Marking Google's 15th birthday, Hummingbird is the biggest change to the inner workings of the world's most popular search engine since Google's "Caffeine" update in 2010, which sped up Google's indexing of sites and delivery of search results. The Hummingbird update focuses more on Google's Knowledge Graph – an encyclopaedia of about 570m concepts and relationships that allows Google to anticipate facts and figures you might want to know about your search term. Hummingbird isn't an overhaul that Google search users will instantly notice, however. "In general, Hummingbird – Google says – is a new engine built on both existing and new parts, organised in a way to especially serve the search demands of today, rather than one created for the needs of 10 years ago, with the technologies back then," said Danny Sullivan of the search blog Search Engine Land. It will benefit those using more modern forms of search, such as conversational or voice search, where you ask Google a question rather than typing keywords into the search box.

Like a lot of information-age talk, the phrase is both schizophrenic and appropriate. For if this World Wide Web we grow to depend on is all-connected and all-connecting, an enfolding organism spinning out and out and out, it is also oceanic. And when it comes to using such a vast, dynamic resource, most of us are like the skinny kid in the half-zipped wetsuit, paddling just beyond the first break. On a good day, we can handle a three-foot curl. But we never stray too far from shore. And we can easily wind up a long way down the beach, with no idea how we got there. The images illustrating this article were drawn from a computer animation created by Steve Coast, a computer artist and student of physics at University College London.

Anyone who has been transfixed by a gymnast or a figure skater knows that the magic happens when they perform flawlessly and yet make it seem easy. That's how a search should work: Enter a query, and the right results appear in simple, elegant fashion -- even if it took countless hours of preparation to make the magic possible. Yet most enterprise users still stumble as they try to extract data from multiple repositories, each with its own search engine. Enterprises seem awash in a rising tide of structured and unstructured data. And even though users are often forced to tag documents manually across various content management systems in hopes that those documents will be easier to retrieve, searches still yield a surfeit of irrelevant, time-wasting results.

Trying to picture yourself older or with a different hairstyle is near impossible. But now researchers have developed the ultimate face swap that analyzes a picture of your face, searches for images using key terms and seamlessly maps your it onto the results. Called Dreambit, this AI lets anyone see what they would look like with a different hairstyle or colour, or in a different time period, age, country or anything that can be queried in an image search engine. Dreambit lets anyone see what they would look like with a different hairstyle or colour, or in a different time period, age, country or anything that can be queried in an image search engine - as it has done with American actor George Clooney (pictured). 'Dreambit is a personalized image search engine,' reads the website.

In the year since the European Court of Justice ruled that anyone can ask Google to remove personal information about them, the site has evaluated more than one million links. Each request has to be verified and processed by a dedicated team of people, but the sheer volume can cause delays. To speed this up, researchers from Germany and New Zealand have developed an algorithm capable of analysing hundreds of such requests in seconds. Oblivion (illustrated) allows a user to automatically find and tag their personal information on the web, using both text - or natural language processing (NLP) - and image recognition. And they hope to offer it to Google, and other search engines, to help them manage future demands.

Professor Karen Spärck Jones was one of the pioneers in information retrieval (IR) and natural language processing (NLP). She worked in these areas since the late 1950s and made major contributions to the understanding of information systems. Her international status as a researcher was recognised by the most prestigious awards in her field, the ACM SIGIR Salton Award, the American Society for Information Science and Technologys Award of Merit, the Association for Computational Linguistics Lifetime Achievement Award, the BCS Lovelace Medal, and the ACM-AAAI Allen Newell Award, as well as by her election as a Fellow of the British Academy, of the American Association for Artificial Intelligence, and as a European AI Fellow. Karen Spärck Jones started her research career at the Cambridge Language Research Unit in the late 1950s, working on the use of thesauri for language processing. At this time she collaborated with Roger Needham, whom she married in 1958.

Many web search engines use the concept of a'spider' - automated software which goes out onto the web and trawls through the contents of each server it encounters, indexing documents as it finds them. This approach results in the kinds of databases maintained by services such as Alta Vista and Excite - huge indexes to a vast chunk of what's currently available on the web. However, the problems which users can face when using such databases are beginning to be well documented. A recent JISC-funded investigation [1] into the use of web search engines indicates that users can typically encounter a number of difficulties. These include the issue of finding information relevant to their needs, and the problem of information overload - when far too much information is returned from a search.

The ACM Turing Award, the most prestigious technical award in the field of computing (often referred to as the "Nobel Prize of computing"), is turning 50! The ACM is throwing a big birthday celebration June 23-24, 2017 at the Westin St.Francis in San Francisco, California (https://www.acm.org/turing-award-50). Watch this video to learn more about the award and event, which includes commentary from many past recipients: https://www.youtube.com/watch?v l7qprcl6a-Y . SIGIR is an event sponsor and as part of our sponsorship, we are sending 10 student delegates to the celebration. Those selected will receive travel grants of approximately $1000-2000USD to attend the celebration.

The National Information Infrastructure (NII) will have profound effects on the lives of every citizen. It promises to deliver to people in their homes and offices a vast array of information in many forms, changing the ways in which business is conducted, offering new educational opportunities, bringing geographically dispersed library resources and entertainment materials to everyone's doorstep. It will connect people to people, and help them with their jobs and tasks. For the NII to be useful, however, people will need easy and efficient access to its resources. Today's computers are complex and difficult to use, even for experts. The NII will be orders of magnitude more complex than current systems; it could easily become a labyrinth of databases and services that is inconvenient for experts and inaccessible to many Americans. The field of artificial intelligence (AI) can play a pivotal role in meeting major challenges of the NII. AI uses the theoretical and experimental tools of ...

"About 6,000 languages are currently spoken in the world today," says Elizabeth Salesky of MIT Lincoln Laboratory's Human Language Technology (HLT) Group. "Within the law enforcement community, there are not enough multilingual analysts who possess the necessary level of proficiency to understand and analyze content across these languages," she continues. This problem of too many languages and too few specialized analysts is one Salesky and her colleagues are now working to solve for law enforcement agencies, but their work has potential application for the Department of Defense and Intelligence Community. The research team is taking advantage of major advances in language recognition, speaker recognition, speech recognition, machine translation, and information retrieval to automate language processing tasks so that the limited number of linguists available for analyzing text and spoken foreign languages can be used more efficiently. "With HLT, an equivalent of 20 times more foreign language analysts are at your disposal," says Salesky.