Despite its name, the infrastructure used by the “cloud” accounts for more global greenhouse emissions than commercial flights. In 2018, for instance, the 5bn YouTube hits for the viral song Despacito used the same amount of energy it would take to heat 40,000 US homes annually.

Large language models such as ChatGPT are some of the most energy-guzzling technologies of all. Research suggests, for instance, that about 700,000 litres of water could have been used to cool the machines that trained ChatGPT-3 at Microsoft’s data facilities.

Additionally, as these companies aim to reduce their reliance on fossil fuels, they may opt to base their datacentres in regions with cheaper electricity, such as the southern US, potentially exacerbating water consumption issues in drier parts of the world.

Furthermore, while minerals such as lithium and cobalt are most commonly associated with batteries in the motor sector, they are also crucial for the batteries used in datacentres. The extraction process often involves significant water usage and can lead to pollution, undermining water security. The extraction of these minerals are also often linked to human rights violations and poor labour standards. Trying to achieve one climate goal of limiting our dependence on fossil fuels can compromise another goal, of ensuring everyone has a safe and accessible water supply.

Moreover, when significant energy resources are allocated to tech-related endeavours, it can lead to energy shortages for essential needs such as residential power supply. Recent data from the UK shows that the country’s outdated electricity network is holding back affordable housing projects.

In other words, policy needs to be designed not to pick sectors or technologies as “winners”, but to pick the willing by providing support that is conditional on companies moving in the right direction. Making disclosure of environmental practices and impacts a condition for government support could ensure greater transparency and accountability.

  • Fades@lemmy.world
    link
    fedilink
    English
    arrow-up
    4
    arrow-down
    1
    ·
    edit-2
    5 months ago

    That’s bs now and will only become more so with time.

    This was posted two days ago: https://stackoverflow.blog/2024/05/29/developers-get-by-with-a-little-help-from-ai-stack-overflow-knows-code-assistant-pulse-survey-results/

    We found that most of those using code assistant tools report that these assistants are satisfying and easy to use and a majority (but not all) are on teams where half or more of their coworkers are using them, too. These tools may not always be answering queries accurately or solving contextual or overly specific problems, but for those that are adopting these tools into their workflow, code assistants offer a way to increase the quality of time spent working.

    The majority of respondents (76%) let us know they are using or are planning to use AI code assistants. Some roles use these tools more than others amongst professional developers: Academic researchers (87%), AI developers (76%), frontend developers (75%), mobile developers (60%), and data scientists (67%) currently use code assistants the most. Other roles indicated they are using code assistants (or planning to) much less than average: data/business analysts (29%), desktop developers (39%), data engineers (39%), and embedded developers (42%). The nature of these tools lend themselves to work well when trained well; a tool such as GitHub Copilot that is trained on publicly available code most likely will be good at JavaScript for frontend developers and not so good with enterprise and proprietary code scenarios that business analysts and desktop developers face regularly.

    But go ahead, speak for the whole goddamn industry, we’re totally not using AI or AI code-assist!!!

    • zepplenzap@lemmy.one
      link
      fedilink
      English
      arrow-up
      3
      ·
      5 months ago

      Sorry, I’m not seeing how your source is helping your argument.

      The line I’m responding to is

      “This is absolutely false. GitHub Copilot (and it’s competitors) alone are already actively helping and assisting virtually every software developer around the world.”

      While your source says: "The majority of respondents (76%) let us know they are using or are planning to use AI code assistants. "

      An un scientific survey (aka not random) which it’s self claims the 75% of people who respond used OR ARE PLANNING ON USING (aka, not use it yet), does not equal virtually every developer.

      Also wasn’t stack overflow recently getting bad press for selling content to AI companies? Something that pissed large parts of the developer community? Something that would make developers not happy with AI not take the survey?

      Anyway, have a great day, and enjoy your AI assistant.