The stand-off between the FBI and Apple over a terrorist’s locked iPhone is on pause; the intelligence agency has apparently found someone capable of hacking into the mobile device without a court order. But this whole kerfluffle could have been over a lot sooner, if the FBI had just called up Johns Hopkins.
In the course of daily life, most of us go up and down dozens of stairs every day. And usually, we don’t think much of it. But thanks to a transformation by undergrads in the Johns Hopkins Robotics Club, a staircase in one of the university’s academic buildings is now a whole different kind of experience.
This is amazing: So, like many professors, Johns Hopkins computer scientist Peter Frohlich grades exams on a curve, meaning that everyone’s grades are relative to the top scorer. (If the smartest student gets an 85, s/he gets an A, and everyone else’s score is weighted accordingly.) There’s an obvious loophole, though — if everyone taking the exam gets the same score, then everyone gets an A. Even better, if everyone gets a zero, they get an A. This is exactly what Frohlich’s students did — and it worked.
In lists of college majors with the highest starting salaries, engineering always dominates; according to Forbes, the only non-engineering major in the top-five top-earning list is computer science. Which makes it all the more worrisome that women make up a measly 12 percent of CS majors — down significantly from the 1980s, when women made up more than a third of CS grads.
The next time you hear someone talk about debugging a computer program, think of Grace Hopper, the U.S. Naval officer and pioneering computer scientist who once removed an actual bug (okay, a moth) from a glitchy machine. Hopper is also known for being one of the first software engineers, inventing the compiler, and generally being a bad-ass lady computer scientist when that world was very much closed off to women. And although things have changed, the computing world is still overwhelmingly male. Which is why it’s extra-exciting (and important!) that Baltimore plays host to the international Grace Hopper Celebration of Women in Computing this week.
By day, Avi Rubin is a computer security consultant and a professor of computer science at Johns Hopkins’ Whiting School of Engineering. But by night — and on the weekends, and whenever his wife doesn’t mind too much — Rubin is a poker aficionado, one of those real obsessives with his sights set on the World Series of Poker in Las Vegas. And with a talent for numbers and an obsessive focus on probabilities, he just might end up making it there.
Rubin sees the game in terms of his academic interests — game theory, machine learning, combinatorics. A true computer scientist at heart, he envisioned a poker hand as a finite, countable structure. Once the first cards are dealt (in Texas Hold-Em, each player is dealt two cards face down; five communal cards are dealt faceup), the rest of the game unfolds like a kind of decision tree. Rubin crafted a program to determine the relative probabilities of success given particular variables — his position in the betting, number of opponents, etc. “For any given spot in the decision tree,” he told Johns Hopkins Magazine, “I could come up with a probability distribution of different plays. Then I could write a learning program that I could use as a simulator on the computer and play a thousand times with particular settings, then tweak the settings and run it again to see if I do better, and work backward from it to infer why that was a better play in that situation.”
But because computers can’t yet model the full complexity of playing with real human beings, who bluff/get bored/try to show off/otherwise behave unpredictably, Rubin sat in on weekly games with friends, many of whom were doctors and lawyers. “The lawyers tend to be better,” he says. “The math in poker is basic arithmetic, it’s not that hard. But you still have people, like a lot of the doctors that I play with, who’d rather not bother with all the math. They feel that they have enough intuition for the game.” But that intuitive technique tends to backfire, in Rubin’s experience: “The fundamental math is much more important. If you’re a solid mathematical player, in the long run you’re going to kill the intuitive player.”