GitHub cuts AI deals with Google, Anthropic • Hacker News Board

Re: GitHub cuts AI deals with Google, Anthropic

#631

Post by fragmede » Wed, Oct 30, 2024, 12:22 PM UTC

Cthulhu_ wrote: post #627

scubbo wrote: post #479

Earlier quoted context omitted.

> Me reviewing AI code is no different from me reviewing anyone else's code. I take your point, and on the whole I agree with your post, but this point is fundamentally _not_ correct, in that if I have a question about someone else's code I can ask them about their intention, state-of-mind, and understanding at the time they wrote it, and (subjectively, sure; but I think this is a reasonable claim) can _usually_ dete…

> Asking AI for explanations tends to lead to extremely convincing and confident false justifications rather than an admission of error or doubt. Not always true, AI can realise their own mistakes and they can learn. It's a feedback loop system, and / but as it stands this feedback of what is good and bad is provided by end-users and fed back into e.g. Copilot.

That loop is not a short one though. LLMs don't actively incorporate new information into its model while you're chatting with it. That goes into its context window/short term memory. That the inputs and outputs can be used when training the next model, or for fine tuning the current one doesn't change that the distinct steps of training and inference.

Re: GitHub cuts AI deals with Google, Anthropic

#632

Post by kamaal » Wed, Oct 30, 2024, 12:22 PM UTC

thih9 wrote: post #221

I use cursor and its tab completion; while what it can do is mind blowing, in practice I’m not noticing a productivity boost. I find that ai can help significantly with doing plumbing, but it has no problems with connecting the pipes wrong. I need to double and triple check the updated code - or fix the resulting errors when I don’t do that. So: boilerplate and outer app layers, yes; architecture and core libraries,…

>>I need to double and triple check the updated code

Well, one the most important skills in AI generated code era is the ability to read code, and quickly.

Another thing is, writing smaller functions helps.

Re: GitHub cuts AI deals with Google, Anthropic

#633

Post by sotix » Wed, Oct 30, 2024, 12:24 PM UTC

This sort of makes me sick as a software engineer with licensed code on GitHub. Am I understanding correctly that they have trained data on my code despite my license? Do I receive monetary payment from the deal? Or have I misunderstood this?

Re: GitHub cuts AI deals with Google, Anthropic

#634

Post by else42 » Wed, Oct 30, 2024, 12:35 PM UTC

sotix wrote: post #633

This sort of makes me sick as a software engineer with licensed code on GitHub. Am I understanding correctly that they have trained data on my code despite my license? Do I receive monetary payment from the deal? Or have I misunderstood this?

How is that different to a human reading your code and building up their experience? Is reading code now also covered by a license? It does not reproduce your code 1:1.

Re: GitHub cuts AI deals with Google, Anthropic

#635

Post by remedan » Wed, Oct 30, 2024, 12:36 PM UTC

sotix wrote: post #633

This sort of makes me sick as a software engineer with licensed code on GitHub. Am I understanding correctly that they have trained data on my code despite my license? Do I receive monetary payment from the deal? Or have I misunderstood this?

I'm pretty sure that to upload your code to GitHub, you have to agree to their terms of service, which potentially give them all sorts of rights to your code. This creates a special relationship between you and GitHub that is separate from the license you assign to your project.

Re: GitHub cuts AI deals with Google, Anthropic

#636

Post by kamaal » Wed, Oct 30, 2024, 12:36 PM UTC

hhdhdbdb wrote: post #466

AIorNot wrote: post #427

Reviewing these conversations is like listening to horse and buggy manufacturers pooh-poohing automobiles: 1. they will scare the horses. a good team of horses is no match for funky 'automobile' 2. how will they be able to deal with our muddy, messy roads 3. their engines are unreliable and prone to breaking down stranding you in the middle and having to do it yourself.. 4. their drivers cant handle the speed, too ma…

I dont see a young/old divide when it comes to AI. Altough there is a young/old divide in familial responsibilies and willingness to be a chip on the VC's roulette table.

There is a young/old divide.

There was a similar divide in the 2000s when Google Search got ubiquitous and writing code got easier than ever. I know a lot of people quit to become 'managers' because they didn't want to fix code which most of the times was being copied from the internet and pasted. Similar arguments on correctness, verbosity and even future maintainability were made. Everybody knows how that went.

Millennials are just gradually turning into boomers as they enter their 40s.

Re: GitHub cuts AI deals with Google, Anthropic

#637

Post by strangescript » Wed, Oct 30, 2024, 12:40 PM UTC

else42 wrote: post #634

sotix wrote: post #633

This sort of makes me sick as a software engineer with licensed code on GitHub. Am I understanding correctly that they have trained data on my code despite my license? Do I receive monetary payment from the deal? Or have I misunderstood this?

How is that different to a human reading your code and building up their experience? Is reading code now also covered by a license? It does not reproduce your code 1:1.

As soon as something can be automated, people start acting irrationally upset, especially if the thing is seen as even remotely "creative". Those people are going to have a bad time moving forward.

Re: GitHub cuts AI deals with Google, Anthropic

#638

Post by yifanl » Wed, Oct 30, 2024, 12:42 PM UTC

else42 wrote: post #634

sotix wrote: post #633

This sort of makes me sick as a software engineer with licensed code on GitHub. Am I understanding correctly that they have trained data on my code despite my license? Do I receive monetary payment from the deal? Or have I misunderstood this?

How is that different to a human reading your code and building up their experience? Is reading code now also covered by a license? It does not reproduce your code 1:1.

Because we had an implicit understanding that it would continue to be humans reading the code.

Re: GitHub cuts AI deals with Google, Anthropic

#639

Post by visarga » Wed, Oct 30, 2024, 12:43 PM UTC

strangescript wrote: post #637

else42 wrote: post #634

Earlier quoted context omitted.

How is that different to a human reading your code and building up their experience? Is reading code now also covered by a license? It does not reproduce your code 1:1.

As soon as something can be automated, people start acting irrationally upset, especially if the thing is seen as even remotely "creative". Those people are going to have a bad time moving forward.

We either allow copyright on abstract ideas or allow AI to learn and use those ideas

Re: GitHub cuts AI deals with Google, Anthropic

#640

Post by _petronius » Wed, Oct 30, 2024, 12:43 PM UTC

else42 wrote: post #634

sotix wrote: post #633

This sort of makes me sick as a software engineer with licensed code on GitHub. Am I understanding correctly that they have trained data on my code despite my license? Do I receive monetary payment from the deal? Or have I misunderstood this?

How is that different to a human reading your code and building up their experience? Is reading code now also covered by a license? It does not reproduce your code 1:1.

I think this is a bad-faith argument, if you know anything at all about how machine-learning systems work (in general, and LLMs in particular), and I wish people would stop trotting it out.

First, there are repeated documented examples of prompts beign designed that can cause an LLM to output training data (first link from a quick google: https://www.darkreading.com/cyber-risk/researchers-simple-te... but there are other examples, and some well-discussed ones on this site involving Github's own Copilot).

Second, the "it's just like a person learning" argument has been applied to all sorts of machine learning, and it rests on several fallacies:

1. That these systems learn the way humans do, and innovate on that learning

2. That their output constitutes any kind of original thought (related, LLM output is not copyrightable; human output is)

3. Most importantly, the scale is totally different. I think we can agree on the trivial example that training an image generation LLM on an artist's style and using that at scale to undercut the market for their work would constitute a kind of technologically-enabled competition that normal humans learning and copying styles could not equal, either in speed or in cost -- even if the quality were orders of magnitude better.