My brain is already negatively impacted having to juggle 3 separate package managers, know the syntax and inputs for 17+ different dotfiles in a repo and then actively context switch between at least 3-4 languages on a daily basis. I counted it up recently and I've built products in at least 20 languages over the past two+ decades. At some point you really just can't effectively compartmentalize it all and context switch perfectly. I try by using different fonts+colors per lang etc but it still is hard. AI has been a net win for syntax recall just by giving it gentle nudges towards intent.

What I meant was: Will you lose it if you don’t use it?

Maybe you won’t, I am not certain. Or maybe you will and you don’t see it now because the “net win for syntax recall just by giving it gentle nudges towards intent” relies on your hard earned ability to understand the code which is gained partly through exercise. You’ve already done your exercise.

I wouldn’t form an opinion just yet. For now we can ask the questions.

Edit: wording of the first sentence for clarity

Maybe we will have a mixed result similar to ORM example. It can lower the barriers to entry, which is good, but won’t eliminate the need for deep expertise. At least initially.

I've done a similar number of platform jumping but I honestly don't remember when I've used more than 3 or 4 at the same time. Like I was really into Clojure for ~1 year back around ~2010 - if you put me on a clojure project I'd be lost for a month. I wouldn't need to get over LISP and functional programming mindset again but the details are lost.

At this point I rarely see big paradigm shifts and it's just picking up the details + connecting with things I already know. I've outsourced remembering details to Google :)

I agree but there is a certain "god of the gaps" process that's happening here.

To me it seems like what's been achieved so far is "encoding" into natural and programming languages. These models can't reason and e.g., can't pass a Turing test. If you play with GPT-3 or ChatGPT enough you can definitely get it to fail on a task a human would succeed at.

When models so far have achieved "reasoning" behavior, usually it's in conjunction with a classical algorithm -- for example AlphaZero used a model to evaluate chess positions but then ran a tree search algorithm to decide what move to play.

I think if LLMs can be combined effectively with some kind of computation process like in AlphaZero or some kind of "chains of thought" [1], then we'll see them do things we'd call reasoning.

Whether to be optimistic or pessimistic about AI depends on the final "gap" -- whether there is an irreplicable/noncomputable/etc. property of human consciousness other than qualia (i.e., if "understanding" is hard). If not humans will become obsolete, so I pray the answer is yes.

[1]: https://ai.googleblog.com/2022/05/language-models-perform-re...

First I tried it on a bunch of programming topics -- it definitely gets in the right ballpark, but then the details are frequently wrong.

I asked which languages have the F# |> operator, and it told me that OCaml, Elixir, Haskell and Scala do. 2 of them are correct, and 2 appeared wrong, so I googled it.

After Googling, then I asked it specifically if Haskell does, and it says no. I ask it if Scala does, and it apologizes for its earlier mistake.

It gave me a good although slightly shallow answer about how PyPy works, but then fell down hard for a prolog type checker, and a few other programming queries. It doesn't understand the question.

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It is generally very mealy-mouthed and vague. It often doesn't answer the question directly, but just tells you what it happens to know in the ballpark.

I like another framing I saw on Twitter -- it's "mansplaining as a service". If you want someone to confidently explain things you didn't really ask about, and be frequently wrong, that's kinda what it does!!

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After programming, I asked it about Black Sabbath, UFC, travel and biking, health, and got similarly vague/slightly incorrect answers.

It confabulates A LOT.

The best I can say is that Google is filled with spam now, so chatting with ChatGPT was a relatively fun and focused experience, after I took into account the fact that it is not "honest" and just trying to "please me" with closely related words.

I honestly don't get the hype, and I feel like there must have been some coordinated marketing aimed at me ...

If this chat is representative of what it can do for programming, then I think this article saying that "programmer salaries will be affected by LLM" is very weird.

It is assuming something that simply has NOT happened!

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I mean even Geoff Hinton (who I respect) said several years ago that "we should stop training radiologists", and that plainly did not happen. Likewise with Elon and the fleet of self-driving taxis.

I'd honestly be surprised if someone wants to argue that a tech company staffed with LLMs + a few smart people is NOT like those predictions. Of course the blog post doesn't give a time frame, so it can't be falsified. But it appears to be nonsense.

(FWIW it doesn't matter to me personally, as I left the industry several years ago. Also FWIW I did work a little bit on deep learning, when the hype was in its upswing.)

I agree that a lot of it is anthropomorphism -- projecting some kind of intelligence, knowledge, or intention on what is really a big, expensive bag of data organized to respond to inputs.

Maybe there are other models that are better, but I was really, honestly not impressed with ChatGPT. Maybe people were hyping it too much for the last several weeks, and inflated my expectations.

i guess one difference might be that i also tried a variety of tasks where confabulation was called for, like making up games and getting it to play them with me.

all of this certainly does seem farther from productizability than the optimists admit... it tantalizingly 'almost works' in so many domains, but despite the rate of progress, its not obvious at all to me that it will soon converging on the reliability which is necessary for robust application.

playing with the tech in more creative areas has certainly expanded my mind as to what is and what may become possible, and i think this is true of the general reaction as well... it's the flashes of strangeness and potential, the weird use cases like simulated command lines and ascii art games, the cat-and-mouse of prompt injection... not hard to let your imagination run wild... depending on how much disbelief you're willing to suspend.

Still impressive, but if you had a picture with dogs sometimes a dog head would be pasted on top at the wrong angle. Confabulation is a great term for it IMHO.

But I can't see how people aren't impressed, we couldn't do this a few years ago, and surely we will build on top of this in coming years.

- taking point form, or messy notes, and converting it to full sentences/paragraphs. Useful for things like writing blurbs, longer emails, proposals. Naturally, it does veer towards cliche, so you kind of have to massage it back after.

- getting a bash script started in the right direction. I'm always fuzzy on bash syntax because I don't use it all the time. ChatGPT will usually screw up some details, but those can be fixed

- getting a general overview of a new topic area like a new software library, or say a historical period

It's like a really smart sheep dog or a junior junior carpenter. It's currently helping me refactor a .NET app to a trending pattern, not because it know how to do that exactly or which pattern is better, but because it doesn't tire out at the "boring" parts like I do, and it knows the difference (most of time) between IQueryable and ISomething that I just can't bother to google for the Nth time.

Stop anthropomorphizing computers, they hate that!

Goddamn do I hate this industry. I work hard to sow dissent in my blue-chip, VC startup though. Guerrilla tactics. And I get to do it raking in a quarter mil a year in my underwear.

Wrong, that research only shows that when you use a GPS, you don't learn routes as quickly. That is only equal to "impacts brain function negatively" in a narrow sense, which you should specify rather than use such a broad and scary-sounding phrase!

Brain function being negatively impacted is not scary on its own and not necessarily permanent.

I didn’t mean to scare you. It’s likely you are confusing the above phrase with “your brain will be altered forever” which is not what it means.

To be fair, this could be said of a surprising number of the developers I've interviewed too, and I checked -- they were hired by someone.

I wonder how code completion and syntax highlighting have altered the brains of programmers negatively as well.

Also there's distinct project structure difference between users of tree style project navigation vs find-anywhere or editor tabs vs modal windows/buffers. I mean, the influence is not negative, at least not obviously, but the deformation is there.