Ejercicio A3 · Inglés PAU Valencia Extraordinaria 2024

TEXT A/TEXTO A

ARTIFICIAL INTELIGENCE’S HUNGER FOR DATA

AND ITS THIRST FOR WATER AND ENERGY

One of the most dangerous myths about digital technology is that it is somehow weightless or immaterial. But datacentres – those enormous metallic cabins containing tens or even hundreds of thousands of noisy servers – consume massive amounts of electricity and need lots of water for their cooling systems. Consider Ireland, a small country with an awful lot of datacentres. In 2022 those centres consumed more electricity (18%) than all the rural dwellings in the country, and as much as all Ireland’s urban homes.

And as far as water consumption is concerned, a study estimated that one medium-sized datacentre used as much water as three average-sized hospitals. Although these industrial spaces are representative of the metaphor of “cloud computing”, there is nothing vague or incorporeal about them. There are now between 9,000 and 11,000 of these datacentres in the world and many of them are beginning to look a bit out-of-date.

But that is going to change, because the industrial interest around Artificial Intelligence (AI) means that the materiality of the computing “cloud” is going to become harder to ignore. Machine learning needed in AI requires a different kind of computer processors which are considerably more complex (and expensive) than conventional processors.

Additionally, they also run hotter, and need significantly more energy. Within the technology industry, it has been widely known that AI faces an energy crisis, but it was only at the World Economic Forum in Davos in January 2024 that one of its leaders finally spoke clearly about this crisis.

Adapted from an article by John Naughton, The Guardian, 2-3-2024.

A3. Find a synonym for each of the four words below from these six options. All words are underlined in the text (1 point: 0.25 each)

myths weightless dwellings representative out-of-date interest

a.

homes:

b.

attention:

c.

obsolete:

d.

typical: