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MIT's Dough Boy

Trevor Ng is getting his Ph.D. in rheology at MIT's non-Newtonian fluid dynamics research group. What this means is that he plays with dough for a living:

His Ph.D. thesis concerns the mechanical properties of matter -- in this case, dough -- and how it behaves when subjected to forces. ...

Non-Newtonian fluids are unusual materials. Their viscosity, or slipperiness, changes with the amount of strain applied to them. Many non-Newtonian fluids have microscopic structures that affect how they react when poked or prodded, and how fast they move when they flow. Picture peanut butter or mayonnaise dripping from a tap -- they would not behave like water. Some non-Newtonian fluids such as polymers bounce like a ball if dropped but flow smoothly if placed on a surface.

[Ng's boss's] research group looks at DNA, saliva, tree sap and okra, a natural polymer used as a food thickener for thousands of years. Snail slime and such oddities as magnetic fluids also are investigated.

I would love to see the grant application for this one. More on Trevor's research here.

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New AI-Driven Music System Analyzes Tracks for Perfect Playlists
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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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