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Comment by dkjaudyeqooe | Hacker News Reader

I guess we can look forward to weeks of "Show HN: $X created by ChatGPT" but people should be cautioned not to read to much into these results. Always remember that almost all of what is being presented here is the work of humans, regurgitated by a very much non-intelligent machine, despite its name. It's basically:

Human creation -> ChatGPT -> Human query -> Human interpretation

The last bit, the interpretation, is particularly important. Just like we're predisposed to seeing faces everywhere, we're predisposed to seeing meaning, and perhaps "intelligence", everywhere. In this case the meaning is very convincing since it comes from other humans, diced and sliced, but is merely presenting ourselves to ourselves in an interactive way, using our style of discourse.

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I'm sure this line of logic is very comforting, but frankly, this comfort disappears quickly when you actually use ChatGPT. What you find is that you can interact with it in a quite natural way, and it is able to synthesize and iterate at a level that feels easily on par with a moderately skilled human software engineer. I know it's uncomfortable, but it doesn't even matter if the machine is "non-intelligent." Nobody gives a damn. What matters is what you can do with it, and every iteration of GPT the goal posts keep moving further, but this time it's really difficult to deny: you really, really can describe a program at a high level and ChatGPT can implement it. You can point out an error and it can fix it. Hell, you can feed it compiler errors.

Is it literally as good as a human software engineer? No, but it's also better too. I doubt ChatGPT could debug as effectively as a veteran software engineer (... In fairness, most humans can't either.) It can debug pretty decently, but there's still work there. That said, the breadth of knowledge encoded in a language model is stunning. I'm pretty sure you can't just regurgitate an implementation of the discrete cosine transform in Rust without at least pulling up Wikipedia, but ChatGPT can, because well. It doesn't have to pull it up.

I still don't think ChatGPT is ready to replace human programmers. It may be a long time before we have general enough intelligence to replace knowledge work meaningfully with AI. However, if you think it's not happening ever, because machines are not "intelligent" based on some set of goal posts, I've got bad news: that's not part of the job listing.

It's easy to laugh at MSN publishing articles written by GPT; that's just stupid. However, at some level you have to admit that the input to ChatGPT is almost as high level as directives from project managers, and the output is almost low level enough to simply input directly into source control. That leaves very little to the imagination for how this could quickly spiral out of control.

Ye I signed up and tried some queries. It was quite scary.

"Write a function that sorts the elements of a c string backwards, in C." "Add a flag to the sort function which makes it sort the string forward." "Could you write a endian swap function for double argument in PIC assembler?" "Could you write a binary sort in PIC 8-bit assembler" "Write a Javascript function that prints the day of the week together with some Chinese words of wisdom."

It had no problem doing any one those. I ran them all, except the assembler ones.

The question is how good it is to process larger chunks of code and makes changes to it.

People thinking about becoming programmers might need to rethink their plans if this one improves ...

EDIT: Oh dear. I introduced bugs in its sort code and it found them and explained what they did.

Last night I entered the page-long instructions for Advent of Code day 4, and it spewed out perfectly readable code and solved it on the first try [1]. And we're not talking about a common algorithm that has been solved many times before, but a convoluted story that is full of "elves cleaning up overlapping sections of the camp" (!), and ChatGPT was still able to understand it, write the code to solve it, and even explain how it works.

It's nothing short of a phenomenal milestone.

[1] https://twitter.com/GuiAmbros/status/1599282083838296064

Are you sure this whole problem with its solution wasn't indexed in ChatGPT training set, so all it did here is retrieve the whole answer to the problem similar to how google will find the solution pretty quickly if you search for "advent of code day 4 solution"?

Can you see if it solves an advent of code problem whose solution hasn't been posted yet? If it did I will consider this an almost publishable breakthrough.

It wasn't in the training set - the puzzle was released today, as part of this year's advent of code. ChatGPT is eminently publishable and has demonstrably produced plenty of novel, if boring, code.

Genuine question: can it write larger codebases yet such as: “write a pac-man clone in JavaScript, html, and css”

It can't write pacman. But if you describe a scenario to it, it writes pretty accurate code and can drill down. Very impressive

Yes, but you'll have to chop the project up into different parts and describe each sufficiently well.

For example, start with "write a level generator in JavaScript which outputs pacman like levels encoded in ASCII which could be used as the basis for a pacman clone."

Then you'd say "Great, now write a pacman clone in JavaScript which takes the input of the previously generated level generator and takes interactive input on the console."

