The keys to standing up a successful AI lab

Those who work with me know I’m passionate about developing and fostering machine learning talent. In this Harvard Business Review editorial, I share my thoughts on how organizations can grow their AI capabilities – encouraging business leaders to adopt the principles I unequivocally believe in. To go beyond data science and do “real AI” there are three things organizations must do (not-so-subtle hint: it’s all about embracing scientific talent!):

1) Hire the right people

It’s no secret that there’s a worldwide shortage of AI experts. In Canada, the impacts of that challenge are amplified. It’s been well documented that our top Canadian talent is finding what they believe to be greater opportunity at foreign universities, major tech companies and startups in Silicon Valley.

Now that Canada has actively placed a greater importance on maintaining our AI talent, we’ve started to see this exodus slow down, allowing industry and academia to come together to form a thriving AI ecosystem. This effort over the last two years has led to far more opportunities for highly skilled AI experts in Canada, with cities like Edmonton, Montreal, Toronto, Waterloo and Vancouver attracting major investments in this space. But there’s still much more work to be done.

2) Embrace research

Organizations who want to do real AI can’t just focus on AI for its pure business benefit because that ethos won’t attract the right kind of talent. The true experts in this burgeoning, competitive field are researchers who love hard problems and require autonomy to steer their work wherever they see it could produce the greatest impact. For businesses, this means pairing applied research with fundamental research. Pure scientific research is a must for any company wanting to bring AI in-house.

3) Adapt your culture

Finally, to nurture and retain the highly specialized group of researchers currently coming from academia, organizations need to embrace the values of this community. At the top of that value chain is providing the opportunity for them to publish the results of their research efforts. Researchers take pride in contributions they make, so allowing them to publish their work in top-tier academic conferences and journals and collaborate with top academic groups openly and transparently will give researchers what they crave: academic freedom.

This also translates into allowing the transparency of collaboration and open publication that serves to advance the AI community as a whole.

These are the values we’ve strived to follow at Borealis AI. Borealis AI is a place where we give researchers academic freedom, the computational power and access to massive datasets to help solve real-world problems and push the boundaries of machine learning.

Read my full editorial on Harvard Business Review: How to Set Up an AI R&D Lab.