If this is a con, then consider me a mark.
If this is a con, then consider me a mark.
I think something similar is going on here? For some subjects and some questions, ChatGPT acts like a co-worker who has read all the manuals, and that's enough.
Note: I’m aware UUIDs can contain the time but the intent was the UUID was invariant in the process and it would move to another file once it got to a certain size.
Of course, we're going to find some way to fuck it up with advertising, but that's because we live in the Terran Empire timeline.
I told it that "hey, you forgot to do the addition in that code" and it promptly corrected itself.
Personally, I don't consider that terrible given what I was asking it.
I suspect it's just a bias we have, most people aren't doing or creating anything, they aren't solving problems or learning new things constantly like engineers do, so chatgpt feels useless to them.
Or perhaps the problems we want to talk or learn about are just easier for an ai to answer than the things they want out of it,
or we are just better at asking the right questions to extract the value out of it, similar to how you learn to use Google correctly to find something.
I don't know I'm really confused about how some people think it's so worthless.
But when you start playing with these things, finding out where they’re useful, and how to make use of them, they can do very impressive things.
Maybe because either they believe that ChatGPT is worthless, or they have to deal with the fact that their knowledge is becoming worthless (or, at least, worth less).
Personally I find it useless to see a machine as a colleague when it is not better in any way then a colleague, in the same way I don't see a hammer as a very punchy workmate. If I want to have a conversation about something I'll go talk to a human, when I interrogate a database I expect it to be better then a random human.
> Or perhaps the problems we want to talk or learn about are just easier for an ai to answer than the things they want out of it
I think the ABOVE two lines captures the real CORE of why they are two big groups of ChatGPT : supporters and haters
For technical people who are in coding, we may spend 20 minutes with many suggestions to get the final correct code. We test the code and Check-in into github and we EARNED a part of LIVING for that day (as employee).
Now take non-technical person, he is writing an article. He may spend one hour giving various suggestions to complete the article. At the end the article is OK, but not the best. He can not send it to some magazine or news paper, because it is not THE BEST. So in order have an article to have it accepted, he needs to have his ORIGINAL thinking. So in that sense ChatGPT is not SO helpful for him, for that one hour spent he feel ChatGPT is a Conman.
The point I am trying to make: for ChatGPT to be useful for a Technical person with a piece of code, ChatGPT does not have to be ORIGINAL thinker and produce the BEST, it can be average and It has existing template( previous code which workd), all it need to figure out is how to get to that existing solution.
There are two distinct groups of opinions regarding the usefulness of ChatGPT: supporters and detractors. These differing perspectives stem from the varying needs and expectations of individuals in different professions.
For technical individuals, such as coders, the process of finding the correct solution to a problem can take a considerable amount of time. ChatGPT can be extremely helpful in streamlining this process by suggesting code snippets that have worked in the past, reducing the time spent on trial and error. In this sense, ChatGPT does not have to be an original thinker or produce the absolute best solution, as long as it helps the coder to reach a workable solution efficiently.
However, for non-technical individuals, such as writers, the focus is often on originality and creativity. ChatGPT may not be as helpful in this context because it is limited to suggesting based on pre-existing templates and previous examples. A writer who spends an hour relying on ChatGPT's suggestions may not end up with the best possible article, which could result in a feeling of dissatisfaction. In this scenario, the writer may feel that ChatGPT is not truly helping them to reach their full potential, leading them to view it as a hindrance rather than a help.
In conclusion, the usefulness of ChatGPT is dependent on the individual's specific needs and expectations. For those in technical fields, it can be a valuable tool, while for those in more creative professions, its limitations may outweigh its benefits.
I asked it if it could help with my anxiety regarding to my first therapy session it gave me an actionable 6 steps plan to help me reduce my anxiety by actively preparing for that dreaded first session. Not only I am less stressed about that session but I am also a lot more prepared and likely to benefit from it.
If it was available purely offline I would probably replace the therapy with chatGPT entirely, but I dont trust the great AI in the cloud, it whit something I would not share in a forum so no robot psychotherapist for me, not yet at least ...
Does copilot do anything differently other than being available as an IDE extension?
Also, it can read all of my other code (in the project?) so it seems more context aware.
It makes mistakes tho. For example, if you have two fields in a struct that could have been used and their names are very similar and they have the same type, then Copilot could use the wrong one. This is effectively a typo, except in code that was autogenerated, and it often takes a LONG TIME to debug a typo like this....
Ideally, you would be in a language with a more expressive type system (like Ocaml) so that those two fields have different types and such a typo cannot be valid.
The thing is that this doesn't extend to situations where, say, a common summary of a topic isn't true when one looks at things in more detail.
For example, Earnest Hemingway is know for "short, concise sentences" and ChatGPT will give this description when asked about his style. But Hemingway in fact used complicate compound sentences fairly frequently - sentences by that a Strunk and White style definition should be broken up. ChatGPT will not admit this even when prompted (though I think most actual critics say this), and it will recommend the long sample sentence I give it be broken up.
