Element AI from Canada to the World
CAD $200 Million to Accelerate Deployment and Commercialisation
In 2017 Element AI received US$102 million in funding in a series A round led by Data Collective and Microsoft Ventures. On September the 13th 2019 Element AI raised money in a Series B round of financing. It received there CAD $200 million (USD $151.4 million) to accelerate deployment and commercialisation. This, in addition to a few other investments, is bringing the total amount raised so far to CAD $340M (US $257M).
About Element AI
Element AI is an artificial intelligence company based in Montreal, Quebec and was founded in October 2016. It was founded by Jean-François Gagné and co-founders Yoshua Bengio, Anne Martel, Nicolas Chapados, and Philippe Beaudoin, along with Jean-Sébastien Cournoyer of Montreal venture capital fund Real Ventures.
Element AI Research
It is stated about Element AI the importance of its focus on research, and this makes sense due to its founders, one of whom is one of the central figures in the new focus on artificial intelligence, Yoshua Bengio.
“Element AI maintains a strong connection to academia through research collaborations and takes a leadership position in policy-making around the impact of technology on society.”
They list as part of their research team the following:
- Yoshua Bengio, PhD. Co-Founder & Deep Learning Pioneer. Widely considered one of the three pioneers of deep learning, Dr. Bengio is a world-renowned researcher with more than 300 publications and over 80,000 citations to his name.
- Marie-Claude Coté, PhD. Director — AI Core and Applied Research Practices. Prior to joining Element AI, Marie-Claude worked as an operational researcher at ExPretio technologies and led the Data Science team at JDA Software, a company specializing in execution and planning systems for the supply chain and retail sectors.
- Christopher Pal, PhD. Principal Research Scientist. Christopher Pal is an associate professor in the department of software and information engineering at Polytechnique Montreal and an adjunct faculty member in the department of computer science and operations research at the University of Montreal.
- Negar Rostamzadeh, PhD. Fundamental Research Scientist. Negar Rostamzadeh is a Research Scientist at Element AI. Her areas of interests are Machine Learning (particularity deep learning approaches) applied to Computer Vision problems (mainly Video Understanding). Negar got her Ph.D. at the Mhug (Multimedia and Human understanding) group, University of Trento, Italy.
- David Vázquez, PhD. Fundamental Research Scientist. David Vázquez is a Fundamental Research Scientist at Element AI, where he works on computer vision. Previously he was a postdoctoral researcher at Computer Vision Center of Barcelona (CVC) and Montreal Institute of Learning Algorithms (MILA) and Assistant Professor in the Department of Computer Science at the Autonomous University of Barcelona (UAB).
- Anqi Xu, PhD. Fundamental Research Scientist. Anqi is a Fundamental Research Scientist at Element AI. Anqi has over 10 years of research experience with diverse facets of mobile robotics, including human interaction, perception, control, localization, and planning. He holds a PhD in Computer Science from McGill University, where he studied trust in human-robot interactions.
They additionally have a network of research fellows. The slogan on their website is: “Join us in solving the world’s toughest problems with artificial intelligence.”
How AI can Help with Climate Change
In a recent blog post written by Alexandre Lacoste, a research scientist at Element AI the title was: “Climate Change: How Can AI Help?” He was part of authoring the report “Tackling Climate Change with Machine Learning,” which I have mentioned previously as an important step in the right direction for the AI community. There is apparently a recording of the event at ICML in 2019 worth taking a look at.
“I believe that AI and climate change represents a vital but too often overlooked area of research with enormous potential. Our workshop and paper will, I hope, help draw attention to the important work already in this space and encourage new approaches. We need to find high-impact solutions and make sure that many of them can be implemented within 20 years.”
He is part of running a workshop at NeurIPS in 2019 on the topic of Tackling Climate Change with Machine Learning.
This is day 118 of #500daysofAI. If you enjoy this article please give me a response as I do want to improve my writing or discover new research, companies and projects.
