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![](/i/favi32.png) April 22nd-28th 2023 Ukraine’s game planThe EconomistThe lure grows greater
The London tech boss says he is “incredi
bly nervous about the existential threat”
posed by
AI
, even as he pursues it, and is
“speaking with [other] founders about it
daily”. Governments in America, Europe
and China have all started mulling new
regulations. Prominent voices are calling
for the development of artificial intelli
gence to be paused, lest the software some
how run out of control and damage, or
even destroy, human society. To calibrate
how worried or excited you should be
about this technology, it helps first to un
derstand where it came from, how it works
and what the limits are to its growth.
The contemporary explosion of the ca
pabilities of
AI
software began in the early
2010s, when a software technique called
“deep learning” became popular. Using the
magic mix of vast datasets and powerful
computers running neural networks on
Graphics Processing Units (
GPU
s), deep
learning dramatically improved comput
ers’ abilities to recognise images, process
audio and play games. By the late 2010s
computers could do many of these tasks
better than any human.
But neural networks tended to be em
bedded in software with broader function
ality, like email clients, and noncoders
rarely interacted with these
AI
s directly.
Those that did often described their expe
rience in nearspiritual terms. Lee Sedol,
one of the world’s best players of Go, an an
cient Chinese board game, retired from the
game after Alphabet’s neuralnetbased Al
phaGo software crushed him in 2016. “Even
if I become the number one,” he said,
“there is an entity that cannot be defeated.”
By working in the most human of medi
ums, conversation, Chat
GPT
is now allow
ing the internetusing public to experience
something similar, a kind of intellectual
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