Then you'd have to ask it to generate the HTML and CSS. It won't do it all at once. But it will do it piece by piece.

Yes, it's absolutely feasible. I did exactly that with a simpler version of this (Tic Tac Toe, and console only, no actual visual interface) but it worked pretty well.

The main thing is having a good idea of what the overall program structure will look like. If you have that, I think you can go pretty far with it.

Btw, in case anyone wants to see what working like this may look like, I recorded myself while doing that little experiment: https://youtu.be/TBMQIDMwI5E

I'm trying that right now. It can probably do it, the big issue right now is that it won't give really long answers and just stop in the middle, which can be avoided by asking him to finish it, but it doesn't always works.

If you can break down what you want into smaller functions, instead of just asking for the whole thing at once, you can actually do a lot with it, including telling it to out it all together at the end.

Won't link it again so as to not get too spammy, but I posted a recording of an experiment I did playing around with ChatGPT in that way on a sibling comment if you want to check that out.

I've tried giving it languages like Turbo Pascal or telling it to obscure frameworks like fp-ts and while sometimes it's not syntactically perfect, but I can guarntee it's not just scraping code snippets from somewhere.

The guy that got the first position for the first part, thus the first solution ever on that problem, was using ChatGPT to do it. [1]

[1] https://github.com/max-sixty/aoc-gpt

I tried higher level problems: write an http server in rust using warp and postgres, with endpoint for get users and put user.

9 compile errors, some due to cargo.toml issues (it only generated main.rs). But mostly worked.

The post we’re discussing is also pretty impressive, a working lexer/parser

The answer is it’s very bad at large amounts of code. It has no skill at reasoning across a large amount of files where say you’d need to make many small changes in a handful of places and know that those changes all work together.

These models are amazing at regurgitation. They have no skill at reasoning and any solution outside their training set. They have a distinct disability for precision in anything remotely novel or large. And they will bullshit subtle bugs all over the place at scale.

Even a junior programmer would produce more value than the next generations of this, simply because they can take vague English instructions and actually make iterative progress across a huge codebase, test those changes for all sorts of vague constraints, and be precise. There’s no ability for that here.

This tool would make for a great pair programmer and an intelligent interactive rubber duck

Except you must have the underlying knowledge to effectively review code. So how that would obviate a career in programming is a strange choice by the grandparent commenter. Anyone can rubber stamp bad code, but to stop bad code from entering projects you need experts.

Most projects have plenty of bad code, nobody cares, as long as it solves the problem.

The bad code it produces is not just stylistically bad, it often doesn't solve the problem.

It seems to be making the same kind of errors in code as we've seen in speech, you get a lot of plausible but subtly wrong hallucinated content that only someone who knows the subject can identify. It prefers probable output over matching the specifications so it'll add unnecessary branches just because it's seen them millions of times.

Among errors I've seen it make there is bad indexing, adding conditions that serve no purpose or assuming a variable has a specific structure when it doesn't.

Well my mortgage is thankful for that.

I have a feeling though that tools like this will lower the skill threshold for programming by a lot.

I gave it this code I just made and asked it what it does and it figured it out:

    public class mean_sink {

        double sum;
        long n;
        
        public mean_sink(){
        }
        
        public void add(double d){
            sum += d;
            n++;
        }
        
        public double getMean(){
            if(n == 0)
                return Double.NaN;
            return sum/n;
        }
    }

I asked it to improve the numerical accuracy and it did it with BigDecimal instead. I asked it to only use doubles and it did some strange reciprocal summation when I was "hoping" for Kahan summation algorithm. Its "reciprocal summation" did not work. But it made a correct Kahan when I asked for it.

I dunno. This is insane anyway. It is really hard to grasp the consequences.

>Even a junior programmer would produce more value than the next generations of this

At the rate this is evolving that wont be a limitation for long.

My 14 yr old son thats taught himself to code in c# over the last few years is going to be put of a potential job before he cab be taught to code professionally.

This is quite frightening, the rate of evolution.

> The question is how good it is to process larger chunks of code and makes changes to it.

> People thinking about becoming programmers might need to rethink their plans if this one improves ...

Very true, and this thought definitely crossed my mind as well. In the short term I imagine this is going to be like any other tool, it will increase your leverage, and make it possible for you to write code faster.

For example, I fed it 100 lines of a Django model and asked it to write some query code for me. Produced something that was possible faster than I could have. The few slight deficiencies it did have (optimizations) basically felt like me doing a code review.

Hi, thanks for breaking it down.

Do you write code close to the machine at $job?

I wanna try with more feature and UI heavy request.

I actually comment because of your edit in your response : you manually introduced bugs, reran the process, and it seen you broke it ( fine ) but was able to explain it to you in English ?

Where is that comming from ? Adjacent comments and git comments?

I asked it to make some stuff in flutter and it worked well. I did notice sometimes it just adds a comment in the function saying “insert logic here for X” when it doesn’t know how to write it.

> I actually comment because of your edit in your response : you manually introduced bugs, reran the process, and it seen you broke it ( fine ) but was able to explain it to you in English ?

I fed it it's own sorting function but I added bugs to it and asked it to spot the bugs.

I tried a hard level leetcode problem on it. Perfect results on the first attempt.

it was trained with leetcode data though?

Ah I didn't know that.

Something I’ve noticed in my own experimentations is that it’s really only limited by the length of its replies. It can happily generate perfect code but then stop in the middle of a function simply because the website only asked for 200 tokens or something. It’s really quite something to say that one of my gripes lies not in the model but in the user interface wrapping the model.

programmers are final worker. there are not no more jobs.

I already managed to get it to write an implementation of Pong and a Chip8 interpreter, both in C and using SDL2 for graphics/input/sound (it even wrote a function to generate the waveform for a beep for Chip8 and rebound sound for Pong!). I'm pretty sure I can get it to generate all the code for a Gameboy or NES emulator, I've taken a few tentative steps and it definitely can reproduce the memory map and generate code to parse iNES/GB cartridge headers

Still, it's a tool that requires human input. Similarly how Photoshop didn't make artists obsolete, it elevated the trade to a new level and capabilities.

"And what would excite me about actually the birth of superintelligent AI - one of the things, apart from solving obvious problems like curing disease and energy issues and all the rest, perhaps differs a little bit with what Stuart said. I’m not so worried about idiocracy or all of us just losing our way as apes and living unproductive lives in dialogue with these oracles. I think actually, I would want a truly value-aligned superintelligence to incrementally show us, not merely conserve what we want, but show us what we should want to keep improving our values so that we can navigate in the space of all possible experiences and converge on better and better ones." - Sam Harris

Source : https://youtu.be/h0962biiZa4?t=2486

It is probably an excellent learning tool. You can show it code and it will point of the bugs.

    void sort_string(char *str, int backwards) {
      // Get the length of the string
      int len = strlen(str);

      // Use a bubble sort algorithm to sort the string
      for (int i = 0; i < len; i++) {
        for (int j = 0; j < len - i; j++) {
          // If the current character is greater than the next character (or less than, if sorting backwards), swap them
          if ((backwards && str[j] < str[i + 1]) || (!backwards && str[j] > str[i + 1])) {
            char temp = str[j];
            str[j] = str[j + 1];
            str[j + 1] = temp;
          }
        }
      }
    }

Will yield: "The sort_string() function contains two bugs. The first bug is in the inner loop conditional statement [...] The second bug is in the termination condition of the inner loop."

and a detailed explanation of the fix and what the problems are.

The problem is that the working market might be flooded by this since way more people will be able to code ... Github Co-pilot is nowhere near this.

Yes, it seems useful for advanced learners who might actually have questions. It probably can't teach you from scratch yet.

I asked it to write a Forth function to do something and when it used commands (words) I didn’t know I asked it what those did. Seems useful for learning. The problem I see is you never know for sure when it’s bluffing about a fact.

> Github Co-pilot is nowhere near this. They're both based on GPT-3. The difference is that Copilot's model is trained on a lot more code. I'd be amazed if Copilot doesn't have a super-linter soon that can find and fix these kind of bugs.

Photoshop didn't make artists obsolete but i.e. rendering software did many people obsolete.

> However, if you think it's not happening ever, because machines are not "intelligent" based on some set of goal posts, I've got bad news: that's not part of the job listing.

When an AI is able to train itself (like a human) is when developer jobs will be in trouble. Fortunately, every other profession will also be out of a job as well.

Until then, rote work will continue to be automated more effectively but no more.

The most ironic thing is that people who do the hard work are unlikely to be obsoleted any time soon. At least in third-world countries. Theoretically you can build robot today to replace janitors, plumbers or serviceme but it just too expensive and does not scale.

