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The Rise Of Restaurant Robots Amidst Pandemic Measures


In a restaurant landscape where lean profit margins are getting even slimmer due to the necessary COVID-19 safety measures of distancing, staying afloat is an increasingly difficult challenge. Small wonder, then, that some operators are using whatever means they can to stand out from their competition. Robot waiters, although not a new phenomenon, are making headlines around the world again, but this time with a socially distanced twist. At Claypot Rice, a Chinese restaurant in Calgary, robot greeters and servers chat with guests, take orders and run food from the kitchen. These are typically three distinct roles performed by humans, a fact not lost on owner Alex Guo.

Government of Alberta affirms $9M investment in Amii


"Amii exists in large part thanks to crucial investments made by the Government of Alberta, CIFAR and Alberta Innovates – and our partnership with the University of Alberta. With renewed funding, we're able to continue our trajectory of long-established excellence in AI and machine learning and leverage scientific advancement to speed industry adoption, job creation and innovation for Alberta's most forward-thinking organizations."

Artificial intelligence researchers receive $9M from Alberta government


The Alberta government is giving $9 million in funding to the Alberta Machine Intelligence Institute (Amii) in an effort to promote the province's tech sector. The funding is made up of $4 million from Alberta Innovates and $5 million through the Technology Innovation and Emissions Reduction system. The government says it's Investment and Growth Strategy has identified developing Alberta's technology sector as a top priority. They hope it will make way for investment and innovation in other Alberta industries including agriculture, aviation and energy. "Our investment demonstrates that Alberta's government recognizes the important role that Amii and the University of Alberta plays in creating a stronger economy," said Minister of Advanced Education Demetrios Nicolaides.

Canadian police charged a Tesla owner for sleeping while driving


Police in Canada say they recently charged a Tesla Model S owner with driving dangerously for sleeping at his car's wheel. In July, the Royal Canadian Mounted Police (RCMP) say they responded to a speeding complaint on Highway 2 near Ponoka -- a town in Alberta, south of the province's capital of Edmonton. Those who saw the car report it was traveling faster than 140 kilometers per hour (86MPH), with the front seats "completely reclined," and both the driver and passenger seemingly asleep. When a police officer found the 2019 Model S and turned on their emergency lights, the vehicle accelerated to 150 kilometers per hour (about 93MPH) before it eventually stopped. Police initially charged the driver, a 20-year-old man from the province of British Columbia, with speeding and handed him a 24-hour license suspension for driving while fatigued. He was also later charged with dangerous driving and has a court date in December.

[D] Non-US research groups working on Deep Learning?


Almost every group on earth is working on'deep learning' in some form. In Canada there are the big three research units: MILA at Montreal, Vector at Toronto, AMII at Edmonton. Both MILA and Vector have several research groups/universities affiliated to them in Quebec and Ontario respectively. Weirdly folks at UBC are also affiliated with Vector. AMII is mostly University of Alberta.

Tesla driver, 20, charged after found asleep at wheel of self-driving car traveling over 90 mph: cops

FOX News

Fox News Flash top headlines are here. Check out what's clicking on A Canadian man has been charged after he was found asleep at the wheel of a self-driving Tesla traveling over 93 mph down a highway in the province of Alberta, authorities said on Thursday. The July 9 incident occurred after authorities received a complaint that a Model S Tesla was speeding on a highway near the town of Ponoka, located about 60 miles south of Edmonton, according to a release by Alberta Royal Canadian Mounted police (RCMP). "The car appeared to be self-driving, traveling over 140km/h, with both front seats completely reclined and both occupants appearing to be asleep," the RCMP said in a statement.

Alberta Machine Intelligence Institute


As one of Canada’s preeminent centres of artificial intelligence, we thrive in our unique role bridging world-leading research and industry adoption.

Choosing Artificial Intelligence after MS in Theory


As always, it's going to come down to your application and your history. From the sounds of it, you'll be a very strong candidate based on your theory background -- You just need to find the right school / supervisor that will see how to help you pursue those interests. Look for schools with good AI programs. Knowing the research focuses at the CS Department in the University of Alberta, I think you'd have a good shot there with a number of supervisors, both in reinforcement learning and in machine learning. Really though, it's going to come down to a demonstration that you can do the research, via your reference letters, CV, etc.

Trends in Artificial Intelligence in Alberta


Christy Holtby, Managing Director of Partnership and Sales with the Alberta Machine Intelligence Institute, talks about the trends we can expect to see in the province in the future.

Scientists build machine learning model for detecting early signs of depression in text


A new machine learning model can detect early signs of depression in written text like Twitter posts, according to a study by University of Alberta computing scientists. "The outcome of our study is that we can build useful predictive models that can accurately identify depressive language," said graduate student Nawshad Farruque, who designed the model to identify linguistic clues in everyday communication. "While we are using the model to identify depressive language on Twitter, (it) can be easily applied to text from other domains for detecting depression." The English-language model was developed using samples of writing by individuals who identify as depressed on online depression forums. The machine learning algorithm was then trained to identify depressive language in tweets.