Of course.
"There are already huge resources involved in indexing and searching internet content, but the incorporation of AI requires a different kind of firepower," Alan Woodward, a cybersecurity expert at the University of Surrey, told the magazine.
"It requires processing power as well as storage and efficient search. Every time we see a step change in online processing, we see significant increases in the power and cooling resources required by large processing centers," he added. "I think this could be such a step."that training the large language models that the likes of ChatGPT run on is so prohibitively resource intensive that essentialy "only the Big Tech companies can train them.
Unfortunately, none of them — namely Microsoft and Google — have publicly disclosed how much computational power they're consuming to get their chatty AIs off the ground. But anfound that training OpenAI's GPT-3 model consumed 1,287 megawatt hours, which the outlet compared to "the same amount as a single person taking 550 roundtrips between New York and San Francisco."bad.
"At least four or five times more computing per search," estimates Martin Bouchard, co-founder of the sustainable data center company QScale, toAt scale, that could be very substantial. Bouchard notes that the computing demands will only get worse when the AIs are eventually trained on current data and not merely datasets from a snapshot in time.
"Current data centers and the infrastructure we have in place will not be able to cope with [the race of generative AI]," he added. "It's too much."
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