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CheatGPT

blog.humphd.org

321–330 of 544 posts

Re: CheatGPT

#321
post #147

Earlier quoted context omitted.

Right, any humans that reads open source code ever should also be forced to submit any code they write to ensure they've not mentally performed copyright violations. I don't give two shits if whatever current expensive GPT is dumping out code 'very similar' to open source code today. And you'd be chopping off your own nose if you did too. Thinking these models will remain as expensive to run in the future means that…

That’s why we have clean room development. For patents it is to avoid triggering triple damages. For copyright it is to help avoid allegations of plagiarism. > Burn copyright to the ground. Burn patents to the ground! Copyright has some use, but the Disney changes have somewhat ruined its purpose.

Cleanroom development practice is a great point to make.

We have precedent of believing that exposure to some code (or other internals) might taint an engineer, such that they can't, say, write a sufficiently independent implementation.

Re: CheatGPT

#322

As a CS professor myself, I don't think ChatGPT really creates entirely new problems for assessment, but rather makes problems that we had been sweeping under the carpet more obvious and harder to ignore. Any assignment that can be cheated by using ChatGPT could already be cheated before by asking a friend, an expert or paying someone else to do it. But most teachers assumed this doesn't happen often, and thus acted…

As a parent, I'm hoping this will reduce the at-home workloads and shift more work towards school. What's the real life value of having students go to school and then spend all-nighters trying to do homework and all the expected extra-curricular?

Re: CheatGPT

#323

So most interview questions like "make a binary tree" are dead. The best interview question that will never die: "What's the weirdest bug you debugged? What made it weird?" For posterity: https://www.gamedeveloper.com/programming/my-hardest-bug-eve...

> "What's the weirdest bug you debugged? What made it weird?" If you can remember, 5-10 years after you solved it.

It doesn't have to be true though, it just has to be a nice story. And this is the kind of interview questions you can prepare.

Re: CheatGPT

#324

As a CS professor myself, I don't think ChatGPT really creates entirely new problems for assessment, but rather makes problems that we had been sweeping under the carpet more obvious and harder to ignore. Any assignment that can be cheated by using ChatGPT could already be cheated before by asking a friend, an expert or paying someone else to do it. But most teachers assumed this doesn't happen often, and thus acted…

As a first year grad student, I had a professor in material science who gave the same assignments and mostly same exams every year. Of course a) I didn't know this b) using previous works was prohibited c) cheating was rampant. I only found this out after getting heavily marked down on the first HW and joining a study group which was moderately chaste (eg only used the answers to check our work before turning it in). Missing a single question on HW or the exam would drop your grade a letter, and three or more was likely D/F range. When I brought this up with the professor before the final he at least acted completely shocked as I asked how likely he thought it was that half the class never missed a question (yes half the class got As). Really weird conversation, but most of the class was undergrads, and I think they liked the easy grade with minimal work and so he got 'good ratings'.

Undergrad college had 'infinite time' and 'open everything but people' exams, but graded on a curve so that sometimes getting half the questions right was an A. Much more stressful, learned more, and basically no cheating.

Certainly, I had one CS class with a newly invented language (compiled). In the days of Fortran, Pascal, and K&R that was kinda par for the course. Not much cheating on that either.

Re: CheatGPT

#325
post #284

Earlier quoted context omitted.

>What we're seeing is the first instance, still very limited and imperfect, of AGI absolutely not. language-model text generation is actually about as non-general as it gets -- they are fundamentally incapable of understanding anything at all, ever. they can't do math, work through basic logic problems, or produce any output that isn't just an assumed logical continuation of the input.

People seem so convinced of this and I just don't get it. I'm seeing this comment through my eyeballs, generating some pertinent text in my brain, and outputting it back out. But so many people seem convinced convinced this process is something radically, fundamentally, irreducibly different than what ChatGPT is doing internally, and I don't get why. Is it because I have a consciousness with an internal narrative and…

LLM (and deep learning in general) are to AGI what bogosort is to sorting. For some reason beyond me people think it's very important to not try to understand anything about the structure of the problem you're trying to solve and just make a very general algorithm which will be suboptimal in just about every way except for the generality of it's code.

Seeing the world as a trillion dimensional token soup is definitely quite general and at the same time very very weak in terms of expressivity.

Re: CheatGPT

#326
post #284

Earlier quoted context omitted.

People seem so convinced of this and I just don't get it. I'm seeing this comment through my eyeballs, generating some pertinent text in my brain, and outputting it back out. But so many people seem convinced convinced this process is something radically, fundamentally, irreducibly different than what ChatGPT is doing internally, and I don't get why. Is it because I have a consciousness with an internal narrative and…

It's because whatever you and I are doing, it's not simply statistical analysis. That is all that ChatGPT is doing. It may be possible to create a machine that flirts with actual intelligence, but this is simply not it. There's not even room for doubt about this.

I can't claim to understand everything my brain is doing, but accepting input and filtering it through a bunch of neuron chains to result in some kind of output sounds like "statistical analysis" to me.

You seem convinced that ChatGPT will never have "actual intelligence" — care to make a prediction about something that LLMs will never accomplish? We know they can write code, write essays, generate artwork, and play chess. What's a task that requires "actual intelligence"? Parenting a child? Running for President? Making a steak sandwich?

