As the oracles of Silicon Valley debate whether the latest tech boom is
sliding toward bust, there is talk about what will drive the industry's
next growth spurt.The way we use computing is changing, toward a boom
(and, if history is any guide, a bubble) in collecting oceans of data in
so-called cloud computing centres, then analysing the information to
build new businesses.The terms most often associated with this are
"machine learning" and "artificial intelligence," or AI. And the
creations spawned by this market could affect things ranging from
globe-spanning computer systems to how you pay at the cafeteria."
There
is going to be a boom for design companies, because there's going to be
so much information people have to work through quickly," said Diane B.
Greene, head of Google Compute Engine, one of the companies hoping to
steer an AI boom. "Just teaching companies how to use AI will be a big
business."
This kind of change is what keeps Silicon Valley going.
When personal computers displaced mainframe computers, it opened the
door not just for Apple, but for companies making PC software for
business, games and publishing. In the networking and Internet
revolutions, venture capitalists invested in these new computing styles,
and another generation of companies was born.
Over the last
decade, smartphones, social networks and cloud computing have moved from
feeding the growth of companies like Facebook and Twitter, leapfrogging
to Uber, Airbnb and others that have used the phones, personal rating
systems and powerful remote computers in the cloud to create their own
new businesses.
Believe it or not, that stuff may be heading for
the rearview mirror. The tech industry's new architecture is based not
just on the giant public computing clouds of Google, Microsoft and
Amazon, but also on their AI capabilities. These clouds create more
efficient and supple use of computing resources, available for rent.
Smaller clouds used in corporate systems were designed to connect to
them.
The AI resources Greene is opening up at Google are
remarkable. Google's autocomplete feature that most of us use when doing
a search can instantaneously touch 500 computers in several locations
as it guesses what we are looking for. Services like Maps and Photos
have more than 1 billion users, sorting places and faces by computer.
Gmail sifts through 1.4 petabytes of data, or roughly 2 billion books'
worth of information, every day.
Handling all that, plus tasks
like language translation and speech recognition, Google has amassed a
wealth of analysis technology that it can offer to customers. Urs
Holzle, Greene's chief of technical infrastructure, predicts that the
business of renting out machines and software will eventually surpass
Google advertising. In 2015, ad profits were $16.4 billion.
"In
the '80s, it was spreadsheets," said Andreas Bechtolsheim, a noted
computer design expert who was Google's first investor. "Now it's what
you can do with machine learning."
He added: "Better maps and photos is just the start. It's going to be in life sciences, automobiles, everything."
A
number of startups are aimed at the new architecture. A Mountain View,
California, outfit called Mashgin uses "computer vision" to automate
retail checkout. Up Highway 101 in San Mateo, a company called Alluxio
is creating ways to make cloud-based AI work better. Last week, a San
Francisco company called Mesosphere, which makes a way to operate among
various corporate and public clouds, raised $73.5 million.
Microsoft and Amazon are racing Google to dominate the new architecture.
This
week, Microsoft will kick off a conference in San Francisco that is
expected to focus on ways machine-based intelligence can be used to
analyze, among other things, "the Microsoft graph," or all the data
companies already have in the Microsoft products they've owned for
decades.
Last year, Amazon announced its own machine-learning services, and it is amassing its own large repository of corporate data.
Hewlett-Packard
Enterprise, an older company struggling to find its way in the new
landscape, was one of the investors in Mesosphere.
"When you are
building predictive data, you don't know what you are going to need
next," said William Hilf, a senior vice president at HPE. "If someone
makes a bet in machine learning on Microsoft or Google, they may need to
come down to their old data systems, too. We are building platforms to
bridge among all of them."
To Greene, all of the activity, along
with the size and sophistication of computing, is small compared to what
will happen when the world's biggest businesses start leaning on the
new AI technology.
"We may build an AI system to figure out all
the ways businesses can use this," she joked. "The relationship between
big companies and deep machine intelligence is just starting."
© 2016 New York Times News Service