I am against GenAI and everything it stands for(lpcvoid.com) |
I am against GenAI and everything it stands for(lpcvoid.com) |
The vast majority of AI development is public. There are papers literally every single day to read. In fact everything you need to build Claude and GPT models is public. Thanks to Google, DeepSeek, and all the other research labs. There are more research labs than there are closed shops. In fact there really is only one Anthropic, and lately maybe OpenAI. Google still releases papers all the time on AI.
There are more open source models than closed source models and all of them are accessible without a subscription. Yeah you still need to pay for them, but hey as we build out infrastructure and more time is put into efficient models today will easily run on person compute of the future.
https://web.archive.org/web/20220314184648/https://lpcvoid.c...
I do not understand what the problem is. There are both closed and open models. You can run your own machine with dozens of open models. You can train your own model. You can do everything on your own.
Of course, there are limitations. For example, you cannot magically have all the best hardware at your disposal, but that limitation also exists in normal programming.
AI is definitely on a scale of magnitude more but it has inherent value outside of “scarcity”. It’s actually quite the opposite with sheer supply/demand balance. Also investing in crypto made me less money than investing in myself by using AI to learn and challenge myself to think differently.
AI is going to transform people's lives for the better, because every single solitary advancement in human technology in history has had both benefits and drawbacks. If the only thing you can come up with is drawbacks, you're being willfully ignorant.
Having said that, expecting writers to devote equal time to the pros and cons of an argument can set up a false equivalence. It tells the reader that the benefits and drawbacks must be somewhat equal, even when they're not.
> If the only thing you can come up with is drawbacks, you're being willfully ignorant.
Does this also go the other way? If you can't come up with any drawbacks, you're being "wilfully ignorant"? You may want to amend your post!
I gave the article a chance regardless and it's nothing I've not read before.
In 5-10 years AI is going to be so much better than even the best human coder that this is a moot point. If anything AI will be used to correct all the crappy human made code that is still being pushed due to the vanity of coders still pretending that they are better than AI at coding.
I can understand hating AI, but it seems like many who are against genAI have a strange delusional disbelief of how good the models are, and the trend-line we are on. They think that their special skills will never be eclipsed by an AI model. If you are going on a crusade against genAI and LLM’s at least be honest about what you’re up against.
In my organization, this is already happening. We've been using LLMs to boost our test coverage without touching our human code, then use that as a scaffold to let it go through and refactor, clean up, and optimize, and then validating against both our tests and gold standard test datasets.
In our case, it's made a legacy codebase far more readable to our junior engineers, and the performance improvements (from using an autoresearch-style approach) has resulted in a six figure decrease in our compute spend for the production service we trialed this on.
What funny nonsense. This is like saying AI will replace artists because it's better than your average artist.
Software engineering is as much an artform as it is infrastructure. AI cannot approximate even a poor engineer because it cannot capture the full context of a problem to be solved.
It doesn't help that most of these 'metrics' are literally invented by and ran by the companies that benefit the most from said metrics. I've seen this shit at major companies before, because the c-suite loves to invent metrics that make their product look good even if it ignores reality.
It seems like if they can do it, that there's no reason they can't eventually be trained to do it better up to and beyond human performance. It seems strange to suggest that thinking unlocks some nominal margin of "better" specifically that can't be overcome.
All of that aside, even if they can't outperform the top human programmers...what if they get to within a margin where they're still better than most? Isn't a 95th percentile programmer that can run 24/7 and continuously refine its work still going to ultimately come out on top?
The issue about AI is that it's gobbling so much information that at some point you couldn't tell the difference. Programming specifically is something that inherently documents itself, meaning while human communication and context and memes and culture is something that evolves and exists many times outside of textual mediums, as soon as any new piece of code is born it is now part of the AI's dataset. And it doesn't help that a vast majority of our code is pretty damn repetitive, especially if you insert code written in the span of two decades and more into the future.
Tldr : The better we get at coding, the more code we write, the better AI gets at coding.