Autonomous cars are a chance to reinvent the steering wheel. Because the vehicles themselves do all the driving, cars are no longer bound by such basic conventions as "keep a human facing forward at all times" and "don't try to climb over boulders like a spider." As a grand showcase for the new possibilities of autonomous cars, Honda plotted a seven-stage road trip roughly following that path of humanity's great migration from a species to the edge of the world. The auto company used miniature models for this conceptual video, but the hope is the same principles could be applied to human-sized autonomous vehicles of the future. Honda's route goes from Nairobi, Kenya to Manaus, Brazil, and new vehicles trace individual legs of that journey.

We present a theoretical analysis and empirical evaluations of a novel set of techniques for computational cost reduction of classifiers that are based on learned transform and soft-threshold. By modifying optimization procedures for dictionary and classifier training, as well as the resulting dictionary entries, our techniques allow to reduce the bit precision and to replace each floating-point multiplication by a single integer bit shift. We also show how the optimization algorithms in some dictionary training methods can be modified to penalize higher-energy dictionaries. We applied our techniques with the classifier Learning Algorithm for Soft-Thresholding, testing on the datasets used in its original paper. Our results indicate it is feasible to use solely sums and bit shifts of integers to classify at test time with a limited reduction of the classification accuracy. These low power operations are a valuable trade off in FPGA implementations as they increase the classification throughput while decrease both energy consumption and manufacturing cost.

The summer school occurs at the first two weeks of the Third Frederick Jelinek Memorial Summer Workshop. The North American Chapter of the Association for Computational Linguistics (NAACL) is again offering an exciting summer school opportunity for a limited number of undergraduate students interested in the field of Human Language Technology. The 2016 Jelinek Summer Workshop will be held from Monday, June 13 to Friday, August 5, 2016 at the Johns Hopkins University in Baltimore, Maryland. The first two weeks of the workshop (from June 13 to 24) is a summer school that provides general introductions to the major areas of study within the field of Human Language Technology (e.g., Natural Language Processing, Automatic Speech Recognition, Machine Translation, Information Retrieval) as well as sessions on specialized research topics of current interest in the field. The NAACL scholarship is used to support undergraduate students to participate in the two-week summer school.

Visualization of high-dimensional data, such as text documents, is useful to map out the similarities among various data points. In the high-dimensional space, documents are commonly represented as bags of words, with dimensionality equal to the vocabulary size. Classical approaches to document visualization directly reduce this into visualizable two or three dimensions. Recent approaches consider an intermediate representation in topic space, between word space and visualization space, which preserves the semantics by topic modeling. While aiming for a good fit between the model parameters and the observed data, previous approaches have not considered the local consistency among data instances. We consider the problem of semantic visualization by jointly modeling topics and visualization on the intrinsic document manifold, modeled using a neighborhood graph. Each document has both a topic distribution and visualization coordinate. Specifically, we propose an unsupervised probabilistic model, called Semafore, which aims to preserve the manifold in the lower-dimensional spaces through a neighborhood regularization framework designed for the semantic visualization task. To validate the efficacy of Semafore, our comprehensive experiments on a number of real-life text datasets of news articles and Web pages show that the proposed methods outperform the state-of-the-art baselines on objective evaluation metrics.

It's that time of year: The most prepared of you are carboloading after weeks of training for Marathon Monday, while the least prepared are scrambling to finish your taxes. Either way, surely you'll need some breaks in the pasta and accounting. Should you take your kids to Disney's live-action/CGI remake of its beloved 1967 film "The Jungle Book"? Absolutely, says Ty Burr, who gives three stars to this movie placing "talking animals of almost tactile musculature and movement" in a lush jungle landscape; it holds up right until its overly frenetic final scenes. The jungle beasts are voiced by the likes of Ben Kingsley, Lupita Nyong'o, Bill Murray, Idris Elba, and Scarlett Johanssen, and newcomer Neel Sethi is charming as Mowgli.

The future of food looks a lot like advanced animal product substitutes; we've already gone beyond tofurkey to plant-based burgers that "bleed." Down in Santiago, Chile, a five-person startup is using machine learning to figure out how to create its own versions of vegetarian substitutes for animal products. Called the Not Company (or NotCo), the one-year-old company is rolling out its first products -- NotMilk, NotMayo. "All I can tell you is that there are some star ingredients ranging from legumes to flowers," NotCo cofounder Matias Muchnick tells Tech Insider. Machine learning, the programming technique where algorithms learn from data sets, has become the hot new thing in Silicon Valley.

