Promise Robotics CEO Ramtin Attar with a few Kuka Industrial robots similar to ones fitted with custom tooling developed by Promise Robotics to perform complex construction tasks. Robots constructing homes may sound like science fiction. Yet a Toronto-based startup aims to make this futuristic idea a reality within the next year, leveraging advances in automation, advanced manufacturing, cloud computing and artificial intelligence (AI). Promise Robotics was launched in 2019 by founders Ramtin Attar – a former technology lead at a multinational technology company – and Reza Nasseri, the chief executive officer of Landmark Homes. The technology company, which also has operations in Edmonton, seeks to bring emerging technologies to the home building industry to address the industry's biggest challenge: meeting the rising demand for housing amid a growing shortage of affordable homes.

Maplesoft offers AI-backed technology that can help students solve math problems. Our brains have long relied on machines to help with mathematics – calculators being the most obvious example. Waterloo, Ont.-based Maplesoft offers AI-backed technology that can help students solve math problems, check their homework and explore graphs in 3-D within seconds. "Our mission is to just make math more accessible," says Karishma Punwani, Maplesoft's director of academic products. "We want to change the way students view, learn and access math to help them see the awe in it." The Canadian-built technology isn't only used in the classroom: Maplesoft's software is also used by engineers and researchers at organizations such as Google, NASA, the Canadian Space Agency and research labs around the world.

Dan Eisenhardt, founder and CEO of Form Athletica Inc., wears the company's swim goggles, which have a smart display inside them, in North Vancouver, on June 7, 2021. It was during an entrepreneurship class at the University of British Columbia 15 years ago that Dan Eisenhardt came up with the idea to make performance-tracking swim goggles similar to what runners and cyclists were starting to use on their wrists. It was a far-fetched idea back then, Mr. Eisenhardt recalls, a life-long and college-level competitive swimmer, but he put a team together to develop the concept. It turned out it wasn't possible – then. "Back in 2006, you didn't have the level of miniaturization in electronics that you have today, so we ended up pivoting for this school project into ski goggles instead," Mr. Eisenhardt says.

This is part of a Globe and Mail series in which Beijing correspondent Nathan VanderKlippe looks at China's present and future challenges before his return to Canada. The people tapping on keyboards at Liang Zhi Data Technology possess an unusual set of skills. Some have backgrounds in artificial intelligence, a skill set that has grown common across the Chinese high-tech companies. They are experts in economics, and their work at Liang Zhi is to find new ways of making decisions from data. Mr. Shao stands at the forefront of a bid to bring authoritarian capital – the Chinese economic model – into the supercomputer age.

In health care, the promise of artificial intelligence is alluring: With the help of big data sets and algorithms, AI can aid difficult decisions, like triaging patients and determining diagnoses. And since AI leans on statistics rather than human interpretation, the idea is that it's neutral – it treats everyone in a given data set equally. In October 2019, a study published in the prestigious journal Science showed that a widely used algorithm that predicts which patients will benefit from extra medical care dramatically underestimated the health needs of the sickest Black patients. The algorithm, sold by a health services company called Optum, embodied "significant racial bias," the authors concluded, suggesting that tools used by health systems to manage the care of about 200 million Americans could incorporate similar biases. The problem was fundamental: The commercial algorithm focused on costs, not illness. In looking at which patients would benefit from additional health care services, it underestimated the needs of Black patients because they had cost the system less. But Black patients' costs weren't lower because the patients were healthier; they were lower because they had unequal access to care.

Researchers say the new technology, termed BearID, created a'non-invasive' technique to study the animals. Despite a decade of behavioural research on grizzly bears in B.C.'s Knight Inlet, Melanie Clapham still has trouble telling some individual bears apart. Brown bears, which include grizzly bears, can change dramatically in their appearance during their younger years and, unlike other wildlife that has spots or stripes, they lack distinguishing markings on their bodies. Ms. Clapham, a conservation biologist and postdoctoral research fellow at the University of Victoria, dreamed of technology that could help her individually identify these furry mammals. While she was looking for a tech team to make that idea possible, south of the border, Ed Miller and Mary Nguyen, two Silicon Valley engineers who are also outdoor and wildlife enthusiasts, had started a project to develop machine-learning models that could be adapted to grizzly bears.

Heyday co-founders Steve Desjarlais, left, and Étienne Mérineau stand in the company's Montreal office on Sept. 30, 2020. When COVID-19 hit, forcing people to stay home, Heyday AI knew its chatbot technology would be vital for retailers that could no longer converse with their customers in person. But the Montreal-based company also knew landing new clients would be a challenge given the cancellation of big tech events where it often drums up business face-to-face. "A lot of [those] sales ... bank on relationships, and therefore you need to meet in person," says Étienne Mérineau, who co-founded Heyday in 2017 with Steve Desjarlais, David Bordeleau and Hugues Rousseau. Heyday uses artificial intelligence to help retailers communicate with customers on websites and across various apps and programs such as Facebook Messenger and Google Maps.

Sheema Khan is the author of Of Hockey and Hijab: Reflections of a Canadian Muslim Woman. The warning signs had been there all along. An assault on a 15-year-old boy; death threats against the man's own parents; a police safety bulletin warning of his gun stash and desire to kill a cop; violent attacks against his spouse; a weapons complaint to the RCMP; fear by neighbours and relatives of his sociopathic behaviour; rampant alcoholism. As an in-depth Globe feature reported, the nation's worst mass shooter "was the kind of man who made people nervous, bragged about knowing how to dispose of bodies and built miniature coffins as a hobby." As we wait for the launch of a public inquiry, there are so many questions about the horrible incident in Nova Scotia.

Dr. Alan Bernstein is president and CEO of CIFAR and was the founding president of the Canadian Institutes of Health Research (CIHR) during the SARS epidemic As president of the Canadian Institutes of Health Research (CIHR) in 2003 when an earlier coronavirus, SARS-CoV-1, swept through Canada, I had a unique vantage point from which to view Canada's response to an unprecedented threat to public health. Today, as I watch Canada's response to COVID-19, it's striking to me how much we've learned about the science and policies needed to address such crises. By and large, Canadians trust their governments, and our ministers are responding admirably to the crisis. I've been impressed with the consistent and clear communication, the co-ordination with the provinces and the rapid implementation of very significant financial packages aimed at dealing with the economic, social and health consequences of the pandemic. I'm proud that Canada has a socially cohesive society in which we place a high value on community well-being.

Andy O'Brien, CEO of M&M Food Market, is photographed in the company's Toronto offices. At M&M Food Market, the most valuable product isn't necessarily the food, but the mix of different ingredients the company uses to grow in Canada's highly competitive grocery and prepared meals sector. The recipe isn't complicated: Take a well-known brand – M&M Meats until the company rebranded in 2016 – add a helping of customer data and sprinkle it with predictive analytics and artificial intelligence tools. A company that has gone from a niche purveyor of bacon-wrapped filet to a data-driven prepared-food business tuned into customer habits and desires. M&M's mission today is to be agile and attentive to the appetites of millions of regular customers across Canada, says its chief executive officer, Andy O'Brien.