Who’s afraid of the big, bad GPU?

The increasing use of GPUs to power artificial intelligence is having significant environmental impacts, including high energy consumption, water usage, and e-waste generation. Researchers estimate that AI servers could create between 0.131 million and 0.225 million tons of e-waste each year by 2030, and that the energy needed to train a model can lead to as much air pollution as 10,000 round trips by car between Los Angeles and New York City. Experts argue that the tech industry's "bigger is better" mentality is driving these environmental issues, and that companies must prioritize sustainability and accountability in their development of AI technologies. To mitigate these impacts, researchers suggest designing chips and AI models to be more energy-efficient, reducing e-waste through recycling and reuse, and increasing transparency about water usage and environmental footprint.

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