I’m seeing a hilarious new time-wasting trend emerging: software engineers are making "naughty lists" of software "tainted" by AI/LLM involvement, seemingly to shame authors who use AI-assisted tools. They are setting up git repos to crowdsource PRs to help grow these lists of shame. They follow on with "alternative" software that supposedly has no AI involvement in their creation.
But I wonder: what CPUs do these people plan to switch to?
The advent of large language models (LLMs) has revolutionized the fields of artificial intelligence, machine learning, and natural language processing. LLMs, which include tools like OpenAI's ChatGPT, Google's Bard, and others, have demonstrated remarkable capabilities, from answering complex questions to assisting in creative endeavors. However, training and maintaining these models require substantial computational resources, translating into significant environmental impacts. Chief among these impacts is water usage, primarily to cool the vast data centers that run these models, raising the question: are the benefits provided by LLMs worth the strain on the world's increasingly scarce fresh water supplies?
