Radical Reads: Venture Outlook 2022

Sanjana Basu, Investor


Image Source: Headshot by Jeff Beardall


Venture capital investments in 2021 reached US$643 billion across the globe, almost doubling 2020’s record. Canada also set VC investment records in 2021, and investors have even more capital to deploy in 2022, and likely at a faster pace. Canada is now a top 3 target for US international investments, and we expect US interest in Canadian technology startups will continue to grow. Behind this surge in investment interest is a growing recognition of Canada’s extraordinary pool of talent, especially the high concentration of leading AI talent in our ecosystem.


Healthcare, in particular, remains a vertical hungry for technology-led innovations to solve today’s challenges. Over the last two years, AI has played a role in fast-tracking the medicine-to-market process. Higher trust amongst stakeholders has led to increased adoption of AI across all areas of healthcare delivery. Traction will drive up investment interest in healthcare AI companies. In 2022, we expect to see more Canadian companies leveraging their unique position at the centre of world-class health talent and machine learning researchers.


Looking forward, we believe Canada’s vibrant entrepreneurial ecosystem will expand its influence on 2022’s global stage.

Editor’s note: You can read more on Sanjana’s venture industry predictions for 2022 in The Logic (subscription required). Sanjana is a regular contributor to Radical Reads. She authored Canada’s AI in Healthcare Market Map, and our 2020 AI and healthcare thesis: The Adoption Imperative


5 Noteworthy AI and Deep Tech Articles: week of January 10, 2022


1) As third-party cookies fade, the cold start problem becomes an opportunity (VentureBeat) 

As browsers look to address privacy concerns by removing cookies that track user activity across the Web, businesses are stuck looking for other ways to personalize consumer experiences. Not knowing anything about a potential customer that lands on a company’s homepage is known as the ‘cold start problem.’ Alexandre Robicquet, CEO and co-founder of Radical Ventures portfolio company Crossing Minds, explains why the cold start problem matters and the transformational opportunity presented by “the demise of the third-party cookie.” The technology developed by Crossing Minds allows every consumer-facing business to deploy meaningful recommendations while preserving their customer’s privacy. 


2) How AI could prevent the development of new illicit drugs (Scientific American) 

David Wishart, a computer scientist and biologist at the University of Alberta, and his colleagues have developed a deep learning algorithm to identify potential designer drugs that may not yet exist. Identifying millions of chemicals could help governments stay ahead of illicit labs producing recreational drugs by making small chemical tweaks to known substances. The US Drug Enforcement Administration and the United Nations Office of Drugs and Crime are among the agencies already testing the algorithm. 


3) Researchers create novel algorithm for verifying quantum devices (APS Physics)

Researchers at The University of Tokyo developed a practical and approximate tomography method using a recurrent machine learning framework for verifying quantum devices. This is a small step toward practical quantum computing and could help efforts to realize a quantum internet able to transmit large volumes of data across immense distances at a rate that exceeds the speed of light. Almost all applications would benefit from such speed increases. 


4) Future of Work: Computer vision and machine learning may soon bolster restaurant jobs (Washington Post) 

Chipotle CEO Brian Niccol expects the restaurant industry to adopt more emerging technologies to deal with supply chain issues and restaurant efficiency. In recent years fast-food chains such as McDonald’s have increasingly piloted AI technologies. Rather than replacing workers, this round of technology adoption aims to support day-to-day operations. For example, Chipotle is using vision sensors to identify in real-time how much guacamole is made and offer predictions for how much will be needed in the future. The hope is to avoid both waste and customer disappointment.


5) AI can now craft jokes — But it’s no laughing matter (Time)
Computing humour has been in the popular consciousness for over half a century. Computer science researchers have tested AI’s ability to improve their jokes or generate new punchlines. In this latest step toward funny machines, researchers have trained a tiny android to perform a comedy sketch and respond to the audience. While some believe humour will remain the domain of humans, “the goal isn’t to build a thing that will make the laughs for us, but instead, one that can help humans find new things to laugh about.” As with any new technology, the AI’s power will come from the way users choose to interact with it, “with results that no one may yet have imagined.”


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