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Your DNA is in a database.

Your genetic code is probably already in a database, without you ever giving a sample or permission. This video is sponsored by Brilliant. The first 200 people to sign up via https://brilliant.org/veritasium get 20% off a yearly subscription.

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A huge thanks to Paul Holes, Billy Jensen, Brett Williams, Dr Connie Bormans and Dr Doc Edge for being part of this video. Thanks to Verogen and Family Tree DNA for giving me access to film.

Thanks to Sonya Pemberton, Joe Hanson, Raquel Nuno, CGP Grey, and numerous Patreon supporters for helpful feedback on an earlier version of this video.

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Continue reading “Catching Criminals With Their Relative’s DNA” | >

Sickle-cell disease is incurable and affects 15,000 people in the UK.

And the National Institute for Health and Care Excellence said the hope of reducing health inequalities for black people, who are predominantly affected and often have poorer health to start with, made the drug worth recommending.

It called it “an innovative treatment”.

The hope of reducing health inequalities for black people made it worth recommending, the regulator says.

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Humans find AI to be a frustrating teammate when playing a cooperative game together, posing challenges for “teaming intelligence,” study shows.

When it comes to games such as chess or Go, artificial intelligence (AI) programs have far surpassed the best players in the world. These “superhuman” AIs are unmatched competitors, but perhaps harder than competing against humans is collaborating with them. Can the same technology get along with people?

In a new study, MIT Lincoln Laboratory researchers sought to find out how well humans could play the cooperative card game Hanabi with an advanced AI model trained to excel at playing with teammates it has never met before. In single-blind experiments, participants played two series of the game: one with the AI agent as their teammate, and the other with a rule-based agent, a bot manually programmed to play in a predefined way.

The results surprised the researchers. Not only were the scores no better with the AI teammate than with the rule-based agent, but humans consistently hated playing with their AI teammate. They found it to be unpredictable, unreliable, and untrustworthy, and felt negatively even when the team scored well. A paper detailing this study has been accepted to the 2021 Conference on Neural Information Processing Systems (NeurIPS).

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Trust is a very important aspect of human-robot interactions, as it could play a crucial role in the widespread implementation of robots in real-world settings. Nonetheless, trust is a considerably complex construct that can depend on psychological and environmental factors.

Understanding a robot’s decision-making processes and why it performs specific behaviors is not always easy. The ability to talk to itself while completing a given task could thus make a robot more transparent, allowing its users to understand the different processes, considerations and calculations that lead to specific conclusions.

Full Story:

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This robotic arm fuses data from a camera and antenna to locate and retrieve items, even if they are buried under a pile.

Source:

A busy commuter is ready to walk out the door, only to realize they’ve misplaced their keys and must search through piles of stuff to find them. Rapidly sifting through clutter, they wish they could figure out which pile was hiding the keys.

Researchers at MIT have created a robotic system that can do just that. The system, RFusion, is a robotic arm with a camera and radio frequency (RF) antenna attached to its gripper. It fuses signals from the antenna with visual input from the camera to locate and retrieve an item, even if the item is buried under a pile and completely out of view.

The RFusion prototype the researchers developed relies on RFID tags, which are cheap, battery-less tags that can be stuck to an item and reflect signals sent by an antenna. Because RF signals can travel through most surfaces (like the mound of dirty laundry that may be obscuring the keys), RFusion is able to locate a tagged item within a pile.

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GraphWear, a company pursuing needle-free approaches to glucose monitoring, has closed a $20.5 million Series B round. This Series B round is a vote of confidence by investors in GraphWear’s approach: to monitor key metrics in the body, like glucose, without breaking the skin at all.

GraphWear Technologies was founded in 2015 by Rajatesh Gudibande and Saurabh Radhakrishnan, who had both completed master’s degrees in nanotechnology at the University of Pennsylvania. Specifically, GraphWear is developing a skin-surface-level wearable made of graphene (more on this material later). The sensor is small, about the size of an Apple Watch — but the key piece of technology is actually housed on the bottom. It’s a thin slice of graphene that fits onto the back of the watch, or onto a sticker that can be worn on the abdomen.

This Series B round, says Gudibande, will be focused on helping the company build upon previous validation studies of the wearable, completing a pivotal trial and submitting for FDA clearance. The round was led by Mayfield, with participation from MissionBio Capital, Builders VC and VSC Ventures.

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Desalination is the answer to long-term water security, but it’s also expensive and energy-intensive. The good news is that scientists are developing some viable solutions.

The first plant in Europe was built in Spain nearly a half century ago. Since then, facilities have sprung up in water-stressed regions throughout Europe. Just a few years ago, the residents of the small Greek island of Ikaria finally got access to an abundant source of clean drinking water—all thanks to a new desalination plant.

The growing importance of desalinising water is undeniable. Once only an issue in Southern Europe, countries in the north like the Netherlands and Belgium are now also investing in desalination technology.

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