(Chris Devlin) #1

FOCUS


TECH


48


FORTUNE.COM // JUNE.1.19


MACHINE LEARNING


You can thank machine
learning for recom-
mending how to respond
to your boss when she
emails asking whether an
important document is
in order (“Looks good to
me”) or whether you can
meet at noon (“Let’s do it!”).
This is just a taste of how
algorithms help computers
“learn.” The chief attrac-
tion: Companies don’t
need humans to program
the technology for each
specific task it handles.
Example: Google Gmail

NEURAL NETWORKS


A.I.’s rise can be traced
to software developed
decades ago that was
intended to approximate
how the human brain
learns. Inside a neural
network are layers of inter-
connected nodes where
calculations take place that
help computers sift though
data in minute detail. By
doing so, the software can
learn to recognize patterns
that even the most intelli-
gent humans may overlook.
Example: Baidu search


DEEP LEARNING


Mixing neural networks with machine learning
makes for deep learning, a powerful technology
that can crunch enormous amounts of data, like
vast archives of audio clips. A.I.’s biggest break-
throughs—such as recognizing snow leopards
in photos—can be traced to the technology.
Example: Nvidia’s 3D A.I.-generated faces

REINFORCEMENT


LEARNING


This A.I. technique is like
training a dog with treats.
The software learns by suc-
cessfully executing a task
and, on the flip side, from
failure. This fusion of re-
inforcement learning with
deep learning has led to
tremendous breakthroughs,
like computers beating hu-
mans at complicated video
and board games. Example:
Facebook’s targeted
notifications
COMPUTER VISION
Devices using computer
vision are able to see
and understand their
surroundings almost like
a human. Think of facial-
recognition technology
that can automatically
unlock your iPhone or
the systems that help
navigate self-driving cars
without crashing them
into trees. The problem
seems easy to solve. But
in reality, it’s very difficult.
Example: Waymo’s
autonomous vehicles


NATURAL LANGUAGE PROCESSING


This technology makes it possible for computers
to understand and react to human speech
and language. Voice-controlled digital
assistants, which take dictation or power
Internet- connected home speakers, would be
impossible without it. The technology is still
imperfect, but it’s improving quickly.
Example: Amazon Alexa digital assistant

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ARTIFICIAL


INTELLIGENCE 101


Artificial intelligence is having its moment. Business leaders
can’t stop talking about it. New tech products invariably
include it. And news headlines incessantly chronicle
the buzz around it. But for many people, artificial intel-
ligence remains a mystery. To help, we’ve created a guide
that explains some of the key terms associated with
the technology, an increasingly useful tool for businesses
that improves as it crunches more data.
By Jonathan Vanian

PHOTOGRAPH BY THE VOORHES