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GitHub Copilot loses an average of $20 per user per month

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Re: GitHub Copilot loses an average of $20 per user per month

#171
post #58

Earlier quoted context omitted.

For some developers for sure, but not all. I am a senior developer with +20 years of experience and I find Github Copilot amazing. It significantly boosts my productivity. I do not expect the world from it, and I do run into limitations, but it helps me tremendously to be productive in languages and tools which I have low/no familiarity. I think Github Copilot paired with ChatGPT fails the most in idiosyncratic code…

Which language? New or maintenance code?

JavaScript/TypeScript. New code generally.

I find that ChatGPT/Github Copilot knows certain types of patterns, libraries better than others. If you get it to suggest the path forward, and then do that path, it will be better at maintaining that code. Basically ChatGPT sort of has happy paths which you want to follow.

Or you could say it in another way: AI designed code / architecture is easier for an AI to maintain.

Re: GitHub Copilot loses an average of $20 per user per month

#172
post #113

Earlier quoted context omitted.

> We start raving about them, so other people take a look expecting… If that’s what you want to call it. I see hypemen overpromising and product underdelivering. And when pressed about specifics, attempts to drown queries in jargon or an ass-covering retreat to treating it like it’s just a tech demo not intended to be used for anything ever.

And management consultants solving every problem in the world by adding a “AI” box in their powerpoint flow diagram.

Yep, just like "crypto" before that, and "big data" before that and "social media presence" before that and so on and so forth...

Re: GitHub Copilot loses an average of $20 per user per month

#174
post #17

The article says Microsoft wants computers to one day have Neural Processing Units (NPU) like most have GPUs. If that led to faster suggestions for copilot, I'd be all for it. Right now, a GPU is an NPU. Does anyone how an NPU would differ from a graphics card?

isn't it what neural engine on apple silicon is?

Integrated vs Discrete.

Re: GitHub Copilot loses an average of $20 per user per month

#175
post #63

Earlier quoted context omitted.

I think the problem is that they aren’t mind-blowing, but an improvement. I resent some LLM implementations on principle, but decided to give these code helpers a try. What I found was they’re reasonably bad, and I kept telling them the solution doesn’t work, only to be presented with a little tweak. So I don’t see the point of outsourcing my thinking, I’d rather remain intelligent and do the search/try/tweak on my o…

> I think the problem is that they aren’t mind-blowing, but an improvement. You seem to be doing what GP is pointing out. GP's claim is that the relative improvement itself is mind-blowing, not that the tech is mind-blowing in an absolute sense. I tend to agree: much of the detraction hangs on current-state rather than a probable potential-state informed by recent relative advancements. In other words, many proponent…

See, I'm very skeptical that we can guess at the potential, because so much of it depends on research and figuring out better ways to do things going forward, and successful research programs are very unpredictable.

I feel like people are taking Moore's Law, which is definitely a real thing, and thinking that everything else is going to advance like semiconductors did, and I just am not seeing it in any other field. It's not true in software development (where gains, such as they are, are more linear than exponential) its definitely not true in rockets or civil engineering or steel or anything like that. So I am afraid a whole lot of people are expecting Moore's Law type improvements in AI, when really AI advances more like punctuated equilibrium: a sudden dramatic improvement, then a long period of consolidation and stasis, then another sudden dramatic improvement, often in a totally different unpredictable area.

But I've just been keeping tabs on AI since the hot way to do it was Expert Systems back in the 1990's, and I'm aware of its history since Norbert Weiner wrote Cybernetics back in 1947, and this seems to be a repeating pattern: a single major breakthrough (in this case, honestly, the combination of large quantities of data with NN's- with driving and natural language being the two easiest to get, and so the most prominent examples) followed by a lengthy fallow period where not much appreciable progress happens, then another breakthrough, often orthogonal to where earlier breakthroughs happened.

Re: GitHub Copilot loses an average of $20 per user per month

#176

Thus, the price of Github Copilot is going to go up, 2x to 5x. For all of the criticism of Github Copilot, for a lot of developers (but not all), the value Github Copilot is incredibly high, much more than $20/month. The current rock bottom pricing is low compared to the value provided for those users. As such there is a big opportunity to multiply the price here being charged. Probably an increase between 3x to 5x.…

I happily pay it for $10 a month, but I won’t pay $20. My company could pay it for me though.

Re: GitHub Copilot loses an average of $20 per user per month

#178

Earlier quoted context omitted.

Are we talking about Copilot in particular or AI code assistants in general? The value, for me, is extremely high. My teammates feel the same. Our shared opinion/experience is that ChatGPT 4 is better than Copilot in general but Copilot shines in-editor because it's aware of your project. So we use both in tandem. They mostly use Chat GPT and I split about 50%/50%. (Note: I'm using the Copilot X beta which I believe…

> If I need to traverse a tree or list or something, I'm letting AI write that code. Could I write it myself faster? No, and it's going to have an off-by-one error some non-zero portion of the time if I write it. Many languages/companies have existing well understood solutions that _won't_ have errors. Maybe that is the disconnect? I can't remember the last non-interview time I had to write a non-trivial traversal.

    Many languages/companies have existing well understood 
    solutions that _won't_ have errors.
I admit: I chose poor examples in my above post.

In a literal sense it has been years since I wrote a tree or list traversal by hand and I would be very surprised and concerned to see a PR where somebody is doing it by hand rather than using a library.

But, I hope my meaning comes through despite that. I mean the sort of mundane "iterate through a thing, and do a thing with some of the things" sort of code that many/most of us are writing on a regular, hour-to-hour basis.

    Maybe that is the disconnect?
Maybe! Another disconnect might be the level of polyglot one is expected to be.

I'm generally a "full stack" web developer (currently switching between Python and Ruby on the backend) and I don't mind admitting: front end crap changes fast enough that I can't possibly keep up with it. In my experience nobody is expert in the whole stack. Altogether it's just a really big surface area of Shit I Need To Know. AI is very welcome here for me.

Other coders might have a smaller surface area of shit they need to know, and they already know it inside and out, and therefore see no real value add from an AI buddy who is not correct and optimal 100% of the time.

Re: GitHub Copilot loses an average of $20 per user per month

#179

AI is such a huge expectations dichotomy. For those of us used to the continual disappointment that pre-LLM AI was, the current crop of LLM's are amazing, mind blowing things. We start raving about them, so other people take a look expecting that modern LLM's are the greatest thing since sliced bread. They're not quite that, so we get HN comments complaining that AI sucks.

>> For those of us used to the continual disappointment that pre-LLM AI was, the current crop of LLM's are amazing, mind blowing things.

Aren't you overgeneralising a bit? Not even I would say that CNNs for image classification, or Deep-RL for board game-playing are a "continual disappointment" and they certainly predate LLMs. Are you talking about NLP? Even Neural Turing Machines were quite capable in language pairs with large parallel corpora (and similar linguistic structure).

Basically, what do you mean by "continual disappointment"? What I'm aware of is an incessant hype crescendo that crashing over everything like a relentless wave.

Re: GitHub Copilot loses an average of $20 per user per month

#180
post #125

Earlier quoted context omitted.

The quote from the article says "more than 1.5 million people have used it and it is helping build nearly half of Copilot users’ code" Not a native speaker, but to me this sounds much more ambiguous than up to 50% of code is produced by Copilot. Also, how different from previous solutions is this actually? I use autocomplete and code snippets extensively. Never measured it , but I wouldn't be surprised if my IDE had…

It doesn't sound ambiguous to me. It says that those people have Copilot enabled while they write more than half of their code. AKA it's on the editor they use for most things. It doesn't say anything about its value.

half of co-pilot users' code, not half of all users' code.
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