Radical Reads: 2020’s top AI stories

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Radical Talks 2020

The holidays offer a perfect time to catch up on thoughtful insights from some of the greatest minds in technology and AI. This year we launched our podcast Radical Talks exploring the intersection of technology, the economy, politics and culture. We had the opportunity to speak to global thought leaders on the future of healthcare, the latest on robotics, and the role artificial intelligence is playing in reshaping the economy.

We’re sharing highlights below. Be sure to tune in to Radical Talks in 2021 for more great conversations. Subscribe to Radical Talks wherever you listen to podcasts.

1. Re-Imagining the Economy with Eric Schmidt: A conversation with former Google and Alphabet CEO and Chairman, Eric Schmidt. We discuss the macro impacts of the pandemic, China relations, Sidewalk Labs and how technology and society might look very different coming out the other side of this crisis. Eric Schmidt is an investor in Radical Ventures.

2. Artificial Intelligence and the Future of Healthcare with Dr Eric Topol: Dr. Eric Topol, founder and director of the Scripps Research Translational Institute, discusses the latest challenges in combating COVID-19, and how artificial intelligence is the future of healthcare — the key to better health and more compassionate care. His latest book is Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again.

3. Making Robots Smart with Pieter Abbeel: A feature interview with Pieter Abbeel, the world’s leading expert on AI and robotics, on COVID19’s impact on automation and how AI has revolutionized the field of robotics. Pieter is the director of the Robot Learning Lab at University of California, Berkeley and co-founder of Covariant, a company that has built a universal ‘AI brain’ software platform for robotics. Radical Ventures is an investor in Covariant.

Top AI Stories of 2020

From tracking the outbreak of a global pandemic to breakthroughs in drug discovery, there was no shortage of AI headlines in 2020. We are sharing five of the most-read AI stories in Radical Reads during 2020.

1) AI Early-Warning of Coronavirus: An AI Epidemiologist Sent the First Warnings of the Wuhan Virus (Wired)

“On January 9, the World Health Organization notified the public of a flu-like outbreak in China: a cluster of pneumonia cases had been reported in Wuhan, possibly from vendors’ exposure to live animals at the Huanan Seafood Market. The US Centers for Disease Control and Prevention had gotten the word out a few days earlier, on January 6. But a Canadian health monitoring platform had beaten them both to the punch, sending word of the outbreak to its customers on December 31.

BlueDot uses an AI-driven algorithm that scours foreign-language news reports, animal and plant disease networks, and official proclamations to give its clients advance warning to avoid danger zones like Wuhan.”

Radical Commentary: Weeks before COVID-19 hit the World Health Organization’s radar, an AI system positively identified the early warning signs of what would soon become a global pandemic. Toronto-based BlueDot has been at the forefront of using machine intelligence to help identify and manage outbreaks of disease. AI early-warning systems will likely become a critical component of infectious disease management for healthcare systems, governments, insurers, and businesses. This year, we saw similar applications of AI to help spot wildfires in California and provide flood warnings in India and Bangladesh. AI-powered early warning systems have the power to help economies, protect property, and save lives.

2) Digital Health Disruption: The Digital Disruptors Changing Health in Canada (PwC)

“COVID-19 has changed the way care is being delivered in Canada. The pandemic has put immense pressure on those in our health care system to adopt new ways of working, and we’ve seen new levels of collaboration between the private and public sectors as they’ve come together to protect the wellbeing and safety of citizens.

Digital health, defined as the use of technologies to drive improvements in the design of medical products and the delivery of health care services, is powering much of this collaboration and innovation. As the pandemic continues to put pressure on health systems in the months to come, we expect this trend to continue to accelerate.”

Radical Commentary: This report by PwC and CB Insights underscored the strength of Canada’s digital health ecosystem this year and reflected a wave of innovation we anticipated in Radical’s health thesis. A notable trend in 2020 was a compressed time frame for technology adoption within the sector. For example, in the first months of the pandemic, Toronto startup and Radical portfolio company, PocketHealth (a medical image access and sharing software platform for patients, doctors and hospitals) saw an immediate 300% spike in demand.

As new norms and expectations of our healthcare system have been established this past year, it seems unlikely that patients, providers, and pharma will retreat to the past. The most disruptive health crisis in recent history created the optimal conditions for a revolution in how we use technology to care for one another.

3) AI Language Models: OpenAI’s new language generator GPT-3 is shockingly good—and completely mindless (MIT Technology Review)

“Exactly what’s going on inside GPT-3 isn’t clear. But what it seems to be good at is synthesizing text it has found elsewhere on the internet, making it a kind of vast, eclectic scrapbook created from millions and millions of snippets of text that it then glues together in weird and wonderful ways on demand.”

