Last weekend, I visited St. Louis and got to catch up with some friends who live in an old brick house in that city's South Grand/Tower Grove neighborhood. (Which is awesome, by the way. After hearing nothing but bad news about St. Louis for years, I was pleasantly surprised by great, thriving neighborhoods like this one.)
There's a little porch off one of the upstairs windows, facing the street. But, at first, it's not entirely clear how you get out onto it. But, whoever built this old house had a clever trick up their sleeve — and it's one I'd never seen in action before. That's a picture of the closed window above.
MattAttackPro is a chemistry and physics teacher in South Carolina. This is what happened when he dropped a roll of unused camera film into a container of hydrochloric acid.
What you're seeing is the plastic backing separating from the "film" from which film takes its name—a coating of multiple layers of light-sensitive salts suspended in gelatin. Yes, film is like a jello salad. And it makes for a beautiful photograph.
Google has been testing out its self-driving cars on real roads. This is still a long way from being available for you to purchase, but it's clear that it's working surprisingly well on a technological level.
You can watch some footage, recorded in the driverless cars during their test runs, in the video above. IEEE Spectrum's Erico Guizzo (who, incidentally, says he's a lot less skeptical of Google's goals after seeing this video) explains what makes the system work.
Two things seem particularly interesting about Google's approach. First, it relies on very detailed maps of the roads and terrain, something that Urmson said is essential to determine accurately where the car is. Using GPS-based techniques alone, he said, the location could be off by several meters.
The second thing is that, before sending the self-driving car on a road test, Google engineers drive along the route one or more times to gather data about the environment. When it's the autonomous vehicle's turn to drive itself, it compares the data it is acquiring to the previously recorded data, an approach that is useful to differentiate pedestrians from stationary objects like poles and mailboxes.
The video above shows the results. At one point you can see the car stopping at an intersection. After the light turns green, the car starts a left turn, but there are pedestrians crossing. No problem: It yields to the pedestrians, and even to a guy who decides to cross at the last minute.