The conventional wisdom of finding a “good” job might be a very risky move. Respected and thought-provoking Waterloo Economics professor, Larry Smith (MA ’75), is on a mission to help us avoid good jobs so we can find a great one. In his book “No Fears, No Excuses: What You Need to Do to Have a Great Career” he itemizes all the excuses and worries that can hold us back — and deconstructs them brilliantly to inspire all readers to pursue their passion.
He won his 2014 academy award for work in colour perception, as applied to computer graphics, described in his 1997 PhD thesis.He told CTV News he hadn’t done any work in computer graphics for 15 years. Veach had worked at Pixar, but, more recently, he had been a senior developer at Google.
His PhD thesis, Robust Monte Carlo Methods for Light Transport Simulation, is highly cited.
In 2008, the University of Waterloo, the institution where he earned his Bachelor of Mathematics, in 1990, awarded him a J. W. Graham Medal, an annual award granted to a distinguished alumnus who had studied computer science there. His PhD is from Stanford University.
Farhad Manjoo named Veach and two of his non-American colleagues, at Google, in an article entitled, “Why Silicon Valley Wouldn’t Work Without Immigrants”. Manjoo’s article attempted to explain why newly inaugurated President Donald Trump‘s attempts to squeeze off the flow of immigrants to the USA was dangerous. He argued that America disproportionately benefitted from allowing big brained foreigners like Veach to find work.
Government seek to attract investment from big foreign players while stopping the brain drain
Mr. Trudeau has lamented a “brain drain” of Canada’s best tech minds, saying at a recent Google event in Toronto, “Quite frankly, we’re tired of Google poaching our best graduates from the University of Waterloo and sucking them down to California.”
.. Trudeau wrote to Mr. Bezos, asking him to consider Canada because of its inclusiveness, single-payer health-care system, and an immigration system designed to attract high-skilled talent.
.. Canada is widely considered to be at the nucleus of some world-leading research in areas such as machine learning and artificial intelligence.
.. Seminal work published by University of Toronto’s Geoffrey Hinton, University of Montreal’s Yoshua Bengio and others has spawned advancements in voice recognition and automated driving. Mr. Hinton published breakthrough research on “deep learning” in 2007 and 2012 that ushered in a new wave of AI and the potential it could have for smartphones, self-driving cars and other devices.
.. Canada’s AI talent pool is also the third biggest in the world behind the U.S. and the U.K., with about 1,100 researchers in the country
.. An Amazon move to Toronto might also end up being a “Trojan horse” that would draw Canadian workers to the company’s Seattle base rather than improve Canada’s economy
.. “The best and brightest Canadian engineers or marketers that operate under Amazon Canada will see their career path head down to Seattle, not in Canada,”
.. He says companies like Facebook have different needs than startups, noting that staff at Facebook’s AI lab in Montreal are focused on more advanced research.
.. Cole Clifford, a 23-year-old machine-learning engineer at Toronto-based startup DeepLearni.ng , said he received about 50 recruiter emails in his LinkedIn account last month, most of them from Silicon Valley firms
.. the Canadian government spent C$125 million last March to set up new AI “superclusters” in Toronto
.. The goal is to keep researchers in Canada and create 1,000 AI graduates in the next five years
.. “We aren’t realizing that the intellectual property developed by these individuals and all of those economic benefits are rarely in Canada and not taxed in Canada,” Mr. Ruffalo said. “That’s the problem.”
.. One potential avenue for keeping foreign companies in check is for Canada to withhold R&D tax incentives
.. Another option is to create a government-backed sovereign patent fund, similar to what South Korea, Japan and France have launched in recent years, which would protect smaller startups from patent claims by foreign companies
it has become clear over the last decade that photosynthesis—where a particle of light comes in from the sun, is absorbed by a chlorophyll molecule, the energy rattles around inside a leaf and gets turned into more leaves—is operating in a very quantum mechanical fashion.
Exactly the same kinds of models that we use to look at quantum computation allow us to understand what’s happening in photosynthesis. It turns out that photosynthetic plants, bacteria, and algae are extremely sophisticated in the way they use quantum mechanics. They use quantum coherence and funky effects like entanglement to get very high efficiency of energy transport.
.. Indeed, what’s happening in quantum information and quantum computing is it’s become more and more clear that quantum information is a universal language for how nature behaves.
.. this centerfold showed which parts of physics were talking with other parts of physics, who in this field was talking with this other field. They had to put quantum information right in the middle because everybody was talking with the people in quantum information.
.. by using ideas from quantum information, we’ve constructed systems that are much better than even the most efficient, naturally occurring system.
.. Twenty years ago, I wrote the first algorithms for how you could program the quantum computers we have now to explore how their quantum systems behave.
.. If you want to find out what happens when you send a photon a few billionths of second backwards in time and have a try to kill its former self, well, we have experiment that tests to see what happens when you do that.
.. It also turns out that quantum computers can detect and identify patterns that are very hard for a classical computer to detect. For example, if you have a huge dataset like the tick-by-tick history of all the stocks in the Dow Jones over the last fifty years, it’s a big dataset.
If you say, “I’d like to process this to find out what a good portfolio would be for me if I can tolerate a certain amount of risk and I want to have a certain amount of return.” Well, with a pretty small quantum computer, the kind that we’re going to have in the next five years or so, you could find the answer to that question much more accurately then you could do on a classical computer.
.. I, myself, am a theorist, so the experimentalists don’t like me to use a screwdriver in their lab because I tend to break things
.. Quantum computers are still at the stage where we have a small number of bits—10 bits that we can use, soon 50 bits, 100 quantum bits that we can use. Even though this is piddling by comparison with the classical computer, because quantum computers for specific problems are so much more powerful than classic computers
.. Lockheed Martin has bought a D‑Wave computer, Google and NASA have bought them, the Army is buying some of them.
.. I’ve been working with the folks at D-Wave to try to figure out why they are successful when they shouldn’t be. Ever since then, I patent everything by the way, even if I don’t know whether it’s going to work or not.
.. The strategy I’ve learned is that there’re a huge number of technologies out there, and we don’t have to adopt them. You don’t have to adopt these technologies.
You can use the ones that you like. You can not use the ones that you don’t like. I don’t use Facebook or Twitter or other social media, because I feel that there’s presence and there’s absence, and then there’s cyberpresence, and cyberpresence is a heck of a lot closer to absence than it is to actual presence.
.. DARPA was the first funding agency to recognize that this role of quantum mechanics in photosynthesis was a very important thing. They created the first program to fund looking at funky effects like quantum coherence and entanglement in photosynthesis and in energy transport.
.. The largest group or concentration of people working on quantum computation are in Canada at the Institute for Quantum Computing, in Waterloo
.. He had this intuition, and he came up with a formal notion of a quantum computer. But for more than five years or so, he couldn’t come up with something where it could do better.
Then when he finally came up with something, he showed where a classical computer takes two or three steps on average to this problem, a quantum computer can do it in one.