one might be tempted to think ‘I can raise it so why not?’ AI companies do need a fair bit of capital as it takes a long time to incubate research and then make it commercially viable, especially when the use cases aren’t immediately obvious.”
Etzioni says: “It really depends on what you’re trying to build and whether you’re planning to build it from the ground up or need to acquire talent and IP. If there are hardware costs—whether it’s chips or robotics—that’s another driver for needing more capital.”
According to a recent CB Insights report, AI companies raised more than $4.8 billion in 698 funding deals disclosed in 2016. By March 23, 2017, before the close of the first quarter, AI startups raised $1.7 billion in 245 deals. That reflects significant growth since 2012, when companies in the sector raised $559 million in 150 deals.
Element AI’s Gagné says the startup’s profit potential makes it a reasonable bet for the investors who have advanced so much money at such an early stage.
“Our platform and business model offers a lot of monetization opportunities,” Gagné told Xconomy. “Either through licensing our technology or consulting, we are creating value and will take in a position where it makes sense for all parties involved.”
Gagné added: “We expect to do 50 projects in the next six to 12 months and currently have revenue in the millions.”
Asked how Element AI charges its clients for helping them solve problems, Gagné says, “it really depends on the situation, sometimes we charge for consulting, sometimes for licenses.”
Element AI says it worked with noted Montreal A.I. research center MILA to craft “a unique, non-exploitative model of academic cooperation” that they have now replicated to many other institutes.
“It’s a very collaborative model where we have Research Labs professors collaborate on a weekly basis in brainstorming/science curation sessions where we provide unique challenges for them to solve,” Gagné told Xconomy. “The interesting thing about it is that they get to collaborate with world-class experts in many different fields during these sessions, something they would never have access to at their lab or conference. The results are very exciting, they are producing more research papers and we are transferring a lot of technology in the commercial applications.”
Gagné declined to elaborate on the terms under which academics help Element AI to work on its projects for clients, or for itself. That leaves open whether the academics, or their universities, receive financial benefits such as consulting fees, shared revenue, and intellectual property rights.
“The work we do on the research front is typically done in an open innovation way,” Gagné says. “That’s all I can discuss at this moment.”
One thing is for sure—there will be more AI experts working for the company. With its new cache of capital, the startup plans to expand globally and hire another 250 employees in the next six to 12 months, Gagné says.
Does the company plan to recruit and/or accept job applications from engineers outside Canada, such as from Silicon Valley?
“Yes absolutely, we have been doing so already as we now have at least someone coming from every continent working at Element AI,’’ Gagné says.
Xconomy editors Jeff Engel, Benjamin Romano, and Angela Shah contributed to this report.
