Your public school education exists, in large part, thanks to the Second Industrial Revolution. When the revolution took hold of America in the 1870s, 30 years after the end of the first, half of the US population still spent their days toiling in fi...
Every attempt at cloaking devices thus far in our collective technological history has been either bollocks or an array of cameras and some kind of weird screen. The result was that objects kept their shape and displayed a background. Sure, it was less conspicuous than wearing a clown costume, but it’s not the true invisibility that we were all hoping for. Now here’s the big thing: this is, and it costs about $100 to make at home.
“From what we know this is the first cloaking device that provides three-dimensional, continuously multidirectional cloaking,” says University of Rochester grad student and researcher Joseph Choi. No, it can’t yet conceal your entire body, but the fact that an array of common lenses (and some virgin unicorn’s blood, I assume) can make an object just straight up disappear is amazing.
This could be very useful in a variety of fields, according to Choi: “I imagine this could be used to cloak a trailer on the back of a semi-truck so the driver can see directly behind him. It can be used for surgery, in the military, in interior design, art.”
As the director of a ballet company, I’m picturing a clever way to make some of the artform’s more ethereal characters (sylphs, willis, assorted visions and hallucinations) simply appear and disappear into thin air: it would be amazing.
We all know that customer reviews can be prone to, shall we say, a little positive engineering. What if you could gather genuine opinions about a restaurant, or product before you commit your cash? Well, a new system developed at the University of Rochester might be able to offer just that. The "nEmesis" engine uses machine learning, and starts to listen when a user tweets from a geotagged location that matches a restaurant. It then follows the user's tweets for 72 hours, and captures any information about them feeling ill. While the system isn't able to determine that any resulting affliction is directly connected to their restaurant visit, results over a four-month period (a total of 3.8-million analysed tweets) in New York City found 480 reports of food poisoning. It's claimed these data match "fairly well" with that gathered by the local health department. The system's creators admit it's not the whole picture, but could be used alongside other datasets to spot potential problems more quickly. The only question is how long before we see "sabotage" tweets?
Your public school education exists, in large part, thanks to the Second Industrial Revolution. When the revolution took hold of America in the 1870s, 30 years after the end of the first, half of the US population still spent their days toiling in fi...