Radical Commentary: In June 2020, OpenAI announced GPT-3, a 175 billion parameter language model. It was the largest AI language model ever created, trained on trillions of words from the Internet. The purpose of the model is to provide natural sounding answers to questions, to translate between languages, and to coherently generate improvised text.

Effective natural language processing (NLP) models offer the potential to create entirely new products and new markets. In one example, a developer used the GPT-3 model to generate code for a website layout based on a natural language query. Some, including Elon Musk (a founder of OpenAI), have cited the work as evidence that Artificial General Intelligence — or at least AI that is smarter than humans — is on the near term horizon.

There are still many elements of GPT-3’s model that require fine-tuning. For instance, some developers have found that there are biases generated by the model, and in other cases, the model lacks common sense and struggles with simple math questions.

Still, advances in NLP hold enormous promise. Language is the primary information interface between humans and, as a consequence, nearly all information constructed and communicated is via language. Models that can thoughtfully and effectively leverage this will have a profound impact. Radical has made an investment in an NLP company currently in stealth, and we will be sharing our overview of the space in 2021.

4) AI Talent: With a big vision, Toronto founders can attract AI talent from Silicon Valley (Vector Institute and Radical Ventures)

“With nearly 15,000 tech companies, the Toronto-Waterloo corridor is the second largest technology cluster on the continent, boasting a high concentration of AI startups. Venture capital interest in Canadian AI companies is growing, with $658 million invested in 2019, up from $289 million two years prior, the majority of which was invested in Toronto and Montreal-based companies. The last three years have also seen a flood of investment from large organizations, with over 45 corporate AI labs opening or expanding in the region. Ambition, expertise, and energy permeate the corridor. For engineers interested in moving to a city with a flourishing community of high-performing peers and interesting projects, Toronto is a prime destination.”

Radical Commentary: It was only a few years ago that Toronto confronted major concerns of a “brain drain” as top engineering students graduating Canadian universities were leaving for Valley-based tech jobs. However, this has quickly changed. According to CBRE’s 2020 Tech Talent report, Toronto is now the 4th ranked city overall in North America behind the Bay Area, Washington DC and Seattle. Toronto came in 2nd on the list for the top “brain gain” score and came in 3rd with the highest concentration of tech talent with approximately 250,000 tech workers and growing.

While it is clear that Toronto’s tech ecosystem has seen very significant growth and is now a top choice for highly-skilled foreign nationals over other tech hubs in the US, founders still struggle to hire top AI talent. Although COVID increased movement in the market, the competition to recruit top tier tech talent remains fierce. Large technology companies continue to grow their ranks of engineers while also expanding their research footprint. Meanwhile, recruiting in the startup space is equally competitive as companies receive more capital and market traction. In order to offer some advice to founders looking for their next great hire, Radical collaborated with our friends at the Vector Institute to offer five tactical tips for startups to help them win over AI talent.

5) AI & Biology: ‘It will change everything’: DeepMind’s AI makes gigantic leap in solving protein structures (Nature)

“Figuring out what shapes proteins fold into is known as the “protein folding problem”, and has stood as a grand challenge in biology for the past 50 years. In a major scientific advance, the latest version of our AI system AlphaFold has been recognised as a solution to this grand challenge by the organisers of the biennial Critical Assessment of protein Structure Prediction (CASP). This breakthrough demonstrates the impact AI can have on scientific discovery and its potential to dramatically accelerate progress in some of the most fundamental fields that explain and shape our world.”

Radical Commentary: Artificial intelligence is rapidly gaining widespread use in biology, enabling new ways to understand biological data that will lead to radical innovations for decades to come. DeepMind’s announcement of a breakthrough in solving the protein folding problem was one of many developments in the industrialization of biotechnology this year.

The AlphaFold development holds significant promise for the design of protein therapeutics and, while these results are potentially groundbreaking, the impact is more likely to be seen in the medium to long term as the methods used in AlphaFold are adapted for use by multidisciplinary teams and finely tuned wet lab processes. The development of any advanced material, including protein or small molecule therapeutics, requires a close link between the material development process and the end product.

Our belief in the importance of a multidisciplinary approach to creating and capturing the benefits of computational biology is what led to Radical’s investment in Genesis Therapeutics. Genesis is at the forefront of applying AI to the field of drug discovery, using novel graph neural networks for molecular property prediction.

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