The ACM constitution provides that our Association hold a general election in the even-numbered years for the positions of President, Vice President, Secretary/Treasurer, and Members-at-Large. Biographical information and statements of the candidates appear on the following pages (candidates' names appear in random order). In addition to the election of ACM's officers--President, Vice President, Secretary/Treasurer--five Members-at-Large will be elected to serve on ACM Council. Please refer to the instructions posted at https://www.esc-vote.com/acm2016. To access the secure voting site, you will need to enter your email address (the email address associated with your ACM member record) and your unique PIN provided by Election Services Co. Please return your ballot in the enclosed envelope, which must be signed by you on the outside in the space provided. The signed ballot envelope may be inserted into a separate envelope for mailing if you prefer this method. All ballots must be received by no later than 16:00 UTC on 24 May 2016. Validation by the Tellers Committee will take place at 14:00 UTC on 26 May 2016. Vicki Hanson is a Distinguished Professor of Computing at Rochester Institute of Technology, U.S. (since 2013), Professor and Chair of Inclusive Technologies, Computing, University of Dundee, U.K. (since 2009), and an IBM Research Staff Member Emeritus (since 2009). Previously, she was Research Staff Member and Manager, IBM T.J. Watson Research Center (1986–2008), Research Associate, Haskins Laboratories, New Haven, CT (1980–86), and Postdoctoral Fellow at the Salk Institute for Biological Studies (1978–80). Vicki is the ACM Vice President. She also currently serves as a member of the ACM Executive Committee and Council, on the ACM-W Europe Executive Committee, and on the ACM Fellows Awards Committee (Chair, 2015). She is Vice President at Large of ACM SIGCHI and an ACM Distinguished Speaker. She has served on the SIG Governing Board Executive Committee (2005–14; SGB Chair 2010–12), and as Chair of SIGACCESS, where she revitalized the SIG and established a successful annual conference (ASSETS). She co-founded the field's premier archival journal (ACM Transactions on Accessible Computing) and served as Associate Editor of ACM TWEB. She was on the organizing committee for several SIGPLAN OOPSLA conferences, chaired the recent ACM CEO Search Committee, and currently serves on the Royal Society of Edinburgh Fellows committee (since 2013; Convener 2015). She is an ACM Fellow, a Chartered Fellow of the British Computer Society, a Fellow of the Royal Society of Edinburgh, and a Senior Member of IEEE.

AUSTIN, Texas (Reuters) - The Alamo Drafthouse Cinema Plaza here is a strip mall with a pet-accessories store, a Thai restaurant and a yogurt shop, an unlikely venue to display the high-tech future. But one Saturday morning in March, Google did just that. A small convoy of its driverless cars cruised into the fading asphalt parking lot to give test drives – test rides, actually – to American mayors visiting Austin's annual South by Southwest tech-and-culture festival. Mayor Richard J. Berry of Albuquerque, New Mexico, was impressed with how the cars dodged pedestrians and fallen tree limbs. Sam Liccardo, mayor of San Jose, California, right in Google's backyard, was impressed that he got to see the cars at all. "These things are crawling all over my city" in tests, "but I had to come to Austin to ride in one," said Liccardo. "This is going to change cities."

About a year ago, London design studio Map picked up a job from Honda. The brief called for a design for a self-driving Honda car that could, in some not-so-distant future, take passengers around the world. But the circumstances of the commission were unusual, for two reasons: (1) Map is a small firm that typically works with upstart entrepreneurs, and (2) Honda didn't even want anything tangible or buyable from Map. The automaker wanted beautiful ideas--a concept that gazed dreamily into the future of transportation. Great Journey" is the result of Map's work.

Intellectual Ventures Laboratory has built a new microscope equipped with artificial intelligence to accurately detect malaria from blood samples. The results of their study were published in IEEE Explore. IVL is the research facility of Intellectual Ventures located in Seattle, which is owned by Charles Delahunt. The development of this new microscope was funded by Bill and Melinda Gates as part of the Global Good Fund. The new microscope is called Autoscope.