The (New) New Einsteins: Nathalie Cabrol

In the current issue of mental_floss magazine, Erik Vance profiled nine "New Einsteins"—visionaries who are discovering how to grow organs, peer into black holes, levitate food, cure plagues, and let blind men see. This week, Mr. Vance will be anointing five additional New Einsteins here on, one per day. Today, it's Nathalie Cabrol's turn.

Who She Is: Nathalie Cabrol, astrobiologist and principal investigator with the SETI Institute

What She Did: Cabrol's work covers a number of different aspects of the search for extra-terrestrial intelligence (often called SETI). First, she looks for life in one of the harshest environments on the planet, the Atacama Desert in Northern Chile. The idea is that understanding plants and animals in an environment that might go decades without rain (until 1971, some parts might have gone rainless since 1570) tells us something about what might survive on Mars. The Atacama Desert is so harsh that if the same Viking landers that couldn't find life on Mars in the mid-1970s were to land there, they would say the same thing about Earth.

A few years ago, she climbed the nearby volcano, Licancabur. At the 20,000-foot summit, she descended into the cauldron and dove into the crater lake. It was the unofficial record for the highest female dive. Yet even there, where temperatures get down to -30 degrees, she found tiny living organisms.

Recently she has been focused on helping the Mars rovers. She has helped run several experiments with one version (named Zo), where researchers follow it along and see if it can detect life in the desert.

Why You Should Start Idolizing Her Immediately:

Cabrol is an alien hunter who climbs desert mountains and SCUBA dives the world's highest lakes for a living. And she plays with robots. She's like a Michael Crichton book that met a Jerry Bruckheimer film and decided to guest star on an episode of The X-Files.

More than that, her work is actually a crucial link between theory and practice of SETI. For the brief time that Mars had a working atmosphere, water on its surface, and was moderately hospitable to life, it probably looked a lot like the Atacama Desert "“ heavy UV radiation, not much oxygen, kind of cold. Scientists who believe Mars has life must assume that something managed to form, evolve, and make the jump from water to land before the water dried up.

Science increasingly tells us this may be possible. On our own planet life exists at the bottom of the ocean, in boiling sulfur pits, and deep in the Earth's crust. And in the Atacama. It's not hard to imagine some of the microbes that she found at the top of Licancabur surviving under the surface of Mars "“ with a few adaptations. But we are going to have to find them, and that may harder than just digging a few scoops of slushy dirt looking for water. We will need to find the right place to land and know just what to look for. By doing ecological maps of Mars-on-Earth, Cabrol gives us a rough blueprint for what to look for when we see the real thing.

Previous (New) New Einsteins: Marin Soljačić , Roland Fryer


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New AI-Driven Music System Analyzes Tracks for Perfect Playlists

Whether you're planning a bachelorette party or recovering from a breakup, a well-curated playlist makes all the difference. If you don't have time to pick the perfect songs manually, services that use the AI-driven system Sonic Style may be able to figure out exactly what you have in mind based on your request.

According to Fast Company, Sonic Style is the new music-categorizing service from the media and entertainment data provider Gracenote. There are plenty of music algorithms out there already, but Sonic Style works a little differently. Rather than listing the entire discography of a certain artist under a single genre, the AI analyzes individual tracks. It considers factors like the artist's typical genre and the era the song was recorded in, as well as qualities it can only learn through listening, like tempo and mood. Based on nearly 450 descriptors, it creates a super-accurate "style profile" of the track that makes it easier for listeners to find it when searching for the perfect song to fit an occasion.

Playlists that use data from Sonic Style feel like they were made by a person with a deep knowledge of music rather than a machine. That's thanks to the system's advanced neural network. It also recognizes artists that don't fit neatly into one genre, or that have evolved into a completely different music style over their careers. Any service—including music-streaming platforms and voice-activated assistants—that uses Gracenote's data will be able to take advantage of the new technology.

With AI at your disposal, all you have to do as the listener is decide on a style of music. Here are some ideas to get you started if you want a playlist for productivity.

[h/t Fast Company]

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