Last year, we took a look at Fove, a unique take on virtual reality that tracks your eyes in addition to your head for increased accuracy and realism. This doesn't just reduce head movement -- it also reduces the likelihood of VR sickness and introduces a whole new style of gameplay where you can simply look at certain objects to trigger an action. Back then, Fove was just a Kickstarter project, but now it's ready for the masses. Units will finally start shipping to Kickstarter backers next month, and it's also now available for pre-order on Fove's website. It'll retail for $599 but those who pre-order between now and November 9th can get it for $549.

Virtual reality is on the cusp of becoming mainstream, but one startup in Japan is betting the technology won't really succeed unless it cracks a critical piece of the puzzle: human eyeballs. Fove Inc. is introducing the world's first commercially available VR goggles equipped with tiny infrared cameras to follow eye movements. By tracking human irises, the gadget aims to reduce motion sickness, improve graphics performance and enhance social experiences by making virtual eye-contact possible, says Yuka Kojima, Fove's founder and chief executive officer. "We want to be the company that figures out VR's unsolved problems," Kojima said. "The immediate goal for now is to get as many headsets into the hands of developers as possible."

San Francisco-based startup Fove has developed eye-tracking for virtual reality -- that kernel of technology many feel is key for the illusion of becoming immersed in a setting. Or use a death stare to shoot down virtual spaceships. Watch a movie of a forest or a room and be able to look around wherever you want. "It allows you to go inside the world that's behind the display," said Yuka Kojima, Fove's co-founder and a rare female chief executive in male-dominated Japan Inc. Fove, which comes from "fovea," the part of the eye with the sharpest vision, from "field of view," and the word's similarity with "love," has devised a way to use tiny infrared sensors inside headset goggles to monitor the movements of a wearer's pupils. It's a small company, founded in 2014, with offices in Tokyo, San Francisco and Los Angeles, and employing just 17 people.

Many representation schemes combining first-order logic and probability have been proposed in recent years. Progress in unifying logical and probabilistic inference has been slower. Existing methods are mainly variants of lifted variable elimination and belief propagation, neither of which take logical structure into account. We propose the first method that has the full power of both graphical model inference and first-order theorem proving (in finite domains with Herbrand interpretations). We first define probabilistic theorem proving, their generalization, as the problem of computing the probability of a logical formula given the probabilities or weights of a set of formulas. We then show how this can be reduced to the problem of lifted weighted model counting, and develop an efficient algorithm for the latter. We prove the correctness of this algorithm, investigate its properties, and show how it generalizes previous approaches. Experiments show that it greatly outperforms lifted variable elimination when logical structure is present. Finally, we propose an algorithm for approximate probabilistic theorem proving, and show that it can greatly outperform lifted belief propagation.