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Guilty until proven innocent will satisfy the author's LLM-specific point of contention, but it is hardly a good principle.
> This sort of protectionism is also seen in e.g. controlled-appelation foods like artisanal cheese or cured ham. These require not just traditional manufacturing methods and high-quality ingredients from farm to table, but also a specific geographic origin. Maybe "Artisanal Coding" will be a thing in the future?
This is an absolute chef-kiss double-entendre.
btw you can make git commits with AI as author and you as commiter. Which makes git blame easier
And "lazy". Claude makes me mad: even when I ask for small code snippets to be improved, it increasingly starts to comment "what I could improve" in the code I stead of generating the embarrassingly easy code with the improvement itself. If I point it to that by something like "include that yourself", it does a decent job. That's so _L_azy.
LLMs are cheaters because their goal isn't to produce good code but to please the human.
>If you ask me, no court should have ever rendered a judgement on whether AI output as a category is legal or copyrightable, because none of it is sourced. The judgement simply cannot be made, and AI output should be treated like a forgery unless and until proven otherwise. Guilty until proven innocent will satisfy the author's LLM-specific point of contention, but it is hardly a good principle.
He is proposing to not make a judgement at all. If the AI company CLAIMS something they have to prove it. Like they do in science or something. Any claim is treated as such, a claim. The trick is to not even claim anything, let the users all on their own come to the conclusion that it's magic. And it's true that LLMs by design cannot cite sources. Thus they cannot by design tell you if they made something up with disregard to it making sense or working, if they just copy and pasted it, something that either works or is crap, or if they somehow created something new that is fantastic.
All we ever see are the success stories. The success after the n-th try and tweaking of the prompt and the process of handling your agents the right way. The hidden cost is out there, barely hidden.
This ambiguity is benefitting the AI companies and they are exploiting it to the maximum. Going even as far as illegally obtaining pirated intellectual property from an entity that is banned in many countries on one end of their utilization pipeline and selling it as the biggest thing ever at the other end. And yes, all the doomsday stories of AI taking over the world are part of the marketing hype.
> It's not a co-pilot, it's just on auto-pilot. Love it. Calling it "Copilot" in itself is a lie. Marketing speak to sell you an idea that doesn't exist. The idea is that you are still in control.
Well initially it was a lot less capable. Someone might describe it auto-complete on steroids. Someone might call LLMs that today, except they've stepped a bit up from steroids.
Most of what we do is programming is some small novel idea at high level and repeatable boilerplate at low level. A fair question is: why hasn’t the boilerplate been automated as libraries or other abstractions? LLMs are especially good at fuzzy abstracting repeatable code, and it’s simply not possible to get the same result from other manual methods.
I empathise because it is distressing to realise that most of value we provide is not in those lines of code but in that small innovation at the higher layer. No developer wants to hear that, they would like to think each lexicon is a creation from their soul.
What the author and many others find hard to digest is that LLMs are surfacing the reality that most of our work is a small bit of novelty against boiler plate redundant code. Most of what we do is programming is some small novel idea at high level and repeatable boilerplate at low level. A fair question is: why hasn’t the boilerplate been automated as libraries or other abstractions? LLMs are especially good at fuzz…