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1) Investing in AI: What investment trends reveal about the global AI landscape (Brookings)

“The world’s AI landscape is changing fast, and a plethora of unpredictable geopolitical factors, from U.S.-China “decoupling” to COVID-related disruptions, counsel against confident claims about where the global AI landscape is headed next…AI is a global wave, not a bipolar contest. The data are clear: AI is booming around the world, not just in the United States and China.”

Radical Commentary: This week, Brookings released its analysis on global AI investments across the globe, focusing on private markets. The analysis found that the global AI industry is booming, with the private sector driving progress in AI technologies. US-based AI companies attracted nearly two-thirds of total global investment. Canadian-based AI companies attracted about $900M USD in disclosed investment in 2019, ranking fifth globally on investment value and third on investment value growth over the past five years.

The analysis also found that US governments are reducing internal technology development and are now more reliant on private AI companies, but that those companies focus less on areas of interest to governments such as infrastructure and security. As this trend progresses, policymakers may need to consider different strategies to incentivize private companies to develop AI in these areas of public interest.

2) AI Diagnosis Using Voice: Alexa, do I have COVID-19? (Nature)

“Researchers are now working to identify speech-based biomarkers for other kinds of neurodegenerative disease. For instance, a trio of scientists in Toronto, Canada, used voice samples and transcripts from more than 250 people to identify dozens of differences between the speech of people with possible or probable Alzheimer’s disease and that of people without it.”

Radical Commentary: Voice-analysis start-ups are racing to determine biomarkers for COVID-19. This may increase the value of recording patients who are COVID-19 positive, although much of the research is limited to analyzing recordings of those who are symptomatic, particularly focusing on cough data.

Using voice for diagnosis remains a nascent science as large, longitudinal trials are required to demonstrate if such analysis can actually detect disease earlier than standard diagnostic methods. However, there is already significant activity in the diagnostic space relating to cognitive health. For example, AI developed by Professor Frank Rudzicz of the Vector Institute for AI and University of Toronto (referred to in the quote above) can now discern Alzheimer’s with 92% accuracy.

With the prevalence of voice assistants in homes and healthcare facilities, the volume of training data for AI is increasing at an enormous pace. Whether the voice assistant platforms controlled by big tech companies will open themselves broadly to outside researchers and companies building voice diagnostic tools remains a question. If so then this research space will gain momentum. Either way, we expect AI trained on voice data will ultimately become part of the standard of care in supporting diagnosis of cognitive function and impairment.

3) 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: PwC and CB Insights released a report that underscores the strength of Canada’s digital health ecosystem and reflects a wave of innovation we anticipated in Radical’s health thesis. The report notes that so far this year Canadian-based digital health startups have raised more than $300M USD, roughly double the amount raised in all of 2019. PwC and CB Insights also published a market map of 51 VC-backed digital health companies in the country. Five of Radical’s portfolio companies are featured: Aspect Biosystems and PocketHealth are portfolio companies in Radical’s second fund; and BenchSci, Medchart, and Phenomic are investments in Radical’s first fund.

Canada has a unique advantage as digital healthcare evolves to become more focused on AI: a high concentration of AI and healthcare researchers, an incredibly diverse population, and a data-rich single-payer health system. Importantly, we are now starting to see government and VC investments plus large donations to build upon these opportunities. As discussed in last week’s Radical Reads, the University of Toronto Faculty of Medicine announced a $250 million donation, which includes a focus on AI for healthcare. We expect to see significant acceleration of digital and ultimately AI adoption across the healthcare space in Canada and around the world.

4) AI in Space: AI is Helping Scientists Discover Fresh Craters on Mars (NASA Jet Propulsion Laboratory)

“Sometime between March 2010 and May 2012, a meteor streaked across the Martian sky and broke into pieces, slamming into the planet’s surface. The resulting craters were relatively small — just 13 feet (4 meters) in diameter. The smaller the features, the more difficult they are to spot using Mars orbiters. But in this case — and for the first time — scientists spotted them with a little extra help: artificial intelligence (AI).”

Radical Commentary: This is the first time AI has been used to find unknown craters on Mars — a milestone for planetary scientists and AI researchers at NASA. Typically, researchers spend hours each day studying images captured by NASA’s Mars Reconnaissance Orbiter (MRO) looking for changes in the surface. To save time, researchers created an AI tool called a crater classifier. To train the crater classifier, researchers fed thousands of images of Mars’ surface with craters and without. The AI tool identifies unknown craters in five seconds — a task that takes a trained researcher 40 minutes to accomplish.

While this crater classifier runs on computers on Earth, NASA says the ultimate goal is to develop similar classifiers that would be used by future Mars orbiters. The use of AI in spotting craters will save researchers time and increase the volume of insights on the topography of the red planet.

5) AI at Home: These Robots Use AI to Learn How to Clean Your House (Wired)

“Inside an ordinary-looking home, a robot suspended from the ceiling slowly expands arms holding a sponge, before carefully wiping a kitchen surface clean. Nearby, another robot gently cleans a flat-screen television, causing it to wobble slightly.

The cleaning robots live inside a mock home located at the Toyota Research Institute in Los Altos, California. The institute’s researchers are testing a range of robot technologies designed to help finally realize the dream of a home robot.”

Radical commentary: While Toyota does not have a timeline for commercializing its prototypes, it could be an early entrant in a potentially big market. As cities around the world, including in North America, begin thinking about how to care for an aging population, robots running AI software could help clean homes, tend to people who need physical help, and even keep them company.

Having a robot perform useful tasks around our homes is still a challenge because every physical space is different and requires custom adaptation. For home robots to become ubiquitous there will need to be advances in AI enabling robots to learn and adapt. Currently robots are mostly used in industries and are typically only capable of executing repetitive tasks. But this is starting to change. Covariant, a Radical portfolio company, is deploying AI robotics software that enables quick learning and adaptation of industrial robots. As this technology develops, we expect to see ‘thinking’ robots supporting human needs across industries and at home.

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Editor’s Note: We will continue to use this platform to share without commentary articles focused on data and the use of it to illustrate and illuminate racial injustice. Because you cannot fix problems you cannot see or understand.

6) Closing the Racial Inequality Gaps (Citi Global Perspective and Solutions)

“The analysis in the accompanying report shows if four key racial gaps for Blacks — wages, education, housing, and investment — were closed 20 years ago, $16 trillion could have been added to the U.S. economy. And if the gaps are closed today, $5 trillion can be added to U.S. GDP over the next five years.

These gaps exist based on systemic issues that caused and continue to cause discrimination against Blacks over the years. The gaps in many cases remain wide 60 years after the Civil Rights Movement. In some cases, including in homeownership rates and college degree attainment, the gaps are wider now than in the 1950’s and 1960’s. For each of the gaps faced by Blacks, we identify the degree of the gap between Blacks and whites in wages, labor segmentation, education, wealth, housing and investment and identify the impact closing each gap would have on the U.S. economy. Finally, we outline how we believe governments, corporations, and individuals can work together to eliminate these gaps for good.”