But replacing computer operators is scalable. So I definitely expect most office people including low skilled developers to be replaced by AI in a 20 years. High-skilled developers might survive (and I'm not sure if I'd qualify) but obviously for most workers that's not very encouraging.

> However, at some level you have to admit that the input to ChatGPT is almost as high level as directives from project managers, and the output is almost low level enough to simply input directly into source control.

This is the part that is going to change the way people work in fundamental ways very quickly. It will turn good software developers into non-shitty project managers, project managers into ?, and mediocre developers into ?.

Project managers into mediocre developers and mediocre developers into jobless.

Honestly the thing that shocked me the most is this kind of query I've been doing for the last 10 hours:

  Rewrite the following in Rust:

  size_t strlenNEON(const char *p)
  {
      const char *const top = p;
      uint8x16_t c16 = vdupq_n_u8(0);
      /* 16 byte alignment */
      size_t n = reinterpret_cast<size_t>(p) & 15;
      if (n > 0) {
          uint8x16_t x = *(const uint8x16_t*)&p[-n];
          uint8x16_t a = vceqq_u8(x, c16);
          unsigned long mask = GetByteMask(a) << (16 + n);
          if (mask) {
              return __builtin_clz(mask);
          }
          p += 16 - n;
      }
      assert((reinterpret_cast<size_t>(p) & 15) == 0);
      for (;;) {
          uint8x16_t x = *(const uint8x16_t*)&p[0];
          uint8x16_t a = vceqq_u8(x, c16);
  
          if (isFound(a)) {
              unsigned int mask = GetByteMask(a);
              return p + __builtin_clz(mask) - top;
          }
          p += 16;
      }
  }

It even correctly produces the implementation of the unimplemented functions being called from the C++ impl.

It's the journey not the destination that matters.

It works well with popular languages. Any somewhat obscure language results in ChatGPT hallucinating nonsense code and telling you it's correct when it's not.

It can do pretty well with obscure languages if you explain how they work before you ask for a solution. You can even invent a whole new language just for the question.

Almost all the comments I've seen criticizing ChatGPT run into the same fallacy: they're applying a double standard compared to humans. What you said applies to output produced by humans as well. Similarly, many humans also have difficulty doing multiplication with large integers, differentiating between truth and fiction, answering with non bullshit answers, etc. Sure, it's probably a question of degree (and it's an important limitation), so we could probably say it's at the level of a dumb human, but even so, it can already exceed the average human's capabilities in many interesting and useful tasks!

And not only that, what's most amazing is that it can exceed humans at abilities that many years ago, most people thought only humans could accomplish (tasks including creativity, including creating art, writing poems/literature, interpreting ambiguous human questions and text, doing analogy-based reasoning and problem solving, grasping and explaining puns, making new jokes, etc). And these models can only improve in the future!

Tools are often objects that "exceed the average human's capabilities" in some respect or another but assigning the quality of intelligence to tool itself is like calling a hammer strong or a chisel brave. It maybe true in a metaphorical sense but it doesn't have any objective meaning.

I really don't understand the argument you're making. From my perspective, you're doing exactly what I said: you're setting a double standard, like the previous poster.

If I have a robot that talks like a human, including answering questions like a human, behaves like a human in any way that is important... wouldn't this "tool" be intelligent, just like a human?

How are robots different from ChatGPT except having a physical presence and being able to manipulate the world physically?

Or are humans so special to you (or intelligence so subjective) that you can't possibly answer "yes" to the above statement about a robot being intelligent?

what you are saying here basically is: if it quacks and can fly, it’s obviously a duck.

No, because I'm not saying robots are human just because they're intelligent.

The analogy is more like: if robots can write like a human, then robots have the ability to write, and saying otherwise is just applying a double standard.

Similarly, if a robot can behave as intelligently as a human, then such a robot is intelligent and I don't see how anyone can argue otherwise without logical fallacies.

ok, no argument from me on that.

but are we saying robots can behave intelligently as a human?

> but are we saying robots can behave intelligently as a human?

I believe that ChatGPT can behave more intelligently than most humans at many important and useful tasks already.

I also believe that it behaves less intelligently than most humans at many tasks that are also important and useful.

For some other tasks, it behaves at more or less the same level as a human.

Moreover, I believe that the gaps between what models like ChatGPT can do and what a human can do are closing extremely rapidly.

