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Gitlab’s AI-assisted code suggestions

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Re: Gitlab’s AI-assisted code suggestions

#31

Post by blibble »

ianhawes wrote: post #13

This looks very interesting, but as an FYI using LLMs to do machine translation is a terrible waste of resources. The example on their landing page has a "translate.py" sample which, albeit handy, is not something I would do beyond basic string translations.

it's not doing that, it has generated a dictionary with some values

presumably to be used later to lookup words (crap approach, but it's an LLM, what do you expect)

but it didn't bother to write any code, it's just data

(plus it even managed to screw up the dictionary with double braces)

Re: Gitlab’s AI-assisted code suggestions

#32

Post by olddustytrail »

wizzwizz4 wrote: post #24
colordrops wrote: post #11

Earlier quoted context omitted.

Unless the LLM is cutting and pasting GPL code, I don't see how this differs from an engineer learning to code by referencing open source projects then creating their own project with its own licensing. I'd imagine these models could be tuned or at least a check could be added that no licensed code is being returned.

If someone learns to program by memorising and then re-using blocks of code, they're absolutely doing it wrong – but, also, they should be able to attribute their code. Most of the techniques I used, I've invented myself (or learnt from the standard documentation). When I use a technique that I haven't invented myself, I look up where it came from. Half the time, my version is actually radically different (and my att…

LLMs don't memorize and reuse. They don't really have a memory of any kind. I think the problem is they're more different from human learning than you think.

Re: Gitlab’s AI-assisted code suggestions

#33

Post by hospitalJail »

mattl wrote: post #30
hospitalJail wrote: post #26

Earlier quoted context omitted.

I'm so torn on GPL... It prevents bad actors like Apple from ripping off people's philanthropic labor, but it also prevents me from ripping off people's labor. It also focuses effort onto the FOSS project. I like PyQts solution of having GPL or buy a commercial license. I suppose I still like MIT/Apache style the best. Even if someone rips them off, we didn't lose progress.

Why do you want to rip off people's labor? What's stopping you from incorporating it into your own work?

I mean:

Compile already working code, slap my logo on it, spend millions of dollars marketing it with young good looking adults subliminally letting you know that you aren't cool unless you give me money.

Re: Gitlab’s AI-assisted code suggestions

#34

Post by SparkyMcUnicorn »

mmcclure wrote: post #7
ases wrote: post #4

All the code examples on this page are doubling any brackets ([], {}, ()). How have they managed that? Not a fantastic first impression of its capabilities...

I'm going to give them the benefit of the doubt and assume this is a marketing site problem and not a product problem, but either way, not a good look. Reminds me of Google's big Bard announcement including a wrong answer in the image.

Gitlab is using Google's Vertex Codey models/API for the code completions.

Showcasing innacuracies in AI responses must be a Google requirement.

Re: Gitlab’s AI-assisted code suggestions

#35

Post by cj »

jedbrown wrote: post #29
RadiozRadioz wrote: post #3

Crucial: do they train on GPL code? If I am to use this tool, I must abide by the license terms of the training data. Even if it is found that the GPL does not cover LLM responses as derivative works, I would prefer to be on the safe side and refuse to use models trained on software with non-permissive licenses unless I am building Free Software.

Even MIT licensed code requires you to preserve the copyright and permission notice. If a human did what these language models are doing (output derivative works with the copyright and license stripped), it would be a license violation. When humans want to create a new implementation with clean IP, they have one team study the IP-encumbered code and write a spec, then a different team writes a new implementation acco…

Has anyone been able to create a prompt that GPT4 replies to with copyrighted content (or content extremely similar to the original content)?

I'm curious how easy or difficult it is to get GPT to spit out content (code or text) that could be considered obvious infringement.

Tempted to give it half of some closed-source or restrictive licensed code to see if it auto-completes the other half in a manner that is obviously recreating the original work.

Re: Gitlab’s AI-assisted code suggestions

#37

Post by ENGNR »

hospitalJail wrote: post #33
mattl wrote: post #30

Earlier quoted context omitted.

Why do you want to rip off people's labor? What's stopping you from incorporating it into your own work?

I mean: Compile already working code, slap my logo on it, spend millions of dollars marketing it with young good looking adults subliminally letting you know that you aren't cool unless you give me money.

At least you’re honest!

Re: Gitlab’s AI-assisted code suggestions

#38

Post by littlestymaar »

cj wrote: post #35
jedbrown wrote: post #29

Earlier quoted context omitted.

Even MIT licensed code requires you to preserve the copyright and permission notice. If a human did what these language models are doing (output derivative works with the copyright and license stripped), it would be a license violation. When humans want to create a new implementation with clean IP, they have one team study the IP-encumbered code and write a spec, then a different team writes a new implementation acco…

Has anyone been able to create a prompt that GPT4 replies to with copyrighted content (or content extremely similar to the original content)? I'm curious how easy or difficult it is to get GPT to spit out content (code or text) that could be considered obvious infringement. Tempted to give it half of some closed-source or restrictive licensed code to see if it auto-completes the other half in a manner that is obvious…

I don't know about GPT-4 but you could get ChatGPT to spit Carmac's Fast Inverse square root with the comments and all (I can't find the tweet though…)

Edit: it wasn't ChatGPT but Copilot see https://twitter.com/mitsuhiko/status/1410886329924194309

Re: Gitlab’s AI-assisted code suggestions

#39

Post by johndough »

nonameiguess wrote: post #17
RadiozRadioz wrote: post #3

Crucial: do they train on GPL code? If I am to use this tool, I must abide by the license terms of the training data. Even if it is found that the GPL does not cover LLM responses as derivative works, I would prefer to be on the safe side and refuse to use models trained on software with non-permissive licenses unless I am building Free Software.

I guess we'll see what the legal system says, but it's nearly impossible for me to imagine how anyone could ever justify saying a system trained on potentially millions of separate open-source projects can then be said to universally produce derivative works of any specific project it trained on. On the other hand, if a developer using this tool then goes and tells it "please write me a C library in the style of GNU…

GitHub Copilot copying Quake's fast inverse square root function is a famous example where Copilot copied GPL-licensed code only given the comment

    // fast inverse square root
https://news.ycombinator.com/item?id=27710287
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