NextAI welcomes first startup cohort

INAUGURAL PROGRAM LAUNCHES WITH 20 TEAMS

Revolution AI

Anew wave of AI startups has hit the fast track with NextAI’s inaugural program for entrepreneurs. This first cohort of 20 teams is made up of wouldbe entrepreneurs and students from across Canada and around the world interested in making their mark on the AI ecosystem — whether it’s in robotics or chasing dreams.

The qualifying candidates range from idea-generating individuals looking for an application to put their machine learning skills to use, to newly formed companies seeking ways to leverage AI for their solutions. Half the participants are international, the other half homegrown innovators.

The areas of research and development are equally eclectic, ranging from fintech, medical and robotics to HR, education and debt-collection applications. One team, Cerebrian, is even working on dream-recording technology.

“We were looking for very special skill sets from the applicants,” says Graham Taylor, academic director at NextAI, which is based in Toronto. “We weren’t just looking for teams with the potential to be business leaders, but also for what they can do for other people in the programs, whether it’s leadership skills, or AI and machine learning expertise.”

As such, there were two main criteria that led the selection process, he adds. “The first was the idea, the other was technical ability. In most situations, teams excelled in both. But in certain cases they excelled on one or the other side, but we felt they would be valuable to other teams.”

NextAI was launched by NEXT Canada — a non-profit charity — to fund, support and mentor entrepreneurs working on artificial intelligence technology. It is open to Canadian and international university students, professionals and entrepreneurs interested in developing AI-based solutions for commercialization.

Each of the 20 teams selected receives $50,000 in seed funding and an opportunity to access an additional $150,000 depending on their progress. They also receive technical and business training from top university faculty in North America, as well as access to technology platforms and training with technology partners.

The program, hosted in a “founder friendly” office-sharing spot called Project Spaces, runs to September, allowing ample time for participants to build their companies. At times they will follow a structured curriculum, at others they will be developing prototypes and sharing knowledge with their peers. It culminates in an AI Demo Day, at which they pitch their ideas to corporate partners, investors, business leaders and others.

Every participant has a different story to tell about their vision and purpose for being there. For example, David Vradenburg and Noel Webb are co-founders of Karen.ai, a recruiting assessment tool for talent acquisition. Their hope is that the program will connect them to the AI resources they need to reach the next level. “One thing we liked is the ecosystem presented to us,” Webb says. “It will allow us to begin to compete in a larger market space.”

While Vradenburg has a software engineering background, he says they are working toward learning AI as well as recruiting AI talent to help build its systems. “Here we have access to data and a network of world-class people.”

Dan Yang is at the opposite end of the spectrum. One of the few individuals accepted into the program, she has been studying machine learning since 2004 and has published on the subject. Her particular area of interest is research engines. While she has previously started companies, she admits “It was too early. The timing was not right.”

Yang believes the NextAI program will help her build her business skills. “I’m a self-starter, but I lack business training and I’m not so good at networking,” she says. “I’m here so I can get some real training and apply my academic strengths to commercialization.”

In a few cases, teams were the result of a match-making process. PetroPredict, for example, matched Roi Shabshin from Tel Aviv with Dudon Wai from Calgary to work on a business intelligence tool for the oil and gas industry that combines machine learning, natural language processing and computer vision with predictive analytics.

Taylor says much of the success of the program hinges on corporate support, as they provide access to the vast data needs of AI projects, as well as take on the role of early adopters of products and services. “One of the barriers to building an AI company is lack of access to data. That’s where sponsors come in, because they have the biggest pools of data but are not fully exploiting (them) yet.”

Ultimately, programs such as NextAI provide a key opportunity to build some critical mass in the AI space in Canada, Taylor believes. “A lot of people are leaving the country to go to Google Brain, Google DeepMind or OpenAI. But we want to attract and keep them here. If we can bring people in and build companies, we will have more amazing technical talent in our ecosystem.”