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 Recent data from the UK shows that the country’s outdated electricity network is holding back affordable housing projects.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.
thing is that few if any use cases for blockchain were found and any actual useful things would not require much energy. The high energy crypto itself does nothing useful over more efficient alternatives and I don’t know what you mean by fizzle out but it still uses massive amounts of energy. the language models unfortunately do things that are useful and is much more likely to keep drawing power.
And the really perverted incentive of crypto is that due to the way difficulty is done, in particular with PoW systems, the more adoption there is the more energy intensive it becomes. Scaling actually leads to more inefficiency by design. I mean it’s totally asinine.
oh yeah. in the end you have a system that creates artificial value by requiring the sacrifice of real value. heres one credit for burning a barrel of oil. oh now you have to burn 2 to get a credit, now its 4, now its 8.
And crypto bros somehow think that this means they are buying energy… But you can’t get it back after it’s burned.
