The Tricorder was the diagnostic tool of choice for the fictional Dr. Leonard McCoy — a small handheld device used to quickly and non-invasively assess the health of his crewmates aboard the Star Trek Enterprise. Since the sci-fi prop’s first cameo in the 1960s, a device that non-invasively measures important biomarkers in real-time has captured the imagination of health innovators. Now, thanks to breakthroughs in magnetic resonance and machine learning, the Tricorder is finally closer to reality.
In 2017, Ben Nashman founded Synex Medical with the vision of building wearable or hand-held devices that would tell a person, in real time, how their body is performing by measuring the metabolites that affect everything from weight gain to athletic performance to the likelihood of developing diabetes.
Glucose monitoring, one the most common monitoring use-cases, currently relies on an antiquated and barbaric approach involving regular pin pricks and test strips. The market for blood glucose strips alone was estimated at USD $4.5B in 2019 and is expected to grow to USD $6.6B by 2025. Even the next generation devices that were launched recently do not provide ongoing biomarker measurements. As Ben puts it, “It’s like driving a car without a speedometer or a fuel gauge.”
Synex’s combination of machine learning and novel magnetic resonance technology has opened the possibility of an entirely new category of applications to enable everyone to understand their bodies in real-time and proactively improve their health. Last week, Radical announced its investment in Synex’s seed round alongside Accomplice. Radical had also previously invested in Synex’s founding investment round.
We are proud to continue supporting Ben and the Synex team, who are boldly going where only science fiction has gone before.
4 AI and deep tech articles for the week of Nov 9, 2020
1. AI pioneer Geoff Hinton: “Deep learning is going to be able to do everything” (MIT Technology Review)
Geoffrey Hinton at MIT Technology Review’s annual EmTech MIT conference discusses recent deep learning breakthroughs and the opportunity that still exists for further advances in the field.
2. Artificial Intelligence Shows Potential to Gauge Voter Sentiment (Wall Street Journal)
As results in this US election veered from predictions from traditional political polling methods, technology experts say artificial intelligence could hold promise for better understanding the electorate.
3. Old dog training methods teach robots new tricks (World Economic Forum)
A team of researchers at Johns Hopkins University’s Computational Interaction and Robotics Laboratory have been teaching robots new skills by using techniques normally meant for training dogs. Using positive reinforcement, they were able to teach a robot to learn new things in days, instead of what typically takes a month.The team believes these findings could help train household robots as well as self-driving cars.
4. 2020 AI survey: Confidence in artificial intelligence expands as health industry leaders project faster return on investment (Healthcare IT News)
The third annual Optum Survey on AI in Health Care found that healthcare executives believe AI will deliver value for the industry faster than previously thought. 59% of respondents expect their organizations to see a full return on their AI investments in under three years. That’s up 90% since 2018, when only 31% of respondents expected to break even that quickly.
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