Although these three speakers travel in quite disparate worlds -- natural language processing, mechanics of tiny organisms, and violent cosmic events -- they convey a comparably infectious enthusiasm for their research.

In the early days of artificial intelligence, “people had the naïve idea that if you took a computer, and fed it with enough human knowledge, it could eventually understand human language,” relates Regina Barzilay. In the 1990s, after this “spectacular failure” in methodology, a new approach evolved: training a machine to infer knowledge from piles of data. Some successes are already in evidence (IBM’s chess- and Jeopardy-playing programs). Barzilay wants to move this learning further, toward “grounding interpretation of language in the real world.” She describes algorithms that could take over the often exasperating grunt work of installing new Windows software on computers, by reading common instructions and executing the actions. Her system learns to map words with increasing accuracy by using feedback. She is also investigating how to get a machine to understand and act in a much more complex environment, such as the Civilization computer game. Using simulations, her algorithms make predictions about the best possible

moves (e.g., invade another nation), and can even absorb instructions from the game’s manual, which should make the system “good enough to play against humans.” Her ultimate goal: “enabling computers to function competently in a world rich in unstructured information.”

For tiny organisms in a fluid environment, a key challenges is viscosity, says Anette Hosoi . In particular, Hosoi focuses on eukaryotic cells with spherical heads attacked to flexible tails. Remarkably, the diameters of these tails are the same across all species -- between 250-400 nanometers. Whether a hair in a lung, or a cell in green algae, these tails are all made of microtubule structures that can slide and bend in similar ways. By analyzing these common properties, Hosoi can predict optimal morphology and kinematics of comparable tailed microorganisms. For instance, analyzing sperm cells, Hosoi’s team determined that the best ratio of tail to head for swimming efficiency is 12 – and not just for sperm. “I don’t care what the species is, what it’s made out of, the tail should be 12 times as long as the head…Getting something as clean as that is very exciting!” One outlier in the study: the Bandicoot, whose sperm’s fat tail did not share the same radius as all the others. This kind of optimization research, says Hosoi, can only improve, as the computational costs of analyzing vast repositories of biological data continue to drop. When you begin to understand underlying principles in biological structures, she says, “you can move on to inform engineering designs.”

Nergis Mavalvala takes her audience “to a slightly uncomfortable side of the universe, warped and violent.” She searches the cosmos using “a completely new messenger -- gravitational waves that travel to us from distant sources.” Mavalvala credits Einstein (by way of Newton) for first proposing these waves. He developed a picture of space and time “as a fabric” that can be dented by massive objects, exerting a gravitational pull. Massive objects bouncing around or vibrating caused “ripples of space time itself” -- hence gravitational waves. To produce these waves, says Mavalvala, you need lots of mass and rapid acceleration, explosions and collisions – produced by compact stars slamming together, merging black holes, and the conditions that immediately followed the Big Bang. Using special detectors (laser interferometers), Mavalvala has been trying to detect gravitational waves. The first measurements taken by these detectors found a gamma ray burst explosion, but no gravitational waves. A next-generation detector is on the way that makes it possible to “listen to more distant sounds,” but Mavalvala notes that at this level of “exquisite measurement,” you pay the price of “quantum uncertainty.” However, she is certain the elusive gravitational wave will finally be captured, and “we will be testing general relativity: the first direct observation of ripples of space-time.”...Read the full article/Watch Video