This is the wrong question to be asking. “Is the code good” is literally all that matters when writing software that others will use. Slop is slop no matter if it comes from a person or an LLM. A human should be reviewing all code.
Those are imaginary shit made up to stop progress. AI will be used. If not then the project will be formed and the fork will get leaves better than the human slop version. Meanwhile you’ll keep coping that le AI bad with le enbyornmint. AI uses less water than growing almonds. Stop being a brainwashed cattle
AI will be used. If not then the project will be formed and the fork will get leaves better than the human slop version.
I heavily doubt this is actually the case.
But perhaps you can help out and show me some convincing real-world examples where large, mature, abd widely used FOSS projects were forked and became significantly better because use of LLM code generation?
We have these things now for at least a year and as the old saying from the dot com era goes, Internet years are dog years, meaning a three year old dog is adult, so there must be a really successful application of that LLM technology in software development?
The issue with the almonds is that there are a bunch of dumbasses growing them in an area that, left to itself, would be a desert. They shouldn’t be doing that, either.
My point was that even if the water use of data centers is less than that of almonds, it does not justify the existence of the data centers because the water use of the almonds is also grossly inflated. You don’t waste 999 million dollars just because someone else is wasting a billion.
Powering data centers with renewable energy sources, like solar or wind, requires significantly less water consumption than obtaining energy from fossil fuel power plants. With approximately 56% of the electricity used to power data centers nationwide coming from fossil fuels, deploying more clean energy to power these facilities can significantly reduce water consumption. Coal plants are the most water-intensive facilities, requiring approximately 19,185 gallons of water per megawatt-hour (MWh) of power generation. Natural gas power plants consume approximately 2,800 gallons per MWh. In 2022, 40% of all total U.S. annual water withdrawals, or about 48.5 trillion gallons, were made by coal and gas power plants. Of those 48.5 trillion gallons, 962 billion gallons of water were consumed and were no longer available for direct downstream use.
Yes. I think that’s regularly the reason why I decline AI contribution/assistance. Quality just isn’t great. The coding agents just rewrite way too much code. And the reasoning in the PRs or backlog of the agent is regularly missing the bigger picture, or besides the point. It’s really hard to get good quality out of an LLM and most people (including me) don’t manage to pull it off. At least for more complex stuff. I can do one-off things with AI or cobble a website together with some Javascript included.
This is the wrong question to be asking. “Is the code good” is literally all that matters when writing software that others will use. Slop is slop no matter if it comes from a person or an LLM. A human should be reviewing all code.
Only if one ignores the ethical, environmental, and copyright concerns.
How dare you have nuance!
Those are imaginary shit made up to stop progress. AI will be used. If not then the project will be formed and the fork will get leaves better than the human slop version. Meanwhile you’ll keep coping that le AI bad with le enbyornmint. AI uses less water than growing almonds. Stop being a brainwashed cattle
I heavily doubt this is actually the case.
But perhaps you can help out and show me some convincing real-world examples where large, mature, abd widely used FOSS projects were forked and became significantly better because use of LLM code generation?
We have these things now for at least a year and as the old saying from the dot com era goes, Internet years are dog years, meaning a three year old dog is adult, so there must be a really successful application of that LLM technology in software development?
Thing is, you can eat and process almonds further, ai slop? Not so much.
Citation needed.
The issue with the almonds is that there are a bunch of dumbasses growing them in an area that, left to itself, would be a desert. They shouldn’t be doing that, either.
Irrelevant whataboutism. Nothing about the almonds justifies or is at all related the datacenter build-outs.
My point was that even if the water use of data centers is less than that of almonds, it does not justify the existence of the data centers because the water use of the almonds is also grossly inflated. You don’t waste 999 million dollars just because someone else is wasting a billion.
there are a few. i feel like this one gives the most info succintly
https://rare.org/wp-content/uploads/2026/05/AI-and-Water-Use-Updated.pdf
In general, it’s unwise to cite carpetbaggers who don’t account for the full systemic impacts of their data centers.
See, for example: https://www.eesi.org/articles/view/data-centers-and-water-consumption
No puppies for you
The problem is “slop code” and “bad code” are always the same thing. That’s why it’s called slop code.
Agreed!
Yes. I think that’s regularly the reason why I decline AI contribution/assistance. Quality just isn’t great. The coding agents just rewrite way too much code. And the reasoning in the PRs or backlog of the agent is regularly missing the bigger picture, or besides the point. It’s really hard to get good quality out of an LLM and most people (including me) don’t manage to pull it off. At least for more complex stuff. I can do one-off things with AI or cobble a website together with some Javascript included.