Through the Eyes of an Intern 2016 Part 4: A.I., Deep Learning and the Future

Jul 01, 2016

Written by: Alyssa Wadey 
Marketing Intern, NEXT Canada

Appropriately hosted at Google Canada, Venture Preview Night was structured around the keynote address, “Artificial Intelligence, Deep Learning, and all that”.  Delivered by the Chief Science Officer of Imagia Inc., Nicolas Chapados, the keynote speech addressed the growing industry of artificial intelligence and deep learning, especially within the start-up ecosystem.

A.I. is a monstrous topic, but if there was one quote from Nicolas that could summarize his whole address it would be: “A.I. isn’t about replacing jobs, it is about amplifying intelligence”. For those of you who, like me, may have had minimal exposure to the brilliance of machine and deep learning, here are the definitions Nicolas provided us with: Machine learning (noun): algorithms that learn from and make predictions on data.

Deep learning (noun): machine learning that uses data to learn how to solve tasks The deep learning revolution, as Nicolas put it, has been Canadian-led since its first breakthrough in 2006. A current example of A.I. power, provided by Nicolas, is the ability for a computer to translate images into text, and a future use would be for a computer to reason and answer questions. 

After Nicolas’ inspiring keynote address, he called up three founders developing solutions using A.I. to join him on a panel.: Ben Alarie, a Next Founder and co-founder of Blue J Legal, a legal testing company using machine learning to provide answers in grey areas of tax law; Ron Glozman a N36’er and  co-founder of Knote, software that helps you work smart by automating work flow; and Scott Everett, an industry leader and co-founder of Eigen Innovations, a tech start-up that provides software solutions for the Industrial Internet by leveraging Big Data information from industrial equipment.

After Nicholas’ keynote, the audience of mentors, advisors, entrepreneurs, and investors was burning with questions for the panel. My personal favorite was directed to all panelists and revolved around semi-supervised learning. Nicolas led this discussion by providing a quick definition. In short, he elaborated by describing that semi-supervised learning is indicative of this current transitional period for machine learning: one where humans still oversee and aid the training of the program but the computer does most of the work. For example, Knote must analyze over 10,000 documents – with both software and human capital – in order to train the computer to get the correct answers. Blue J Legal currently staffs 10 law students each summer to compile the data sets necessary to train their software. It was fascinating to hear the panelists discuss the effects of machine learning on their respective industries: Ron with natural language processing, Ben with the legal sector, and Scott with industrial manufacturing.

Post-panel, I had the chance to catch up with the N36’ers. I wanted to know more about their startup journeys and progress as part of the summer program. Many of the N36 ventures are making big strides as they gear up for Venture Day next month. For instance, DYME Fitness, a tailored nutritional products company, is in the process of developing their second product line, and recently partnered with a large American manufacturer. Tandem, a live workspace for developers, has recently integrated with UXP Systems to test their software in three different countries, and has intent-to-pay trials in the pipeline. They’re optimistic that they will be cash flow positive by Venture Day.

It hasn’t been smooth sailing for everyone, though, and for many N36’ers, some course correction has been needed along the way. Giorgio Delgado, co-founder of Moranda, says that the N36 class work allowed him and his co-founders to realize their original venture idea didn’t have the correct framework to become a disruptive business, so they implemented what they learned in class into their pivot. Now, they’re working on a Slackbot that aggregates important conversational information for teams. Further, Giorgio said that “the network itself, being around all these people, [has been] invaluable”.

Similarly, Tandem co-founder Nishant Samantray said that the network and the classes have been the most beneficial to him: “I find motivation in the classroom atmosphere, especially from Reza Satchu, who pushes me to prove myself daily.”

One of my personal favorites was from Tom Grainger, the co-founder of Cultivate Compliance, a company that provides software to make compliance easier for businesses in the agricultural supply chain; Tom said a unique aspect of N36, on top of the connections he has made, was the the fact that “everything that has happened to [them], good or bad, [they were] given a lot of warning about, and none of it [was] real until it [happened]”.

It was when I reached the ground floor of Google and saw a bubbly crowd of founders and guests spill reluctantly out onto the sidewalk that I realized what a success the evening was. It’s plain to see how far the N36 and Next Founders cohorts have come – both individually, and as teams – over the past three months. They’ll spend the next few weeks soaking up more information and fine-tuning their ventures in order to present the best version of them on Venture Day. Stay tuned for my next article to see how this cohort finishes off the summer.