Radical Reads: Ontario’s AI Momentum by the Numbers

By The Editorial Team

The Vector Institute for Artificial Intelligence’s latest Ontario AI Snapshot, prepared by Deloitte, finds that Ontario’s AI ecosystem continued to strengthen over the past year, attracting billions in new investment, creating over 20,000 new AI jobs – a massive 210% increase from the previous year – and developing more new AI talent than ever before through its affiliated graduate degree programs.

Canada’s AI pedigree is no accident. The Canadian Institute for Advanced Research (CIFAR) and the Natural Sciences and Engineering Research Council of Canada (NSERC) were funding the work of AI pioneers Geoffrey Hinton, Yoshua Bengio, and Richard Sutton long before the work of these individuals would define a new era of innovation. As their breakthroughs made the leap from the lab into real-world applications, focused government investment through the world’s first national AI strategy (co-authored by Radical’s founders), paired with commitments from the private sector, anchored this community in Canada, establishing centres of excellence with the shared mission of attracting world-leading research talent. 

Today, the Vector Institute for Artificial Intelligence (co-founded by Radical’s founders Jordan Jacobs and Tomi Poutanen with Geoffrey Hinton and other professors at the University of Toronto, and chaired by Radical partner Ed Clark), the Quebec Artificial Intelligence Institute (Mila) and the Alberta Machine Intelligence Institute (Amii) are major hubs in the hyper-competitive global AI talent landscape, and engines of their respective AI/tech ecosystems.

Toronto, Montreal, and Vancouver have seen robust growth in startup activity. Ontario’s AI ecosystem alone attracted $2.86 billion in venture capital investment, a 206% increase over last year. As well, 273 unique corporate investors made direct investments in Ontario-based AI companies, a 29% rise over last year. We can expect these numbers to continue growing as more than half of business executives surveyed believe that AI plays a strategically important role in achieving their company’s business objectives.


5 Noteworthy AI and Deep Tech Articles: week of November 13, 2022

1) ClimateAi Forecasting Tool: TIME’s Best Inventions of 2022 (TIME)
Radical portfolio company ClimateAi‘s forecasting tool is one of TIME’s 200 best inventions of 2022. Capable of predicting weather and climate up to 10 years into the future at a hyper-localized level, ClimateAi enables more resilient food and other supply chains in the face of climate change. ClimateAi is noted alongside other world-class inventions including the NASA James Webb Space Telescope and DeepMind’s AlphaFold.

2) You.com Ad-Free Search: TIME’s Best Inventions of 2022 (TIME)
Radical portfolio company You.com’s next-generation search platform was also named one of TIME’s 200 best inventions of 2022. You.com Co-Founder and CEO Richard Socher is challenging Google by reimagining search and leveraging large language models to deliver better results, giving users privacy and other controls over their online experiences.

3) The Wunderkind who Won over NASA, Stanford and Peter Thiel (The Information)
A profile of George Sivulka, the driven and charismatic founder behind Radical portfolio company Hebbia, on his early days interning for NASA, securing funding from Peter Thiel and the creation of an NLP-powered search engine capable of reading and comprehending the universe of unstructured data trapped inside companies. 

4) Technology readiness levels for machine learning systems (Nature)
In Nature Communications, MIT Media Lab Director Dava Newman and co-authors present a framework for more robust, reliable, and responsible machine learning systems. The paper applies some of the principles used in engineering domains such as civil and aerospace engineering, to machine learning algorithms. These principles find their fullest expression in spacecraft systems, where every step of the development process takes mission-critical measures and robustness into account.

5) Ukraine’s Crop Storage Infrastructure: Post-Invasion Impact Assessment (Conflict Observatory)
Neural networks are helping humanitarian observers measure the extent of war damage to Ukraine’s grain crop. Analysts from the Yale School of Public Health and Oak Ridge National Laboratory built a computer vision model that detects grain-storage facilities in aerial photos. Its output helped them identify facilities damaged by the Russian invasion.

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