When it comes to the heavily regulated medical space, Robert Brooks says entrepreneurs should steer clear of the launch-it-now-fix-it-later approach favoured by the Mark Zuckerbergs of the world.
“The Silicon Valley idea of ‘move fast and break things’ doesn’t work well in health care,” says the University of Toronto engineering alumnus and CEO of SensOR Medical Laboratories, referring to the Facebook CEO’s original mantra.
It was one of several words of wisdom dispensed by Brooks and fellow U of T entrepreneur Marek Pacal, who founded diabetes detection startup Optiggx, to nearly three dozen attendees at a Health Innovation Hub, or H2i, event this week. The event, held at Autodesk’s offices in the MaRS Discovery District, served to kick off H2i’s HealthEDGE Initiative, which is designed to encourage the creation and prototyping of solutions that address real health-care challenges through workshops, mentorships and a pitch competition.
The University of Toronto’s Rotman School of Management is getting into the technology game.
The business school today launched the Rotman Financial Innovation Hub in Advanced Analytics, or FinHub, in an effort to spur financial innovation and entrepreneurship using potentially disruptive technologies like machine learning and blockchain.
In addition to creating new classes for students, FinHub will encourage research into financial innovation in parternership with U of T’s Faculty of Applied Science & Engineering and department of computer science, as well as promote engagement with the financial industry.
“There’s a lot of disruption in the financial services industry,” said Peter Christoffersen, a Rotman professor of finance and the TMX Chair in Capital Markets.
The television show 30 Rock once joked Toronto is “just like New York but without all the stuff.” But the same can’t easily be said when comparing the two cities’ startup scenes.
At least, that was what Huda Idrees took away from her recent visit to New York City as part of Toronto Mayor John Tory’s two-day trade mission to promote the idea of a cross-border tech corridor to rival Silicon Valley.
Idrees, a University of Toronto alumna who is the founder and CEO of health records startup Dot Health, says many seemed shocked to learn Toronto added more tech jobs between 2015 and 2016 than New York City and Silicon Valley combined.
“It was quite a surprise for most of the people there,” says Idrees, a U of T engineering grad who worked at several local startups before launching her own.
“That’s because, to them, Toronto probably feels like, ‘Yeah, it probably has a tech sector, but it’s probably not very big.”
The artificial intelligence-powered legal research tool built by a University of Toronto startup is boosting the productivity of lawyers – one of whom tells Wired magazine the AI solution makes “you look like a rock star.”
Lawyers at Fennemore Craig in Arizona are using ROSS Intelligence to search millions of pages of case law and write up its findings in a draft memo in about a quarter of the time it would take a human lawyer.
Anthony Austin, a partner at the firm, compared ROSS’s output to that of some first- or second-year associates, but noted a human lawyer was still needed to turn the results into a compelling argument that sways a judge.
“It lets us get to the fun and juicy stuff,” Austin told Wired.
On November 15th ICUBE held their first Women in Tech Workshop featuring Natalie Yeadon, Co-owner and Managing Director of Impetus Digital, and Mary Dimou, Business Development Manager at OCE.
With years of experience in the tech community, both Mary and Natalie were able to provide us with their learning on the two most important aspects of a company’s resources: human capital, and equity.
We often hear about the non-financial indicators of a company’s success, but the practical knowledge and incredible real world advice on how to build a good team, Natalie provided tips and tricks to creating a positive company culture and how to effectively have the “hard talks” with employees and colleagues. Offering knowledge on the practical tools our teams can now utilize to inspire and build relationships early on to find mentors, advisers and employ team members.
Additionally, Mary presented the amazing opportunities for financing and support that many entrepreneurs have access to by the Ontario Centers of Excellence (OCE). Discussing financing tools, business development and scaling we were given key insights that she discovered through her own pivots in her dynamic career path.
The digital tech world has always relished a thrilling zero-to-60 story, but the meteoric ascent of Element AI, a tiny Montreal start-up, was rapid even in an industry where breathless tales of explosive growth are the coin of the realm.
Founded just last year by entrepreneur Jean-François Gagné and University of Montreal computer scientist Yoshua Bengio to commercialize cutting-edge artificial intelligence algorithms, Element in early June bagged an astonishing $102-million equity infusion from a syndicate of venture capital outfits eager to tap into what many in the tech world see as the next major revolution in computing.
Element will use the funds to recruit dozens of highly skilled software engineers and invest in other start-ups in the frothy world of “neural networks,” Bengio’s field. (His own academic research is now being deployed in much-discussed applications such as smartphone apps that can screen for skin cancer.) “It’s one more signal telling the world that Canada is becoming an AI leader,” he says.
One of South Korea’s biggest companies is exploring innovation-related collaboration opportunities with the University of Toronto, the latest in a long line of multinationals to be drawn to U of T’s world-leading research.
A delegation representing LG Electronics, led by chief technology officer Skott Ahn, was at the Ontario Investment and Trade Centre in Toronto this week to meet U of T and Vector Institute researchers, and learn more about the university and its broad interdisciplinary expertise.
Among the topics discussed with LG, a leading global producer of flat panel TVs, mobile devices and appliances: robotics, advanced manufacturing, computer hardware design and artificial intelligence, or AI.
“The University of Toronto is a powerhouse in areas of artificial intelligence,” said David Fleet, a professor in the department of computer and mathematical science at U of T Scarborough.
Last fall, Google Translate rolled out a new-and-improved artificial intelligence translation engine that it claimed was, at times, “nearly indistinguishable” from human translation. Jost Zetzsche could only roll his eyes. The German native had been working as a professional translator for 20 years, and he’d heard time and time again that his industry would be threatened by advances in automation. Every time, he’d found, the hype was overblown—and Google Translate’s makeover was no exception. It certainly wasn’t the key to translation, he thought.
But it was remarkably good. Google had spent the better part of 2016 reworking its translation tool to be powered by AI—and in doing so, it had created something unnervingly powerful. Google Translate, once known for producing stilted but passable translations, had begun producing fluid, highly accurate prose. The kind of output that, to the untrained eye, was nearly indistinguishable from human translation. A 15,000-word New York Times story hailed it as “the great AI awakening.” The engine quickly began learning new tricks, figuring out how to translate language pairs it hadn’t encountered before: If it could do English to Japanese and English to Korean, it could figure out Korean to Japanese. At last month’s Pixel 2 launch, Google took its ambitious agenda a step further, introducing wireless headphones that it promised could translate 40 languages in real-time.
Areti Angeliki Veroniki is a studier of studies.
A scientist at the Li Ka Shing Knowledge Institute at St. Michael’s Hospital, Veroniki’s post-doctoral research at the University of Toronto is focused on pulling new insights from the hundreds of medical studies done on a particular illness – right down to the level of individual patients.
Working under the supervision of Dr. Sharon Straus, a professor in U of T’s Faculty of Medicine and a Canada research chair in knowledge translation and quality of care, Veroniki is performing what’s known as an individual patient data network meta-analysis on studies pertaining to Type 1 diabetes and Alzheimer’s dementia.
Put simply, it’s a statistical analysis of the many studies done on a number of clinical treatments related to a specific illness that, unlike more straightforward network meta-analyses, still takes into account individual data from all the studies’ patient participants.