You ChatGPT? :)

Humans have "skin in the game". If they don't do "good enough", they could be reprimanded (ego-hurt), out of a job (stressful), or even in prison or dead (existential threat). This is not foolproof, but it's at least something. There is no incentive for AI to be correct, nor any incentive for it to become more correct.

To wit: I asked ChatGPT to write me a function to generate Hanukkah dates. It spewed a couple of facts about Hanukkah, and the generated function just returned the 8 days following Christmas. I said it was wrong, and it said "you're right!" and then gave me another wrong function (always returning March 25th, since it's actually in the 3rd month of the Jewish calendar, duh). I told it that it was wrong again and asked specifically for a Jewish to Gregorian calendar conversion function, and it gave me some more code that I have no idea is correct or not. So I asked for a table of 10 test cases of Jewish dates and their corresponding Gregorian dates, and not a single one was valid.

I actually have worked with some remote contractors who pull this kind of crap, just throwing garbage over the wall repeatedly until I give up because I just don't want to deal with them anymore. And no, they never get any better. They are not junior devs you can mentor or train or whatever. Their whole model of work is to generate something complicated enough to seem plausible and then bullshit you into accepting it so they can get paid. I have to inspect every line of code they write and do all the diligence myself anyway, and this is more time-consuming and less fun than just doing it myself in the first place. At best it's a nerd-snipe motivation in a "wrong answer on the internet" kind of way.

Strong No Hire. And if you hire them and stick me on code-review duty, I quit.

> There is no incentive for AI to be correct, nor any incentive for it to become more correct.

Are you saying that for current AI, or also for future AI?

I'm not an expert, but I think reinforcement learning is a pretty well-established AI technique at this point, which does give an AI incentive to be correct and become more correct.

I've heard rumors OpenAI is even doing that with ChatGPT, based on human feedback (with the thumbs up/down button).

> Strong No Hire. And if you hire them and stick me on code-review duty, I quit.

I mean, I agree. I wouldn't hire ChatGPT to replace a programmer currently, just like I wouldn't hire many humans, even many who claim they are programmers/engineers.

But at this rate, I might just hire a future version of it :)

And I'm already using it as a pair programmer, code reviewer, glorified Google search engine, email/letter redactor... and it also gave me truly amazing insights on how to prove difficult mathematical theorems that I was struggling to prove (on a theorem prover).

It's nothing short of a miracle, in my view.

More broadly, I think we'll see a proliferation of internet content generated by ChatGPT--blog posts, essays, product summaries, tutorials, news articles, etc.

The danger is that the content generated by ChatGPT is very coherent, but technical details are frequently wrong. It's going to become increasingly difficult to separate the signal from the noise on the internet.

I also wonder what the effect of more and more model outputs being fed back in as inputs will be.

If this AI is so amazing, it can save us all a lot of grief by translating the Linux kernel to Rust now in one fell swoop rather than enduring 1,000 incremental posts of "now $X is written in rust..."

This is what concerns me. Many people worry about being replaced by AI, but I'm far more worried about AI completely polluting digital communication. I think stuff like this is going to make it harder for companies to assess candidates, fight fraud and generally operate. I hope I'm wrong, but thinking about AI entering the digital communications arms race is only going to make things more difficult, i.e. more personalized spam call scripts, more intelligently targeted ads/spam/scams.

I think AI is going to force us on some level to reclaim some of our communication to the physical world, if for no other reason than it's going to be one of the only ways we can truly verify that we're talking to another person.

Alternatively, we might become more journalistic/academic. Naming and checking your sources will become paramount.

I hope so, but the cynic in me doesn't see this happening because this has long been a problem that isn't going away.

The better that computers get at generating content and behaving in ways that only humans used to be able to is going to make it harder to determine if a source is human or not.

To an extent yes, but this can quickly become overwhelming.

For example, editors and reviewers for academic journals / conferences will likely see a deluge of AI-generated "scientific" papers. Their time is limited, and odds are that more papers with incorrect information will slip through the peer review process.

To be clear, peer review today certainly isn't perfect at catching bad papers. But AI generation has the potential to exaggerate the problem.

For inspiration, here is how the NYTimes deals with anonymous sources:

What we consider before using anonymous sources: How do they know the information?

What’s their motivation for telling us?

Have they proved reliable in the past?

Can we corroborate the information they provide?

Because using anonymous sources puts great strain on our most valuable asset: our readers’ trust, the reporter and at least one editor is required to know the identity of the source. A senior newsroom editor must also approve the use of the information the source provides.

