Shrap Talos lent backward into his outdated interface, closing his eyes as the wall-sized array hijacked his visual cortex and an image took shape. He could see the archive as a highly detailed three dimensional sphere from every angle at once, as if he had a thousand eyes orbiting it like satellites around a planet. That had taken him a while to get used to six long months ago when the technology had first come out. If it wasn't for the daily regime of drugs he was taking to enhance his neuroplasticity, he might never have managed. His plumage shifted a fraction as the thought of being left behind sent a chill across his skin. His role in all this was of the chief architect and maintainer of the archive.

Computers don't have the ability to understand English language, and to address this issue, this is where the Google's free AI software dubbed Parsey McParseface, based on SyntaxNet machine learning framework comes in. The search engine giant announced on Thursday that it will release a new piece of software that will understand written English. More interestingly, Google will release the AI software as open-source which means developers can freely use the software to train computer programs with ability to process natural language. Google says its latest innovation will be equipped with Natural Language Understanding (NLU) to parse written English sentences with up to 94 percent of accuracy. Google added that trained human linguists can only achieve up to 96 percent of accuracy. As an AI machine to achieve such milestone, it is a huge breakthrough in the field of artificial intelligence.

Collaboration With STFC Hartree Centre Taps into IBM Watson to Improve Patient Experience. Alder Hey Children's NHS Foundation Trust today announced a ground-breaking multi-year collaborative programme with the Science and Technology Facilities Council's (STFC) Hartree Centre, supported by IBM (NYSE: IBM), to create the United Kingdom's first'cognitive' hospital by harnessing'big data' and the power of IBM's Watson technology platform. This is the first time that Watson technology will be applied to improve patient experience in the United Kingdom. Alder Hey and the Hartree Centre believe that by applying Watson -- an innovation in computing technology -- it will enhance patient care and potentially generate savings for both the hospital and the NHS (National Health Service) as a whole. Using Watson to analyse any feedback that is voluntarily and securely provided by the patients, with appropriate consent as needed, it is anticipated that Alder Hey will be able to greatly enhance patient experience by; identifying patient anxieties and providing information and reassurance on-demand; reminding young patients and their parents about appointments and about aftercare; and providing insightful feedback to clinicians based on the tone and sentiment of these interactions.

If you love to dance, but fear that your partner might step on your toes, then a new virtual, computer-controlled dancer might be for you. And this virtual dancer may even teach you some new moves when you tango with it, a new project finds. The computer-generated dancer -- dubbed virtual artificial intelligence -- is the brainchild of researchers at the Georgia Institute of Technology in Atlanta. The virtual dancer "watches" a person dancing, and then improvises moves of its own based on its earlier dancing experiences, the researchers said. Once the human dancer responds to the virtual dancer's moves, the virtual dancer responds again, making an impromptu dance with its deft artificial intelligence.

"Here" is a funny word. So says Scott Hassan, the media-shy Silicon Valley billionaire who once set out to build the first fully autonomous humanoid robot, and ended up hawking what looks like a flatscreen atop two long legs with wheels. If Hassan has his way, this seemingly simple device--called a Beam--will close the loop between cyberspace and meat-space. The Beam was designed as a video conferencing tool, allowing instant, face-to-face communication--kind of like FaceTime or Skype, except you can drive the screen on legs around the room remotely, with a keyboard. It could one day become much more.

In one week from now, Google I/O 2016 will have come and gone, and we could very well be revelling in new services, features and if we're lucky, new products. Considering we are only a few days away, there have been very few leaks out of Mountain View, hopefully, that isn't a reflection on the quality of what Google has in store for us all. Our Editor in Chief Dan Tyson will be on the ground again this year, bringing us both hands on coverage as well as seeking out the Australian perspective on everything announced at I/O. No I/O would be complete without just a little speculation on what is coming, however, before we get to that it is important to remember that at its heart I/O is a developer conference, it is intended to let Google inform developers of how to utilise Google's service new and existing, and let developers get up close and personal with Googlers and their knowledge. Now let's get down to guessing speculating on what Google may have in store.

Machine learning is not a new term, but in the last few years it has been brought to the spotlight due to technological advances and bets made by major players like Google and Facebook. We have to go back to 1959, and see Arthur Samuel define it for the first time as the "Field of study that gives computers the ability to learn without being explicitly programmed", but since that it has evolved. Classification: For when you want the algorithm to discriminate and categorize classes on the data available. For example we want it to select from a set of images, the ones who have a computer in it. Regression: In this case it gives us a correlation of outcomes, based on the past experience. In a simple example, if a team always looses when it's raining, the algorithm can show that correlation and the coach can see how can he solve that problem.

A couple of us here built a topic-based group texting app and thought it'd be fun to add a chatbot to find restaurants, where to get coffee, etc. We trained it on a lot of movie scripts and connected it to a bunch of APIs. Love for you guys to test it out and give us some feedback. Once you are in the app, the chatbot is under the "Channelbot" channel. Love to hear areas of improvement from you all, so we can figure out how to further improve it.

Qualcomm, Inc. (NASDAQ:QCOM) is bringing neural networks to its Snapdragon 820 chips. The chipmaker has announced that it will be shipping out software development kits later in 2016 giving its chips some new smart features. Qualcomm is making use of its 820 system on a chip's "heterogeneous compute capabilities" with its Qualcomm Snapdragon Neural Processing Engine built atop of the company's Zeroth Machine Intelligence Platform. Developers can use the SDK to turn Qualcomm's chip into a deep learning machine on which to develop and compile neural network models. The potential applications for portable deep learning in mobile devices are inexhaustible.

Deep learning users can now access pre-configured NVIDIA DIGITS Titan-X GPU instance starting at 49 cents per hour on Nimbix! Data Scientists and Deep learning users can now try the single-click solution on Cloud Service Provider Nimbix to launch an instance configured to run NVIDIA DIGITS on Titan-X GPUs at as low as 0.49/hour, the most affordable high performance GPUs compared to anywhere in the cloud, powered by Bitfusion Boost's Software Defined Supercompute technology. The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning in the hands of data scientists and researchers. Best of all, DIGITS is a complete system so you don't have to write any code. You can train neural network models, including pre-built AlexNet and GoogleNet models.