With a tech industry one-third the size of California’s, Canada has confounded expectations by becoming a leader in the booming market for artificial intelligence. Pioneering technologies developed in Canadian labs can be found in Facebook’s facial recognition algorithms, Google’s Photos app, smartphone voice recognition and even Japanese robots.
Now Canada risks losing its AI edge to Silicon Valley.
Already members of the Canadian AI community are trying to protect what they helped build. A startup called Maluuba (in photo) which makes technology that helps computers talk, is opening a research office in Montreal; the University of Toronto has opened a startup accelerator and this fall launched a program dedicated to AI research.
Elon Musk and Sam Altman worry that artificial intelligence will take over the world. So, the two entrepreneurs are creating a billion-dollar not-for-profit company that will maximize the power of AI—and then share it with anyone who wants it.
At least, this is the message that Musk, the founder of electric car company Tesla Motors, and Altman, the president of startup incubator Y Combinator, delivered in announcing their new endeavor, an unprecedented outfit called OpenAI. In an interview with Steven Levy of Backchannel, timed to the company’s launch, Altman said they expect this decades-long project to surpass human intelligence. But they believe that any risks will be mitigated because the technology will be “usable by everyone instead of usable by, say, just Google.”
“So we’ve built an entirely new machine learning system, which we call “TensorFlow.” TensorFlow is faster, smarter, and more flexible than our old system, so it can be adapted much more easily to new products and research. It’s a highly scalable machine learning system—it can run on a single smartphone or across thousands of computers in datacenters. We use TensorFlow for everything from speech recognition in the Google app, to Smart Reply in Inbox, to search in Google Photos. It allows us to build and train neural nets up to five times faster than our first-generation system, so we can use it to improve our products much more quickly.
We've seen firsthand what TensorFlow can do, and we think it could make an even bigger impact outside Google. So today we’re also open-sourcing TensorFlow. We hope this will let the machine learning community—everyone from academic researchers, to engineers, to hobbyists—exchange ideas much more quickly, through working code rather than just research papers. And that, in turn, will accelerate research on machine learning, in the end making technology work better for everyone. Bonus: TensorFlow is for more than just machine learning. It may be useful wherever researchers are trying to make sense of very complex data—everything from protein folding to crunching astronomy data.”
He starts simply, asking for the time in Berlin and the population of Japan. Basic search-result stuff—followed by a twist: “What is the distance between them?” The app understands the context and fires back, “About 5,536 miles.”
Then Mohajer gets rolling, smiling as he rattles off a barrage of questions that keep escalating in complexity. He asks Hound to calculate the monthly mortgage payments on a million-dollar home, and the app immediately asks him for the interest rate and the term of the loan before dishing out its answer: $4,270.84.
“What is the population of the capital of the country in which the Space Needle is located?” he asks. Hound figures out that Mohajer is fishing for the population of Washington, DC, faster than I do and spits out the correct answer in its rapid-fire robotic voice.
Yann LeCun, who now serves as the director of FAIR, comes from a storied tenure of artificial intelligence research. He began his work in Bell Labs (founded by telephone father Alexander Graham Bell, and known for its experiments across myriad fields in telecommunications and technology) as a researcher starting in 1988, then moving to become a department head at AT&T Labs until developing 2003, when he began to teach at New York University. The modern convolutional neural network is a culmination of work throughout LeCun’s career. Ever wonder how an ATM can read your check? That was LeCun, whose early work included a neural network simulator called “SN” and deployed in 1996.
“When someone like Mark (Zuckerberg) comes to you and says ‘Oh, okay, you pretty much have carte blanche. You can put together a world-class research lab and I expect you to build the best research lab in AI in the world.’ I’ll say,’Hmm, interesting challenge.’”
To be precise, Dr Rubenstein’s ’bot swarm (above) has 1,024 members (210 being a conveniently binary number), known apparently without irony as kilobots. Each is a rigid-legged tripod that moves around by vibrating. Kilobots communicate with infra-red light, which can reflect off the table Dr Rubenstein uses for his experiments, and are programmed with three types of behaviour.
One is edge-following, which allows a ’bot move along the edge of a cluster. The second is gradient-formation, which lets it know how many other ’bots a signal has been relayed through, and thus gives it information about the location of these ’bots and the shape of the cluster it is in. The third is localisation, which means it can agree a system of co-ordinates with its neighbours, so that they can measure distances between themselves.
“Half of these experts (48%) envision a future in which robots and digital agents have displaced significant numbers of both blue- and white-collar workers—with many expressing concern that this will lead to vast increases in income inequality, masses of people who are effectively unemployable, and breakdowns in the social order.
The other half of the experts who responded to this survey (52%) expect that technology will not displace more jobs than it creates by 2025. To be sure, this group anticipates that many jobs currently performed by humans will be substantially taken over by robots or digital agents by 2025. But they have faith that human ingenuity will create new jobs, industries, and ways to make a living, just as it has been doing since the dawn of the Industrial Revolution.”
I find Joaquin Phoenix creepy in most roles so did not enjoy the movie much but found the technology and setting fascinating.
There’s the LA of the future with and no cars (LA?!!! – it’s actually set in Shanghai). There’s evolved artificial intelligence – as in artificial feelings. No devices – desktop or mobile – have keyboards. Mono earpieces provide the UI to check email, get weather reports etc. The video games are holographic. The mobile devices are hinged and buck the larger, curved display trend of today. There’s no dropped anything even on elevators and trains – so the networks have clearly improved.
In quite a compliment, Wired says the movie will dominate UI design even more than Minority Report did. Go see it for that. If you like Amy Adams that’s another reason to go :)
"Masters students from the EPFLAutomatic Control Laboratory (LA) are developing a robot that can play foosball (table football) for their semester project. One of the levers has a mechanical arm capable of propelling the ball into the opposing goal at a speed of 6 meters per second."
From EPFL in Lausanne, Switzerland (hence the French in the video)
"the robotic arm depends on two computers: one to control the
mechanical movement of the arm and the other to provide information
about the position of the ball. In order to position itself correctly,
the robot must have a clear idea of the location of the ball in real
So students replaced the bottom of the foosball table with a
transparent material. They then placed a high-speed camera on the
ground to film the game board. “Through image processing algorithms, we
can analyze the movement of the ball in real time. This information is
transmitted to the computer that controls the movement and positioning
of the arm,” says masters student Martin Savary, who participated in the
Imagine taking a college exam, and, instead of handing in a blue book
and getting a grade from a professor a few weeks later, clicking the
“send” button when you are done and receiving a grade back instantly,
your essay scored by a software program.
EdX, the nonprofit enterprise founded by Harvard and the Massachusetts Institute of Technology
to offer courses on the Internet, has just introduced such a system and
will make its automated software available free on the Web to any
institution that wants to use it. The software uses artificial
intelligence to grade student essays and short written answers, freeing
professors for other tasks.
The EdX assessment tool requires human teachers, or graders, to first
grade 100 essays or essay questions. The system then uses a variety of
machine-learning techniques to train itself to be able to grade any
number of essays or answers automatically and almost instantaneously.