Photo credit: Serj Marco, Ukraine
Predicting what comes next in the rapidly evolving field of artificial intelligence is simple: Follow the talent… Like Benjamin Franklin knotting a key to a kite in a lightning storm, Canada’s artificial-intelligence researchers are unlocking technology that is reshaping our world. Every facet of our economy and lives stands to benefit from breakthroughs in AI.
— “Lightning to lightbulb: accelerating Canada’s AI opportunity,” Aaron Brindle and Leah Morris, Globe and Mail, March 26, 2021
Despite Canada’s pioneering AI pedigree and growing talent base, global competition continues to mount. This week we released our 2021 Primer on Canada’s AI Research Ecosystem. In the report we explore the key pillars underpinning Canada’s vibrant AI ecosystem, drawing on in-depth research and conversations with leaders from Canada’s AI research institutes including the Alberta Machine Intelligence Institute (Amii), the Quebec Artificial Intelligence Institute (Mila), and the Vector Institute for Artificial Intelligence (Vector).
Our recommendations for Canada to keep pace with global AI innovation have three focus areas: talent, capital investment and policy (including, critically, policies regarding data). First, investment in commercialization must accelerate, via venture capital and also from Canadian industry which must continue to expand AI adoption through commercial partnerships. Second, business and the public sector must prioritize AI commercialization enabling policies including responsible data sharing. Finally, we must continue to invest in basic, curiosity-driven AI research. For investors and enterprises looking to accelerate Canada’s AI flywheel, it is important to understand these three essential drivers of the ecosystem. While the primer explores these areas in detail, a shortened version was published this week in the Globe and Mail.
5 Noteworthy AI and Deep Tech Articles: week of Mar 29, 2021
1) It is Time to Negotiate Global Treaties on Artificial Intelligence (Brookings Institute)
The US National Security Commission on Artificial Intelligence has stated that there is an increasing US national security crisis due to insufficient investment in AI and emerging technologies. The Commission Chair, Eric Schmidt, noted the increasing competition with China and the shrinking US lead. Schmidt alluded to the Commission’s worries when we caught up with him on our podcast, Radical Talks. (Eric Schmidt is an investor in Radical Ventures).
2) Is Coffee Good for Us? Maybe Machine Learning Can Help Figure It Out. (The New York Times Magazine)
When it comes to understanding how our diet affects our health, both observational and randomized clinical trials have significant limitations. By processing vast amounts of data, machine learning could transform the ability of nutrition researchers to study their subjects’ behaviour “more precisely and in real time.” With a well-organized and coordinated effort we may eventually be able to put an end to the coffee debate.
3) Five Ways AI can Democratise African Healthcare (Financial Times)
The hype around AI transforming healthcare in lower income countries has been met with structural challenges such as a lack of suitable clinical information systems and ML auditing capacities. Darlington Akogo, founder of Ghana-based minoHealth AI Labs, shows where the technology is proving genuinely useful and provides recommendations to overcome difficulties in tackling diseases.
4) Artificial Intelligence Could Have Helped Alleviate Suffering From Texas Blackouts (Forbes)
After dramatic winter storms battered the southern US and parts of Europe in February, we discussed the impact of technology use and the potential for machine learning to play a critical role in bringing efficiencies to Green House Gas-emitting industries. As this commentary discusses, AI has the potential to monitor the physical condition of the infrastructure that underpins the US power grid and to suggest predictive maintenance to prevent future disruptions.
5) Nothing Breaks Like A.I. Heart (The Pudding)
Explore few-shot learning with GPT-3 through this interactive love-story. Choose from rotating “mad-libs” and list selections to explore a fluid essay about artificial intelligence, emotional intelligence, and finding an ending. The interactive model combines Pamela Mishkin’s creative writing with both the open-ended GPT-3 model, using all 175B parameters to generate text, and a model fine-tuned on “instruction following” to guide the responses toward a logical plot line.
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