The EconomistJanuary 20th 2018 53For daily coverage of business, visit
Economist.com/business-finance1C
ONNECTED devices now regularly
double as digital hoovers: equipped
with a clutch of sensors, they suck in all
kinds of information and send it to their
maker for analysis. Not so the wireless ear-
buds developed by Bragi, a startup from
Munich. They keep most of what they col-
lect, such as the wearers’ vital signs, and
crunch the data locally. “The devices are
getting smarter as they are used,” says Ni-
kolaj Hviid, its chief executive.
Bragi’s earplugs are atthe forefront of a
big shift in the tech industry. In recent years
ever more computing has been pushed
into the “cloud”, meaning networks of big
data centres. But the pendulum has al-
ready started to swing: computing is mov-
ing back to the “edge” of local networks
and intelligent devices.
As with the rise of the cloud in the early
2010s, the shift will cause upheaval. Many
startups will try to ride the trend, as will in-
cumbents such as hardware makers. But
the real fight will be over who colonises
the edge and, in particular, which firms
will control the “internet of things” (IoT),
as connected devices are collectively
called. Will Amazon Web Services (AWS),
Microsoft and other large cloud providers
manage to extend their reach? Or will the
edge be the remit of a different set of firms,
including makers of factory equipment
and other sorts of gear?
Since emerging in the 1950s, commer-quire data to stay within their borders or
even within the walls of a company. Firms
want to use data but, worrying about leaks,
often prefer to keep their own information
inhouse. Consumers, for their part, care
about privacy, which Bragi hopes to ad-
dress with its self-sufficient earplugs.
The dominant narrative in the tech in-
dustry—that most data are best crunched
centrally in the cloud—is also undermined
by the fact that many new applications
have to act fast. According to some esti-
mates, self-driving cars generate as much
as 25 gigabytes per hour, nearly 30 times
more than a high-definition video stream.
Before so many data are uploaded, and
driving instructions sent back, the vehicle
may well already have hit that pedestrian
suddenly crossing the street.
Changing economics are another con-
sideration. The faster adjustments can be
made—for instance, to optimise the opera-
tions of a machine in a factory—the bigger
revenue gains tend to be. That means data
are often best analysed as they are cap-
tured, which needs to be done locally. The
costs of transferring, storing and process-
ing data in the cloud can be avoided too.Car-boot brains
These constraints explain whyservices us-
ing artificial intelligence (AI) are increas-
ingly split in two, much like client-server
applications, explains Pierre Ferragu of
Bernstein Research. The algorithms of au-
tonomous cars, for instance, are first
trained in the cloud with millions of miles
of recorded driving data; only then are
they deployed on powerful computers in
the boot, where they steer the car by inter-
preting live data. Similarly, many video
cameras used for surveillance now ship
with face-recognition software trained in
the cloud, as doesApple’slatestiPhonecial computing hasoscillated between be-
ing more centralised and more distributed.
Until the 1970s it was confined to main-
frames. When smaller machines emerged
in the 1980s and 1990s, it became more
spread out: applications were accessed by
personal computers, but lived in
souped-up PCs in corporate data centres
(something called a “client-server” sys-
tem). With the rise of the cloud in the
2000s, things became more centralised
again. Each era saw a new group of firms
rise to the top, with one leading the pack:
IBMin mainframes, Microsoft in personal
computers and AWSin cloud computing.
Better technology is one reason why
computing is again becoming more distri-
buted. Devices at the edge, from smart-
phones to machinery on the shop floor, are
becoming more intelligent. Equipped with
powerful processors, they can now tackle
computing problems that a few years ago
needed a fully loaded server. As for soft-
ware, its increased flexibility means it can
function well on the edge. Many applica-
tions are now “virtualised”, meaning they
exist separately from any specific type of
hardware: code can thus be packaged in
digital “containers” and easily moved
around within data centres—and, increas-
ingly, closer to the edge.
Demand for computing at the edge is
growing, too, often for non-technical rea-
sons. Many countries have laws that re-Computing geography (1)Life on the edge
Computing is emerging from centralised clouds and moving to the “edge” of local
networks and devicesBusiness
Also in this section54 The Chinese cloud
55 SoftBank’s vision
55 European football rights
56 General Electric keeps fizzling
57 Bamboo in China
58 Schumpeter: Mad men