That's already been a problem for some years already:

https://dailysceptic.org/2022/06/08/fake-science-the-threat-...

The sad thing is it doesn't take a ChatGPT level intelligence to beat scientific peer review. Journals routinely publish papers that are completely auto-generated gibberish. A simple generative grammar or template splicer is apparently enough. These are articles that are immediately visible as the work of a program at first glance, they wouldn't make it past even the most amateur blog or student newspapers, yet they surface in their thousands in journals that are supposed to be the epitome of accurate knowledge!

Worse, the journal publishers are doing nothing about it. Their current approach to trying to fix the problem is to try and use the work of random CS academics to make "spam filters" for paper submissions. The more obvious solution of having editors and reviewers who actually read scientific papers before they are published appears to be rejected out of hand.

I thought about the AI pollution and I don't think it will matter because we already had the exact same problem with forum spam and low information / bad people (=eternal september) type content overwhelming online discourse. I think maybe combatting AI spam will be the least of our problems because humans do plenty of AI-tier spam already. I think the advent of AI may even be positive because people will start to value real human interaction more. It will be like a treasure cove when you find a forum that is highly curated with real people and you can rely on that being the case. Or (and this is just as likely): Online platforms will go towards requiring real human IDs for participants. AI spam would only be used by companies and advertisers.

Maybe eventually there will be a public understanding that only a foolish child would read a reddit frontpage and expect human content. It will all be auto generated to trap people, like a gatcha game.

> Online platforms will go towards requiring real human IDs for participants.

I just don't see how AI won't be used to manipulate these kinds of barriers. Once AI reaches a point where it can truly equal or surpass humans in terms of operating online, how are we going to prevent it from circumventing those barriers? If AI can generate code from a chat prompt, who's to say it can't solve a captcha in the future? And once that happens (because we all know it will at some point), how are we going to be able to differentiate?

real human ids = passports, bank logins

Ok, but the systems that are responsible for creating those IDs are automated, which means that they can be learned and reverse-engineered. There are lots of passports and bank logins floating around that can be used to train AI.

Do you see the problem now?

they are not automated and require real world steps

Passports contain digitally signed X.509 certificates in their chips. No AI can learn to forge a digital signature (we hope).

So you buy them signed at the source.

The only passport you can buy is your own, right? The signing keys are held by national governments. I don't really understand the threat model here.

A government sells you passports without validation of your identity.

The other problem is that AI can be put in charge of phishing operations. Once you devise the correct prompt to get past the filters, it understands what phishing is, and will quite happily write phishing emails for any audience you care to describe. Combine that with an automatic mailer, and you could just fish for IDs (along all the other profitable stuff), and then use those IDs to spam more etc.

There is a market for KYC'd accounts. Someone operating an AI bot farm posing as Real Humans would just buy these.

> I think stuff like this is going to make it harder for companies to assess candidates, fight fraud and generally operate.

Yikes. Now I imagine a totally unqualified candidate for literally anything feeding interview questions to the chat bot and I don't like it at all.

Even worse: now there is a justification for forcing candidates to solve coding problems on whiteboards, as interviews and coding homework problems will be considered intently suspect.

My single worst interview experience was an on-site five hour marathon of whiteboard coding, with a grumpy senior insisting that the code on the whiteboard be syntactically correct. Nothing screams "we want unthinking ticket crunching machines" like optimizing for candidates willing to focus on writing code by hand for hours on end.

Naturally, I rejected the follow-up interview, but I fear that more companies now are going to demand this nonsense.

Side note: in my personal example, the whiteboard session wasn't the reason I turned them down; I asked every person on the team roughly how many hours a week they worked and not one of them answered the question (instead redirected the conversation towards "you can work from home sometimes!" type answers).

Since then, however, I have rejected other companies trying to ape this style flat out. A short half hour, fine. Five hours? Pound sand, I say.

You know the real issue there? In 5 years that kind of company will be using only CodeGPT instead of hiring humans.

I think any company relying solely on AI to build a tech business in the future is itself at risk. Where's your moat if your business is built entirely on AI licensed from someone else?

In an era where that's possible, the expectation will be for humans to be working hand-in-hand with computers, whether to make superior code or answer better interview questions. The bar will simply be elevated, and you will have to judge candidates on their computer/human synergy. The only time that what you say could be a problem is if the technology to answer interview questions is far superior than that of doing actual work. But then there is the next round of interviews (in-person, etc.). This also kind'of exists today in the form of googling answers while on interview, which for some reason lots of companies don't like, even tho no coder isn't constantly googling on the job.

yeah, agree. I think it will be overall a degenerative process.

