But given the huge costs of training deep-learning
models and hiring AI talent, $1 billion would cover
only a few years’ worth of OpenAI’s research. It was
clear from the beginning that the lab would run
into cash problems long before it reached its goal.
“We’ll need to invest billions of dollars in upcoming
years into large-scale cloud compute, attracting
and retaining talented people, and building AI
supercomputers,” the lab declared in 2019, when it
renamed itself OpenAI LP and restructured to a
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invest in OpenAI for returns “capped” at a hundred
times their initial investment.
Shortly after the company’s announcement,
Microsoft invested $1 billion in OpenAI. The
infusion of cash allowed the company to continue
to work on GPT-3 and other expensive deep-
learning projects. But investor money always
comes with strings attached.
SHIFTING TOWARD OBSCURITY
In June, when it announced GPT-3, the company
didn’t release its AI model to the public, as is the
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application programming interface (API) that let
developers give GPT-3 input and obtain the results.
In the future, the company will commercialize
GPT-3 by renting out access to the API.
“Commercializing the technology helps us pay for
our ongoing AI research, safety, and policy
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the GPT-3 API.
B
e
n
D
i
c
k
s
o
n
The infusion of
cash allowed
the company
to continue to
work on GPT-3
and other
deep-learning
projects.
