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GitHub Copilot

copilot.github.com

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Re: GitHub Copilot

#901
How does this compare to tools like resharper? Is it comparable? Is this the next generation of such tools? Or does it work completely differently?

Re: GitHub Copilot

#902
post #351

I've been using the alpha for the past 2 weeks, and I'm blown away. Copilot guesses the exact code I want to write about one in ten times, and the rest of the time it suggests something rather good, or completely off. But when it guesses right, it feels like it's reading my mind. It's really like pair programming, even though I'm coding alone. I have a better understanding of my own code, and I tend to give better na…

Maybe it's just because humans are not as creative as they think. Whatever you do, thousands of others have done the same already. So no need to pay a high level programmer, just a mediocre one and the right AI assistant gives the same results.

With an AI assistant, in the best scenario, you'll get a "wisdom of crowds" effect on implementation details and program architecture. At worst, you'll get a lot of opinionated code bloat and anti-patterns as suggestions.

For most backend programming jobs, the challenge is not in writing complex code but figuring out what the business wants, needs and should have in the first place and distinguishing between them. Figuring out how to integrate with existing systems, processes, fiefdoms and code. Knowing when to say yes and no, how to make code future proof, etc. This is a task fundamentally unfit for what we currently call "AI", because it's not actually intelligent or creative yet.

On the frontend, it becomes even more nebulous. Maybe Copilot can suggest common themes like Bootstrap classes for a form, CSS properties, the basic file structure and implementations for components in an SPA, etc. As I see it, the main challenge is in UX there, not the boilerplate, which again makes it about understanding the user, figuring out how to make UI feel intuitive, etc. Again: unfit for current AI.

I cannot offer any opinion on the utility for actually complex, FANG-level code, for lack of experience.

Re: GitHub Copilot

#903

Gigantic caveat. > I agree to these additional telemetry terms as part of the technical preview

Right. If you’re comfortable giving access to your source files to GitHub+OpenAI, then go for it. I’m not sure how this would apply to secret keys or flat files with customer data/PII, but in any case that makes it a non-starter for me. Their “Please do not share this URL publicly.” Banner at the top of the page which disclosed this info makes my skin crawl a bit… If I were only working on public projects I would be…

> Am I being to paranoid here?

No.

They already admitted that they send telemetry of the code you give it and its training set already has personal information in it anyway, despite what is being hyped up here by the fanatics, even when someone said that 'Copilot guesses the exact code I want to write about one in ten times' [0]

No thanks and certainly no deal.

[0] https://news.ycombinator.com/item?id=27676845

Re: GitHub Copilot

#905

Earlier quoted context omitted.

It could start to replace us in 20 years. Or reduce. It is exciting for now

Until it automatically knows when and how it's wrong, you'll still need a human to figure that out, and that human will need to actually know how to program, without the overgrown auto-complete. May or may not reduce the demand for programmers, though. We'll see.

But that's exactly what you are doing as a programmer who uses it. If you autocomplete using it and then fix the code, you are literally telling it what it got wrong.

Re: GitHub Copilot

#906
post #306

Earlier quoted context omitted.

I’ve also been using the Alpha for around two weeks. I'm impressed by how GitHub Copilot seems to know exactly what I want to type next. Sometimes it even suggests code I was about to look up, such as a snippet to pick a random hex color or completing an array with all the common image mime-types. Copilot is particularly helpful when working on React components where it makes eerily accurate predictions. I see techno…

Has anyone used Copilot with a more succinct language? It appears to only automate boilerplate and rudimentary patterns, which while useful in repetitive low signal to noise ratio languages like React or Java, sounds less appealing if you're writing Clojure.

I've not used Copilot but I've experimented with two other AI driven autocompletion engines in Java and Kotlin. In both cases I uninstalled the plugins due to a combination of two problems:

1. The AI suggestions were often less helpful than the type driven IDE autocompletions (using IntelliJ).

2. The AI plugins were very aggressive in pushing their completions to the top of the suggestions list, even when they were strictly less helpful than the defaults.

The result was it actually slowed me down.

Looking at the marketing materials for these services, they're often focused on dynamic languages like Python or JavaScript where there's far less information available for the IDE to help you with. If you've picked your language partly due to the excellent IDE support, it's probably harder for the AI to compete with hand-written logic and type system information.

Re: GitHub Copilot

#907
post #398

I don't think we need to start looking for new career paths yet. This example has a few bugs and it took me longer to track them down than it would have to write it myself: #!/bin/bash # List all python source files which are more than 1KB and contain the word "copilot". find . \ -name "*.py" \ -size +1000 \ -exec grep -n copilot {}\; "-exec grep -n copilot {}\;" needs to have a space before the semicolon otherwise f…

I am not surprised. Bash is notoriously unreadable.

There is no bash code in that script, it's POSIX find.

Re: GitHub Copilot

#909

Four years later: your AI replacement? When do you all predict something like this will happen?

I'm not at all worried about AI taking over software development. In all likelihood, what you'll see instead are AI plugins in IDE editors which just assist in a much more advanced way than the intellisense we have now. Having machines code out the business logic is very much so something that would be less efficient than having a person do it. Realistically, it just means that, rather than your coworker code-reviewi…

I think programmers will just write model and tests in the end. The rest will be generated.
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