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发表于 2016-7-10 20:11:43
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Last week, Tesla CEO Elon Musk and fellow tech kingpins committed $1
billion to researching artificial intelligence. The group’s findings would be
made available for the world. The possibilities where AI might help include the
ability to detect anomalies in images of cells to detect cancer, programming
robots that can interact with humans, and building programs that could help
teach kids at their pace of learning in a more individual style.
Behind this feel-good effort is a hint at the priorities of some of the
biggest names in Silicon Valley. It also provides an understanding of how AI or
machine learning, as the technology is often called, has the potential to remake
the tech world in the same way the web did in the mid-’90s.
Worries about artificial intelligence have sparked headlines exclaiming
that AI could bring about the death of humanity as smart machines become so much
smarter than us they wipe us out, not out of malice, but because we’re simply in
the way of their own goals. The most optimistic ones focused on the possibility
of sex robots that can carry on conversations.
But in reality, AI has existed for over a decade. It already plays a big
role in technologies that we take for granted like Apple’s Siri personal
assistant, IBM’s Watson Jeopardy-winning computer, and even the autopilot
feature that Teslarolled out in its cars earlier this year.
And before AI can destroy humanity, or provide sexual satisfaction, it has
to get better. Much better. And the launch of OpenAI, the billion-dollar
nonprofit research center announced this week, opens a window into what some of
the big thinkers in computer science and business consider as opportunities and
challenges.
First, as analyst Ben Thompson, who writes over at the site Stratechery,
pointed out in an essay about the topic, OpenAI’s creation can be read as a
manifesto, or as a recruiting ad for top research talent.
Thompson looked past the do-gooder language of the OpenAI blog post, which
talks about ensuring that commercial interests don’t hijack the promise of
artificial intelligence research. Instead, he focused on the final line of the
third paragraph of the introduction, which reads “We hope this is what matters
most to the best in the field.”
The fear is that Google, Facebook, and Chinese search engine Baiduare
luring all of the machine learning talent to their companies using a sales pitch
that hires can work on some of the most complex social problems of our era. Each
company uses huge pools of data to help train sophisticated machine learning
algorithms.
Data is the lifeblood of AI. To train computers to learn more like humans,
you have to feed them tens of thousands of examples of something. Depending on
what type of outcome you are hoping for, the examples can be photos, maps, or
words. The computers try to understand what elements of those examples define
what makes a cat a cat in an image or what gives meaning to a certain word. The
algorithm then gives astatistical weight to each guess that helps the computer
“learn” what the right answer is. The computer scientist helps train the
algorithm by giving feedback and more examples along the way.
That’s why none of these companies ever wants to throw away data. It may
come in handy for AI training someday. And that’s why the promise of using
something like Tesla’s car data for building algorithms might be enough to get a
researcher excited to work with OpenAI instead of Google.
Sam Altman, a co-chair at OpenAI, tells Fortune that data from Tesla would
be made available to researchers working at OpenAI. He said he would also work
to make data from startups that go through Y Combinator, the accelerator program
he leads, available for researchers at OpenAI as well.
“There are also plenty of publicly available data sets on the Internet,”
Altman said. Researchers could use those to come up with new tools and
algorithms that will advance AI as well.
The second element designed to attract talent to OpenAI is its nonprofit
status and its pledge of openness. It’s not that Facebook and others aren’t open
with their research. They publish their research fairly quickly. Google,
however, tends to wait until it has gained a significant strategic advantage
from a new findings before publishing. But it is still made public.
SerkanPiantino, director of Facebook’s AI research program, emphasized the
importance of openness in a conference call ahead of premiering his company’s
new servers designed especially for training computers to learn earlier this
month. Facebook’s engineers expect the work they do to be contributed back to
the open source community. Thus, Facebook contributes code to the community in
part because that keeps its civic-minded engineers happy.
But the race for talent isn’t the only reason OpenAI exists. The
development of true artificial intelligence is going to remake software. And
every business wants to be part of that shift.
“The way software is eating the world today, well, AI will do that to
software,” says Amir Husain, CEO of Spark Cognition, an AI security startup in
Austin, Texas.
He explained that many kinds of business software that replaced paper
documents and in filing cabinets will eventually be transformed into a new
format. And that format will likely be more user-friendly because of hard work
done by artificial intelligence behind the scenes.
“All of these categories will be destroyed and remade, so there’s a lot of
economic potential locked up in this,” says Husain. “It’s sort of like being the
only guy in 1995 who knows HTML.”
And that, more than anything, is why the big brains in Silicon Valley and
at other companies left out of the OpenAI effort are hustling to stake a claim
in this space. Rob High, an IBM Fellow, and VP and CTO of IBM’s Watson Group,
explained that the computing giant is interested in learning more about the
organization and getting involved.
IBM, which learned about the OpenAI group on Friday like nearly everyone
else, has a decades-long program in artificial intelligence through Watson. The
company hopes that it will help it weather the shift from web-based software to
new A.I.-related services.
But IBMis also building an entirely new type of chip designed for
artificial intelligence modeled on the human brain, called a synaptic chip. As
far as hardware for AI goes, IBM is the most serious player in the space.
Following is Nvidia, which makes graphics processors that are actually the
preferred chip used today for training computers to learn.
That gets us back to Altman, from OpenAI, and the plans for the nonprofit.
The short-term goals, he said are to build tools and algorithms that will be
shared publicly. But in the long term, better hardware is needed to build AI
that can perform more like a human.
“If you think about building better AI and modeling it after the human
brain, more hardware research and better hardware will be important,” Altman
says. “But today that is not our primary focus.”
That might be why Altman says OpenAI only spoke very casually with a person
who was involved with Watson at IBM, instead of going through formal channels to
try to get Big Blue involved with the project. (And why IBM found no record of
someone from OpenAI contacting it at all). Or perhaps there’s simply a divide
between the Silicon Valley practice of calling anything with machine learning
involved AI and promoting its involvement in new product launches. Meanwhile,
IBM, which brands all of its AI efforts under Watson and cognitive computing,
may have confused the public.
Plenty of other companies have their own efforts in artificial
intelligence. For example, Apple has hired researchers, but has reportedly found
it to be tough to recruit experts. In part, it’s because the company doesn’t
want to share the research results. Microsoft MSFT 1.29% also has AI research in
natural language for its Skype translation efforts and computer recognition that
are worth mentioning as well.
This is a cheaper way to solve the problem and more Amazon-like. Outside of
the giant tech firms, startups, industrial giants, researchers and more are all
experimenting with using AI. If OpenAI really does build broadly useful tools,
that could help advance science for everyone.
Altman says it’s too soon to list OpenAI’s research priorities. It will
work on tools and algorithms, but the specific areas where it will focus are
unsure. But he said he would consider it a success if the organization, within
one year, publishes “some seminal paper that drives the state of the art
forward.”
However, it’s clear that technologists supporting the project and those
working on AI in general, have much larger goals.
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