Motivation: Text mining has become an important tool for biomedical research. The most fundamental text-mining task is the recognition of biomedical named entities (NER), such as genes, chemicals and diseases. Current NER methods rely on pre-defined features which try to capture the specific surface properties of entity types, properties of the typical local context, background knowledge, and linguistic information. State-of-the-art tools are entity-specific, as dictionaries and empirically optimal feature sets differ between entity types, which makes their development costly. Furthermore, features are often optimized for a specific gold standard corpus, which makes extrapolation of quality measures difficult. Results: We show that a completely generic method based on deep learning and statistical word embeddings [called long short-term memory network-conditional random field (LSTM-CRF)] outperforms state-of-the-art entity-specific NER tools, and often by a large margin. To this end, we compared the performance of LSTM-CRF on 33 data sets covering five different entity classes with that of best-of-class NER tools and an entity-agnostic CRF implementation. On average, F1-score of LSTM-CRF is 5% above that of the baselines, mostly due to a sharp increase in recall. Availability and implementation: The source code for LSTM-CRF is available at https://github.com/glample/tagger Text mining is an important tool for many types of large-scale biomedical data analysis, such as network biology (Zhou et al., 2014), gene prioritization (Aerts et al., 2006), drug repositioning (Wang and Zhang, 2013) or creation of curated databases (Li et al., 2015).

The robotics work programme implements the robotics strategy developed by SPARC, the Public-Private Partnership for Robotics in Europe (see the Strategic Research Agenda). Every week, euRobotics will publish a video interview with a project, so that you can find out more about their activities. Hephaestus project addresses novel concepts to introduce Robotics and Autonomous Systems use in the Construction Sector where the presence of this type of products is minor or almost non-existent. It focuses to give novel solutions to one of the most important parts of the construction sector, the part related to the facades and the works that need to be done when this part of a building is built or need maintenance. It proposes a new automatized way to install these products providing a whole solution not only highly industrialized in production but also in installation and maintenance. Hephaestus aims at automating the On-site Execution or Installation process for empowering and strengthening the Construction Sector in Europe and for positioning the European Robotic Industry as leader and reference in the huge and new growing market for the robotics.

Machine learning is perhaps the hottest buzzword in cybersecurity today. The artificial intelligence technology is deployed by cybersecurity firms in an effort to keep pace with the evolution of cyberattacks, as machine learning algorithms are able to improve predictability the more it is used. But according to Guy Caspi, CEO of cybersecurity company Deep Instinct, machine learning is no longer enough in an age of unprecedented evolution and volume of cybercrime. G DATA researchers recently found that last year a new malware specimen surfaced every 4.6 seconds. In the first quarter of 2017, it reduced to every 4.2 seconds, meaning millions and millions of new malware surfaced every year.

So far, the company has completed two acquisitions, relocated its headquarters to Melbourne, and is now in the process of expanding its cognitive computing and machine learning footprint. Mark Armstrong, vice president and managing director of international operations for APJ and EMEA, for Progress, discusses the company's mission to democratise data science and make technologies such as machine learning, predictive maintenance and Artificial Intelligence more accessible so businesses in Australia and New Zealand can succeed. One of the reasons for our success in the region is the strong collaboration with our local channel partners. We have a strong partner program, and our A/NZ partners have delivered incredible value to the Progress' ecosystem in the past year. Actually just last May, three of our Australian partners were awarded by Progress' Global Partner Awards, amongst the 18 winners across 10 countries.

We are used to bots mimicking humans, and animals, but there is plenty of life beyond the constraints of legged bodies that can inspire useful machines. Researchers at the University of California, Santa Barbara and Stanford University have made a machine with long tendrils that can perform dangerous tasks like reaching through rubble to pump air to a trapped earthquake survivor. In a new study in the journal Science Robotics, researchers Elliot W. Hawkes, Laura H. Blumenschein, Joseph D. Greer, and Allison M. Okamura demonstrate a robot that travels through space like a living thing, but that is perhaps best thought of as a fast-growing, useful, mechanical plant, which unfurls from a single immobile foot. The robot's design is explicitly plant-inspired. "I remember watching an English ivy plant," says Hawke, "over the course of months, grow around the corner of my bookshelf seeking the sunlight and thinking that in a certain, very slow way, it was going somewhere."

The 21st International Cloud Expo has announced that its Call for Papers is open. Cloud Expo, to be held October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Digital Transformation, Machine Learning and WebRTC to one location. All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades. With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo @ThingsExpo, June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA.

Atari, the same company behind the Atari Computer System, has announced a new product called the Atari Speakerhat. The new device is exactly what the name describes: a baseball cap with built-in speakers. "The Atari Speakerhat is a baseball-style cap with high-fidelity stereo speakers and microphone that can connect instantly to any Bluetooth-enabled device," the company said on its website. "Connect to any smartphone, tablet, personal computer to play any music or other media content, initiate or accept phone calls, receive voice commands, etc." The speakers are embedded right in the underside of the cap's bill/visor.

AI may not be able to lead us just yet, but it can judge how well we lead. New findings suggest Apple's CEO, Tim Cook, may just be Silicon Valley's "most imaginative" leader, reported CNBC, citing data from job search firm Paysa. It examined their "speeches, essays, books, transcripts of interviews and other forms of communication" to generate a Personality Insights report. Cook emerged as the industry's "most imaginative" leader, followed by Amazon's Jeff Bezos. Advances in AI mean IBM's Watson can do more than just read your personality.

Hook has just rolled out what it is calling the first artificial intelligence generated fashion feed for consumers. The Hook Fashion Discovery is free and available at the App Store and on Google Play. Parent company Intelligence Node said the app features "user-friendly, editorial-style" content that aims to educate users "at a glance on trending styles and current bestsellers." The company said there are "millions of stockkeeping units featured" on the app, and that shoppers can search for "virtually any fashion item." The app is being positioned in the market to target Millennials.

We are familiar with the famous saying "dog is a man's best friend," but no one could figure out exactly why this particular animal carries the capability of being so friendly toward humans. According to a study published Wednesday, the reason behind humans and dogs striking a common cord might be because the latter descended from wolves. The study found that hyper-social canines carry variants of the genes GTF2I and GTF2IRD1, the deletion of which, in humans, triggers the Williams-Beuren Syndrome, or more commonly known as the Williams syndrome. Bridgett vonHoldt of Princeton University and her colleagues studied a portion of DNA in dogs that included 29 genes. They noticed that deletion of part or all of this section due to prolonged domestication seemed to cause the overtly friendly nature in dogs.