- AI derives insights from data that is usually collected, but not interpreted, by companies. So it has the potential to transform any industry by supplementing, assisting and improving computational processes aimed at identifying valuable data trends and business insights.
- Canadian entrepreneurs, who tend to be more risk-averse, need to take more risks and dream big. Our youth should take entrepreneurial risks and university is the perfect time to do so because those risks do not have extreme side effects.
- AI will replace low-skilled jobs but assist and enhance high-skilled ones, rather than replace professionals.
Canada is performing exceptionally in the field of AI research, but it is now time to commercialize some of the technologies developed in our labs. Private and public investors as well as universities should support incubators, which take research to the next level.
Do you see AI as a force for transformation within industries or as an industry in itself?
AI is a transformational force for the entire economy. It is capable of supplementing, assisting and improving computational processes in any industry. Each industry has been capturing numerous trends in its data for many years, but they have been locked away in silos. These are trends or patterns that humans have never been able to compute or see. But once we give that data to an algorithm or machine-learning systems, we are able to start finding these patterns and drive insights for a specific business. Most startups at this time are going after current, established industries. So you can sprinkle AI in any recipe or any industry and it would taste better.
Who are the key stakeholders of the Canadian AI revolution and what role should they play in it?
I would divide the stakeholders into three categories: academic institutions, entrepreneurs, startupsand investors, which include the government. Basically, academic institutions are the fuel for Canada’s AI revolution. Most pioneersof AItoday, like Yoshua Bengio and Geoffrey Hinton, started out of academic institutions such as the University of Montreal and the University of Toronto. They would not have grown if thefederal, provincial and local governments had not backed them. The government put in place incentives, which encouraged the expansion of Canada’s AI ecosystem and the creation of institutions like CIFAR. So, Canada now has AI startupswilling to take risks and also a whole ecosystem of industries willing to support these risk-takers.
Incubators play a major role in the systematic shaping of an ecosystem and I think both, the government and academic institutionsshould fund and encourage the efforts of such incubators.
“Academic institutions are the fuel for Canada’s AI revolution.”
My advice to entrepreneurs would be to dream big. Reza Satchu, one of the founders of NEXT Canada, rightly believes that Canadians have extremely modest expectations compared to our counterparts that went toHarvard, MITor other places. We always try to go for bronze rather than gold. We need to dream big and aim for gold from the very beginning.
The Creative Destruction Lab founded by Ajay Agarwal at the Rotman School of Management is another pioneer in this space. It is the only platform in Canada that has managed to put seasoned entrepreneurs and investors in the same room as young startups trying to make their way through the ecosystem. This setup is a prime example of going for the gold. Ajay has brought in the best of the best throughout the world to mentor those who are just starting out to ensure the highest success rate, facilitating the rapid growth of the Canadian AI ecosystem.
As a young AI entrepreneur, what are the industry-specific challenges that you are currently facing? Do you have any advice for other Canadian youth interested in AI?
In general, people are a bit more risk-averse in Canada; they need a lot of validation, proof and data to get involved in an initiative. In contrast, when I worked down in California with Tesla Motors, people there were proud of their entrepreneurial spirit and wore it like a badge.
My advice to any youth would be to take an entrepreneurial risk. University is the perfect time to start taking risks because you can either win or learn from your experiences.
“Both governments and universities should fund and encourage incubators.”
Canada does have amazing support systems like NextAI. Intuitive would not exist without NextAI’s unlimited support and guidance. When you are starting a company, advice from mentors is the most important, and NextAI provided us access to them.
I also highly recommend everyone out there to read Anthony Lacavera’s “How We Can Win: And what happens to our country when we don’t”. It is a really inspiring read that reiterates the idea that we, as a nation, need to accept that we are capable of winning the gold and then we must go get it!
Experts claim that not just low-skilled, but also high-skilled jobs are at risk of automation due to AI. How do you think today’s youth can better prepare itself for the jobs of the future?
AI start-ups or entrepreneurs currently consider low-skilled jobs the low-hanging fruits to go after. There are jobs out there devoid of any creativity or intellectual challenges, that no human can possibly enjoy doing. For example, Intuitive is trying to relievepeople who sort trash at waste stations. Why does a human need to sort waste? Which human would want that job? In addition to the soul sucking nature of the work, there are also plenty of health hazards involved when one deals with trash on a daily basis. For instance, there are many dangerous items that could possiblycut the person while sorting, not to mention increasings susceptibilityto diseasesspread through waste matter.So currently, many startupslike ours are trying to optimize the efforts of the labour forceand increase our society’s productivity as a whole.
The use of AI in high-skilled jobs is mainly to assist, rather than replace human professionalssuch as doctors, engineers or architects. AI is reducing the cost of prediction, but the value of a specific doctor or engineer’s judgment will increase because AI will be able to provide accuratepredictions.
“STEM needs to be at the core of education, but we must integrate soft skills into the curriculum.”
STEM has been lacking soft skill education, specifically in the technological or engineering departments. In the future, most of the heavy lifting will be done by the AI or the robot. So we will need people to work in teams, grow teams and create companies because robots are not going to do that. The key skills that our youth need to start acquiring are communication, creativity, adaptability and interpersonal skills. STEM needs to be at the core of education, but we must integrate soft skills into the curriculum.
How is Intuitive leveraging AI to drive sustainability and what is your long-term goal?
The social problem Intuitive is tacklingis that of waste contamination. Everyperson in the world generates waste, and the majority of this waste ends up in landfills. Landfills are essentially time bombs; they are areas of land that release methane gasover time and leak leachate and other harmfulchemicals into our water tables. Additionally, when plastic waste enters oceans, it comes back to harm us through the food chain, not to mention the damage it does to the marine ecosystems.
The majority of waste that does not end up in landfills, oceans, is incineratedor gets pushed tothird-world countries. A very tiny percentage of waste is actually recycled and it makes no sense that we are either burning or burying materials that we mined out of the ground. That is not very intuitive, and it is partly because most of us lack the ability to sort waste appropriately to facilitate recycling down the line. When this was researched with organizations with massive footprints, it was clear that in order to reduce waste, they had to continuously measure what they were producing and if their solutions were working.
“Canada now has AI start-ups willing to take risks and also a whole ecosystem of industries willing to support these risk-takers.”
My Co-Founder Vivek Vyas and I,decided to approach this problem by combining computer vision and machine learning to develop a waste-recognition technology that is able totackle this issue head-on. Intuitive targets the three to six second window that people have right after finishing theircoffees or lunches,as they are approachingthe nearest garbage bin to dispose ofitems. Our technology can go on top of any garbage bin and it detects the item held by the person approaching the bin. It reacts by showingpeople a fun and interactive way of disposing theiritem into the correct waste stream while providing facilities insights on their waste stream. We believe that people generally want to do the right thing and ourtechnology offers a nudge so that people feel rewarded for recycling. Eventually, we will start rewarding people every time they recycle.
Currently, we are introducing our systems in sustainability-focused organizations, but eventually we want to be able to close the loop. Most of the garbage is produced at the household level and is sent to a disposal facility. We want to ensure that no garbage that enters our zero-waste facility ends up in landfills, oceans or third-world countries. Our goal is not to get sympathy from people but to gamify recycling. Our vision is to empower a zero-waste world by developing intuitive technologies that could be applied to many industries or verticals.