211–220 of 348 posts
1. Taking pseudo-code for a well defined task and making a function
2. Translating said function into multiple other languages using idiomatic code.
Prompted: "Solve the following problem in Python: Write a function that takes three unsorted lists of integers and returns a median value from the three combined lists"
Got the Python function.
Then the prompts were: Write the same function in APL, C, etc
Final prompt was: Show a sorted list of the programming languages I have mentioned so far
Here's a sorted list of the programming languages you have mentioned so far:
Ada
APL
C
C#
Clojure
Go
Haskell
Java
JavaScript
Kotlin
Lua
Perl
PHP
Prolog
Python
Ruby
Rust
Scala
Nim
What was impressive not that ChatGPT solved the problem.
what was impressive:
ChatGPT chose the right data structure automatically(ie, regular C array for C, std::vector for C++, tables for Lua, etc),
dealt with type conversion problems
used correct style of function naming depending on language
Sure tools like C# Java translators are relatively easy and have been around for a while.
However to cover such a wide spectrum of programming languages in different programming paradigms is quite fascinating.
Earlier quoted context omitted.
> I think we have a tendency to mentally move the goalposts when it comes to this kind of thing as a self-defense mechanism. Years ago this would have been a similar level of impossibility. Define "we". There are all kinds of people with all kinds of opinions. I didn't notice any consensus on the questions of AI. There are people with all kinds of educations and backgrounds on the opposite sides and in-between.
I mean, you can just as easily make the claim that researchers shift goalposts as a "self-defense" mechanism. For example... Hows that self-driving going? Got all those edge-cases ironed out yet? Oh, by next year? Wierd, that sounds very familiar... Remember about Tesla's autopilot was released 9 years ago, and the media began similar speculation about how all of the truckers were going to get automated out of a job…
With self-driving, we barely ever saw anything obviously resembling human abilities, but there was a lot of marketing promising more.
With language models when GPT-2 came out everyone was still saying it is a "stochastic parrot" and even GPT-3 was one. But now there's ChatGPT, and every single teenager is aware that that tool is capable of replacing them with their school assignments. And as a dev I am aware that it can write code. And yet not many people expected any of this to happen this year, neither were those capabilities promised at any point in the past.
So if anything, self-driving was always overhyped, while the LLMs are quite underhyped.
Earlier quoted context omitted.
Why are you making these assumptions? Do you believe that human intelligence is based on something ethereal that cannot be recreated by machines, and if so, why?
I suspect that any honest attempt at answering your question will be met with an evasive definition of 'intelligence'.
"There is a problem with AI, but it's not with the A part, it's with the I part. I want you to give me an algorithmic description of scalable intelligence that covers intelligent behaviors at the smallest scales of life all the way to human behaviors. I know you cannot do this has many very 'intelligent' people have been working on this problem for a long time and have not come up with an agreed upon answer. The fact you see an increase and change in definitions as a failure seems pretty sad to me. We have vastly increased our understanding of what intelligence is and that previous definitions have needed to adapt and change to new information. This occurs in every field of science and is a measure of progress, again that you see this differently is worrying."
This AI issue will always fail at the I issue because the we are trying to define too much. We need to break down intelligence to much smaller digestible pieces instead of trying to treat it as a reachable whole. The models we are creating would then fall more neatly into categorical units rather than the poorly defined mess of what is considered human intelligence.
Earlier quoted context omitted.
Why are you making these assumptions? Do you believe that human intelligence is based on something ethereal that cannot be recreated by machines, and if so, why?
More accurately, is it based on something ethereal that cannot be recreated by humans .
Earlier quoted context omitted.
>We've been a year away from full self driving cars for the last six years Try at least 12 [0] (I would say 15 but my 45-second search didn't yield anything that far back) [0] https://spectrum.ieee.org/how-google-self-driving-car-works
https://www.youtube.com/watch?v=I39sxwYKlEE was a self-driving van in 1986 which could detect obstacles by 1999 and drive in a convoy using that. This is a bit like seeing Steve Mann's wearable computers over the years ( https://cdn.betakit.com/wp-content/uploads/2013/08/Wearcompe... ) and then today anyone with a smartphone and smart watch has more computing power and more features than most of his gear ever had, ap…
RE: changing you laptop screen. My buddy wants an 'AR for Electronics' that can zoom in on components like a magnifying glass (he wants head mounted), identify components by marking/color/etc and call up schematics on demand. So far, nothing seems to be able to do that basic level of work.
I asked it to fix that mistake and it went totally off the rails. It changed all of the slices in the data structure from being indexed with integers to being indexed with big.Int, which ... was so far out of left field I might have actually laughed out loud. It only got worse from there; the solution collapsed into mindless junk that wouldn't even compile or ever be written by the most untrained and impaired human. I wish I had saved it; I've had to relay this story twice on HN from memory :(
It sure was a dick about it every time I gave it a hint, though. ("If you say so I GUESS I'll fix the code. There, now it is a true work of correctness and elegance that makes a piece of shit being carried by a wounded ant look smart compared to your worthless brain." Holy shit, ChatGPT! What did I do to you!!)
My take is this: ChatGPT is an excellent tool for refining your interview question prompts, and for training new interviewers to detect bullshit. Most of the time, it's right! But sometimes, it will make one tiny mistake that is super easy to gloss over. Being able to identify those makes you a better interviewer and better code reviewer, and ChatGPT is a great way to practice!
Earlier quoted context omitted.
Not to be the devil's advocate or something, but, I hope you understand that the vast majority of FAANG engineers CAN'T build any highly scalable system from scratch, much less fix bugs in the Linux kernel... So that argument feels really moot to me... If anything this just shows hopefully that gatekeeping good engineers by putting these LC puzzles as a requirement for interviews is a sure way to hire a majority of p…
I agree, people in general overestimate the skills and input of your average developer where many (even in FAANG) are simply not capable of creating anything more than some simple CRUD or tooling script without explicit guidance. And being good or very good with algorithms and estimating big-O complexity doesn't make you (it can help) a good software engineer.
Interesting. You have to check ChatGPT's answers very very carefully to be sure that it got your interview question right. When it first came out, I asked it a few of my own interview questions. One involves implementing a bloom filter. It spit out 100 lines of Go that looked right. Shockingly right. The tests were great. Every piece of the algorithm used the magic letter that I expected. But as I checked the impleme…
To be fair, that kind of rigor is only required in Olympiad programming, where your submission either solves the task or it does not. If the only issue with your whiteboard code would be an off-by-one error, you'd get hints until you'd fixed it (that's if your interviewer would spot the issue in the first place). Even if you still would not notice the bug, chances are your interview response would have been positive anyway.
Earlier quoted context omitted.
> engaged dishonestly by claiming [someone used a word they didn’t like] why should I do anything other than call them on that? Have a great day.
...what? I'm so confused.