After that somewhat misleading Golden Scholars story about Chip Kelly, we have a Golden Scholars story about Chip Kelly! Turns out he likes consulting with Berkeley's H. Edwards for advice. Not that H. Edwards, but professor emeritus Harry Edwards for his knowledge on race relations.
Emeritus professor of economics Lloyd Ulman, who specialized in labor, passed away at the age of 94. Our condolences to his friends and family.
Student takes safety into his own hands
A Berkeley undergrad has decided to personally do all that he can to help keep his fellow students safe shy of exposing himself to lab dangers and running around campus at night as a costumed vigilante (wearing blue and gold, of course).
Sawhil Chinoy compiled data about the frequency of crimes in sectors of the Berkeley campus over the past four years and applied them to a map as a rudimentary guide of which parts of campus may be too dangerous to brave late at night
after some hot bangerations after a great study session as all students do.
He based his research on UC crime reports and did most of the work on his own time last winter; once he was finished he posted his findings on Facebook.
"I was thinking if you could mine this data somehow and draw insights that might actually be relevant to students, and helping students stay safer and avoid certain areas when there is a lot of crime that would be really cool," said Chinoy.
The UC Berkeley police department saw Chinoy's work, and has provided a link to it from the department's Twitter feed.
So, what part of the Berkeley campus did Chinoy determine to be the most shady (not counting those bathrooms down in Dwinelle)?
The study found the most unsafe areas were the Grinnel Path where students often walk from the Berkeley BART Station, sections near Telegraph Avenue and People's Park.
The study also found that most crimes occurred on Thursdays and as for what time of day, they typically occurred from 9 p.m. to midnight.
But, like any hero, Chinoy's work isn't finished just yet. Chinoy is looking to execute an app that, in real time, will advise the user for the safest path from A to B. Let's just hope the users aren't too distracted by staring into their phones for that app to pay attention to what's going on around them.
Check out Chinoy's data and interactive map at BerkeleyCrime.org.
"010010110 010010110 010010110" means "zoom zoom zoom"
Let's be frank—driving is cool, but driving sucks. The (rush-hour) traffic, the stress, the idiots, the lost time, the idiots, the idiots, and the idiots are always out there and it's maddening. So, wouldn't it be awesome to have a car that drove itself? On the way to school/work you can finish up your homework/slides for lab meeting. You can spend all night having small, one-gulp drinks of highly concentrated alcohol (repeat a few more times excitedly) without worrying about a designated driver (or driving drunk). It's pro, pro, pro, yes?
Apparently self-driving cars have been a thing for longer than we'd expect; Steven Shladover is the program manager at UC Berkeley's Partners for Advanced Transport Technology (PATH) and working with this technology for over 40 years and is actually less enthused. Shladover sees a number of obstacles and isn't so sure that autonomous cars can hurdle them. Of course they can't hurdle them. They're cars. Cars don't hurdle. Cars drive. They could drive through the hurdles. I mean, I guess if you set up little ramps before each hurdle than they could soar above them.
The first problem Shladover discusses is the difficulty in taking in a world of information around you and processing it to maneuver safely. To be frank, I are too dummy to understand how automated cars do that, but if self-driving cars have been successfully tested without causing accidents, then doesn't that mean they are doing this successfully?
Perhaps the stickiest challenges are moral hazards. Shladover offers this example: An automated vehicle is forced to take action in an emergency. If it goes one direction, it hits and kills a motorcyclist. If it goes the other, it collides with a semi, killing its own occupants. Programmers will have to confront such dilemmas.
Again, I'm no programming expert, but I don't think you would code in the dilemma framed in this way. I don't think you code in:
if (damage motorcycle) or (damage self), then...
So, what does Shladover see for the future of autonomous cars?
Shladover believes that an important step toward realizing the self-driving dream is vehicle-to-vehicle communication, an area PATH has researched extensively. His team is currently developing cooperative adaptive cruise control (CACC) systems that allow vehicles to travel in a tightly packed, wirelessly networked group. CACC-equipped vehicles can relay precise information about location, acceleration, deceleration, and emergencies. Without these cooperative abilities, Shladover says, automated vehicles are deaf and mute.
So when can we expect to turn driving over to the robots? At lectures, Shladover tells audiences that it may not happen within their lifetimes.
So, we can all look forward to more interactions with idiots who don't understand the weaving principle of merging and can't bother their pretty little hand to use a turn signal.