It is what I love most about it
Ask it if it is human
So in other words you basically spent just as much time and effort as if you did it yourself?
It could be the same time spent, but not the same amount of cognitive effort.
Stories itt can as well be boiled down to “I fed it with corrections for some time and it didn’t f..k up this last time and finally included everything into the answer”. What makes you think it would not do just that better or quicker?
Edit: Another probably highly related question is, can it answer “I don’t know this / not sure about these parts”? Never seen that in chat logs.
I don’t really understand how it works, how its iterations are different or what the roadmap is. But what I managed to learn (better say feel) about LLMs isn’t very consistent with such linear predictions.
Well, maybe it will use downvotes as anti-prompts? Existing sources must have had votes too, but it was probably only a subset. Maybe the current iteration didn’t rank by vote at all, so the next one will really shine? Guess we’ll see soon.
Indeed. I wonder what happens as available training data shifts from purely human-generated (now) to largely AI-generated (soon). Is this an information analogue to the “gray goo” doomsday that an uncontrolled self-replicating nano device could cause?
>can it answer “I don’t know this” Such a fabulous question. This statement likely appears infrequently in the training data.
A lot of models were trained to provide some quantifiable output 100% of the time, even if that output was wrong. Ie image recognition models "82.45% certain that is a dog", whereas it makes _all_ the difference for it to be able to say "82.42% certain that is a dog and 95.69% certain I don't know what that is" to indicate that the image has many features of a dog, but not enough for it to be more certain that it is a dog than isn't. It's the negative test problem I guess; us devs often forget to do it too.
In a way I wonder if that's how some of the systems in our brains work as well; ie we evolved certain structures to perform certain tasks, but when those structures fail to determine an action, the "I don't know" from that system can kick back into another. Thing like the fear response: brain tries to identify dark shadow & can't, kicks back to evolutionary defence mechanisms of be scared/cautious feel fear as it's saved the skins of our forebears.
Yeah we can all write this stuff by hand but it's incredibly exciting; when it first came out I was asking it to write snippets of JS for stuff, additions, removals, asking it to write unit tests and then update them when the overall code changed and it maintained several different "threads" of conversation all related to a singular exercise just fine. Sure it's not perfect, but it's kind of cool having a super junior dev who happens to have instant access to most documentation around at the time in its head.
You absolutely cannot deny the fact that chatGPT produces a lot of bullshit.
But at the same time you absolutely cannot deny the fact that it produces a lot of real answers to very complex questions.
Both the ability to make shit up and give real complex answers are amazing achievements.
I think a lot of people haven't picked up on the fact that in both cases chatGPT actually understands what you are telling it.
This is something that I haven't seen mentioned yet.
The stunning aspect of ChatGPT is that it seems to understand* the nuances of what I'm asking. Yes, sometimes it spews bullshit, but the bullshit is still trying to address my questions, no matter how odd.
* I suspect that "understand" may not be the correct word here, depending on your definition. But at the very least, it can parse the nuances of my questions.
In the same day and age, ChatGPT can respond to a statement like "actually it's a cat" with "yes, my apologies for the error, [repeats a lot of stuff with corrections]". In the process it's recognizing that your response is a correction, what "it" refers to, some of the implications of what that change means, and that you are expecting it to issue a response that amends its previous statements. It's several generations ahead of the state of the art.
There's no other word for what's going on. The inputs and resulting outputs show something indistinguishable from understanding.
If we choose to define "understanding" as some deeper internal process well that's a deadend because we don't even know the meaning of the term "understanding" from the context of the human brain.
So more or less from the inputs and the outputs there's only one word that describes what's going on. It "understands" you.
Sometimes I have to clarify "But this will also output x, on line 3, but I really want it to output y". And it gives a correction based on my clarification.
How do you know it was correct? Because you checked it’s entire output manually and determined it probably wasn’t too wrong?
So what happens if you now trust it to write firmware for some difficult old timey hardware that nobody understands anymore. It seems correct. But then it actually was just making it up and the coolant system of the power plant breaks and kills 20,000 people.
How well would anyone do?
Would you trust me?
Hire me
But I would suggest not using a LLM to make nuclear reactor control system code, just like Java.
If you treat ChatGPT as the expert, you’re going to be disappointed. But when YOU are the expert & can verify what ChatGPT outputs, then it makes a fantastic automated reference.
If you cannot….well, that is where it shines at con artistry
This is also how humans learn, although we can do this process purely internally.
Both package and component are made up bullshit, I kid you not. Did you try to actually code and test those graceful termination parts?
Maybe a more fitting question to ask when evaluating the technology as a tool for programmers is if it is better than searching Stack Overflow alone?
I already did before I read this part.