More and more content that gets created by machine that is of low quality will get in the way of its own future training.

There will eventually be less and less human made content to train from.

> I think AI is going to force us on some level to reclaim some of our communication to the physical world, if for no other reason than it's going to be one of the only ways we can truly verify that we're talking to another person.

I've been thinking along these lines a lot recently - it seems as though in every field which AI enters, it causes us to return to some extent to the physical world.

“Very coherent, but technical details wrong” covers a great deal of human-generated content as well.

I see a lot of this on the internet already - essentially just SEO spam generated by RNNs, which is good enough to get a plausible click-through, but not good enough to actually be right. I suspect ChatGPT and its ilk are going to just exacerbate that problem by being harder to recognize as generated, and instead tipping into plausible-but-incorrect.

Sounds like the typical article spamming search results already via cheap content farms ...

But yes, will be "interesting" to observe, how such a new wave will make theinternet worse.

> Always remember that almost all of what is being presented here is the work of humans, regurgitated by a very much non-intelligent machine, despite its name.

Then why does it seem to have some kind of theory of computation?

I gave it code to compute a Fibonacci sequence with nonsense names for functions and it immediately recognized the code (explainable by pattern matching).

I gave it a function and told it to modify the function so that it passes a test, and it did it without a problem.

I’ve had it build a function up by feeding it different test cases.

I had it explain kmeans to me, give me a first-pass solution, asked it how to optimize the first solution, had it do that for me …

I don’t know - it feels different. It also feels like it’s 1-2 years away from being the most useful co-worker on any given team and 5-10 years away from putting a number of us out of a job (or at least changing that job so much as to be something unrecognizable to us today)

What's funny is that most of human intelligence is of itself the work of a few select humans regurgitated by the rest of humans.

It is not just regurgitating.

It is synthesizing.

You can ask it to update its answers. You can ask it to evaluate possible solutions, then write the code for one of the solutions. Then write the code to test the code. And so on.

It turns the coder into a curator, editor, and code reviewer.

> It turns the coder into a curator, editor, and code reviewer.

Cool?

Doesn't sound half bad to me. I've enjoyed learning to code more than actual coding. I'd be happy in a paradigm where only code to learn, to practice, to express ourselves and leave the boring bits to the machines.

The only things that really matter:

1) is the end result useful/valuable?

2) did the GPT-based 'coding' process provide any of the following benefits: [reduce cost | reduce time to market | increase quality]?

> The language doesn't completely run, but it was just a two-hour experiment.

Do you mean?

We can look forward to a ChatGPT-frontpage with articles generated by chatgpt, which we will PREFER compared to the real thing.

Next on HN: connecting two ChatGPT accounts together, giving one the assignment of thinking of projects and tasking/guiding another to implement those.

More specifically, making paper clips.

That "attribution of agency" is probably what brought us myths of human-like gods with human-like intelligence that control everything we didn't understand.

More of the same.

when all you know is an agent, everything looks like an agent

Human-like gods were tools - understandable interface.

I think the “it’s just welding together bits and pieces made by humans” is actually a complete non-answer.

From one perspective, that’s what humans have always been doing. We create new things by welding other things together.

From another perspective, that’s not even a bad thing. Every word exists in the dictionary so what value are books? Unless the value is the structuring of all those things that already exist.

If you believe in evolution then you by principle believe in less intelligent entities organizing to make more intelligent entities than their progenitor. In that case Human-kind does not have to be very intelligent to make something much more intelligent down-the-line. Mind the consequence and bias of interpretation.

> We're predisposed to seeing meaning, and perhaps "intelligence", everywhere.

I’m guilty of this with my dog. I can’t help it with her head tilts and deep stares! Her inner monologue is probably less sophisticated than I like to think it is.

Why are you inclined to think that way?

> In fairness, most humans can't either.

This. I think we’re already seeing superhuman performance here, in the sense that many / most people can’t e.g. read a specification for a programming language and write simple programs in that language.

I love the "Show HN: $X created by ChatGPT" We need people seeing what useful things can be done with this new hammer, things that haven't occurred to us yet.

You are jumping to conclusions and it’s leaking into your framing like using the word “regurgitation”

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