OC below by @HaraldvonBlauzahn@feddit.org
What called my attention is that assessments of AI are becoming polarized and somewhat a matter of belief.
Some people firmly believe LLMs are helpful. But programming is a logical task and LLMs can’t think - only generate statistically plausible patterns.
The author of the article explains that this creates the same psychological hazards like astrology or tarot cards, psychological traps that have been exploited by psychics for centuries - and even very intelligent people can fall prey to these.
Finally what should cause alarm is that on top that LLMs can’t think, but people behave as if they do, there is no objective scientifically sound examination whether AI models can create any working software faster. Given that there are multi-billion dollar investments, and there was more than enough time to carry through controlled experiments, this should raise loud alarm bells.
I know you are willfully being ignorant here as AI data centers are projected to use more electricity than the entire nation of Japan by 2030.
Your own hosted LLM is not the problem nor the issue we are even discussing and quite frankly a little insulting you bring it up
I am not anymore anti-AI than any tool that you can’t determine is accurate nor correct if there is an issue with it. LLM have a long way to go before they are even a fraction of what they claim to be.
Another problem is they do not cite where they get their answers from. Without the ability to audit the answers you are given you won’t know how accurate they are.
I have listed several legitimate gripes about LLM. I find your fanboism misplaced and I think you are just playing devil’s advocate at this point. AI is a hype train and I am sick of it already.
I will just copy my other response about datacenters energy usage, ignore the parts not related to our conversation:
Google is not related with chatgpt. Chatgpt parent company is openAI which is a competitor with google.
A more rational explanation is that technology and digital services on general have been growing and are on the rise. Both because more and more complex services are being offered, and more importantly more people are requesting those services. Whole continents that used not to be cover by digital services are now covered. Generative AI is just a very small part of all that.
The best approach to reduce CO2 emissions is to ask for a reduction in human population. From my point of view is the only rational approach, as with a growing population there’s only two solutions, pollute until we die, or reduce quality of life until life is not worth living. Reducing population allows for fewer people to live better loves without destroying the planet.
It also arises the question on why am I responsible if a big tech company decided to make an llm query of every search or overuse the technology, when I am talking about a completely different usage of that technology, that doesn’t even reach a 20-30 queries a day which would have a power usage of less than a few hundreds wh at most, which os negligible in the scheme of global warming and my total energetic footprint.
How it’s being a fanboy saying that “It works for me in some particular cases and not others, it’s a tool that can be used”.
Please, read again this conversation and do a second guess on who is a radical extremist here.
In the case we were talking, writing code, I am the auditor of the answers. I do not ““vibe code”” I read the code that’s proposed, understand it, and if it’s code that I would have written I copy it, if not I change it. “Vibe coding” is an example of bad usage of the tool that would lead to problems. All code not written by yourself and copied from other source should be reviewed. Once it pass my review is as good as my own code. If it fail it would fail the same as any other code witten by me, as it’s something that I was clearly unable to see.
For instance a couple of months ago I wrote a small API service that worked fine at first and suddenly stopped working a few weeks in production. It was a stupid mistake I made, and I needed no LLM to do that mistake. The service was so simple that I didn’t really even used LLM there. But I made a mistake regardless. I could have use AI and get the same bad function that caused the issue. And the blame would still be mine for not seeing the problem.
Once again is a tool. If some jackass decide to vibe code an app and it’s a shit app, is a bad use of the tool. But some other people can de proper reviews and analysis of the generated code and assume full responsibility of any failures of that code.