done and… guess what, it did the work! Do I trust it to do everything? Obviously not. But sometimes I don’t need perfect code. For example recently I asked it to create an example SystemVerilog file for me utilising as many syntax features as possible (testing an auto-formatter). It did a pretty good job. Saved some time. What psychological hazard have I fallen for exactly?
Overall, B-. Interesting ideas but flawed logic.
Ah still rolling out the old “computers think” pseudo-science.
Ah yes the old pointless vague anecdote.
Promoting pseudo-science.
Overall D. Neither interesting nor new nor useful.
If your argument is “LLMs can’t do useful work”, and then I say “no, I’ve used them to do useful work many times” how is that a pointless vague anecdote? It’s a direct proof that you’re wrong.
Sorry what? This is bizarre.
It is a bunch of stochastic parrots. It just happens frequently that the words they are parroting were orginally written by a bunch of intelligent people which were knowledgeable in their fields.
Note this doesn’t makes the parrots intelligent - in the same way that a book written by Einstein to explain special relativity has any own intelligence. Einstein was intelligent, his words transport his intelligent ideas, but the book conveying them to other people (as, the printed pages with cardboard cover) is as dumb as a stone. You would not ask a piece of cardboard so solve a math problem, would you?
Your comment doesn’t account for the fact that LLMs can generalise. Often not very well but they can produce outputs for inputs not seen in their training sets. Otherwise what would be the point?
Uhhh you know LLMs can solve quite complex maths problems? Including novel ones.
Amen
And to add that smart people fall for dumb biases, we just need to look at the object oriented mania of the 2000s to late 2010s to see us shoehorn in one paradigm into everything without critically considering whether it made sense over other models.
Can an LLM do everything I need yet? No.
But is a stochastic parrot good enough to help me complete a function and help me restructure code? Yes definitely.
Claude is good enough for so much of the low value code I write that is actually a useful tool. I have to review the code but it’s useable.
I use AI search to lookup functions that I don’t need detailed docs for, or to help me debug arcane library specific errors (just had one earlier today where in polars the list and array types are very much not interchangeable and the explode method was failing).
I still read the docs on things that are critical, and I write the critical paths and dictate structure and understand the problem im solving well.
It’s really amazing the number of people trying to argue that LLMs are useless, while simultaneously so many people are using them successfully. Makes me wonder if they’ve even tried them.