Re: CheatGPT

#327
the world has changed dramatically in only one year. these advancements in AI are talked about everywhere and by everyone.

in 2018 i warned people i knew and i wrote many comments online warning people that huge changes were coming. almost every single person on HN insisted that GTP was just a parlor trick because it would ramble sometimes, get stuck in loops and overall did not demonstrate the insane level of lucidity that it does now. almost every single person on HN would silently downvote my comments. almost every single HN user insisted that AI could never progress to where it is now. well here is my bittersweet vindication. watching people move the goalposts is like watching a supernova. its so powerful and unbelievable that it can only be compared to a force of nature.

commenting a sentiment that doesnt paint AI as harmless is like screaming into a hurricane. i dont even know why i bother anymore. but let me just say it: i think carmack made a great point when he said that the first AGI will be a bunch of lower AIs plugged into each other. GTP doesnt behave in a sentient way but it is very similar to more primitive parts of the mind. its like a persons intuition. dont be fooled by the limitations of any one model. whats important is the road we are on. and for the hundredth time i will scream into the wind: there absolutely is hope in the idea of preventing AI from progressing rapidly or even at all. to do so is absolutely necessary for us to preserve anything that we would consider a good life for future generations.

and i will offer a prediction. nobody will agree with me. but after a handful of explosive advancements in AI, everyone will agree with me.

Re: CheatGPT

#328

So most interview questions like "make a binary tree" are dead. The best interview question that will never die: "What's the weirdest bug you debugged? What made it weird?" For posterity: https://www.gamedeveloper.com/programming/my-hardest-bug-eve...

> "What's the weirdest bug you debugged? What made it weird?" If you can remember, 5-10 years after you solved it.

Me to ChatGPT: reply to this interview question "What's the weirdest bug you debugged? What made it weird?" in first-person, make it a personal story.

ChatGPT: It was early on in my career as a software developer, and I was working on a web application that was designed to allow users to upload images and apply filters to them.

One day, a user reported a strange issue where some of the filters were producing unexpected results. Specifically, they were seeing images that appeared to be completely random and unrelated to the original image. At first, I assumed it was a problem with the filter algorithms, but as I dug deeper, I realized that the issue was actually caused by a very strange bug.

It turned out that the user's browser was caching a previously uploaded image and reusing it for subsequent filter operations, even if the user had selected a completely different image. This led to some very bizarre and unexpected results, as the filter algorithms were being applied to an entirely different image than what the user intended.

To fix the bug, I had to implement a workaround that forced the browser to always load the most recent version of the image from the server, rather than relying on its cache. It was definitely one of the weirdest bugs I've ever encountered, and it taught me the importance of always being vigilant when it comes to caching and browser behavior.

Me to ChatGPT: reply to this interview question "What's the weirdest bug you debugged? What made it weird?" in first-person, make it a personal story, make it using C++.

ChatGPT: I was working on a project that involved developing a custom compiler. One day, a user reported a very strange issue where the compiled program would crash whenever it encountered certain input files. At first, I assumed it was a problem with the input files themselves, but as I dug deeper, I realized that the issue was actually caused by a very strange bug in the compiler code.

It turned out that there was a subtle error in one of the class definitions that was causing memory corruption in certain circumstances. Specifically, the class had a virtual destructor, but the derived class failed to declare its own destructor as virtual. This led to undefined behavior when deleting objects of the derived class, which in turn caused the program to crash.

To fix the bug, I had to carefully analyze the affected class definitions and make sure that all derived classes properly declared their destructors as virtual. It was definitely one of the weirdest bugs I've ever encountered, and it taught me the importance of paying close attention to class hierarchies and virtual functions in C++.

Me to ChatGPT (since I haven't worked on a compiler): reply to this interview question "What's the weirdest bug you debugged? What made it weird?" in first-person, make it a personal story, make it using C++ about the time when I ported PyTorch from Python to R.

ChatGPT: One of the weirdest bugs I encountered was during my work on porting PyTorch from Python to R. One of the major challenges was ensuring that the R implementation matched the performance and functionality of the Python version. As I was going through the codebase, I noticed a particularly strange issue that was causing crashes in the R implementation.

The issue turned out to be related to differences in how Python and R handle memory allocation and deallocation. PyTorch relied heavily on dynamically allocated memory, but the R implementation was not properly managing this memory, leading to crashes and other unexpected behavior.

To fix the issue, I had to go through the entire codebase and carefully analyze all memory-related operations. This involved a lot of debugging and experimentation, as well as close collaboration with the rest of the development team.

Ultimately, we were able to resolve the issue and deliver a stable and performant port of PyTorch to R. It was definitely one of the weirdest bugs I've ever encountered, and it taught me the importance of paying close attention to memory management in C++ and other low-level languages.

Note: Likely ChatGPT can also generate a fake resume, etc. so yeah.

Re: CheatGPT

#329

Earlier quoted context omitted.

Something that I don't quite understand is why the tendency of ChatGPT to be inaccurate sometimes is a fundamental flaw rather than something that can be improved on iteratively if its just a matter of improving the statistical likelihood of accuracy. The question of whether its AGI or not is, to paraphrase the famous quote, a bit like the question of whether a submarine can swim.

Because ChatGPT isn't thinking. It's not reasoning at all. It's assembling sentences that are statistically predicted from using existing writings as the template. Accuracy isn't a part of the process except in terms of how accurate the training data is. ChatGPT is not making any sort of truth or accuracy determination, let alone doing so poorly.

Can you point to where the thinking happens in a human?

Re: CheatGPT

#330
post #83

Earlier quoted context omitted.

What is the difference between `let` and `const`?

https://stackoverflow.com/questions/22308071/what-is-the-dif... The difference between let and const is that once you bind a value/object to a variable using const, you can't reassign to that variable. In other words Example: const something = {}; something = 1; // Error. let somethingElse = {}; somethingElse = 100; // This is ok

Which is odd because in every other language that uses let (lisp, scheme, swift, rust, scala/kotlin val, haskell, etc.), let bindings are const and let is synonymous with const.
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