Google is expected to dive deeper into virtual reality and artificial intelligence Wednesday during an annual conference that serves as a launching pad for its latest products and innovations. Although Google keeps its plans under wraps until the big event, the conference agenda makes it clear that virtual reality and artificial intelligence, or "machine learning," will be among the focal points. That has spurred speculation that Google is getting ready to release a virtual-reality device to compete with Facebook's new Oculus Rift headset, as well as the Samsung's Gear VR and the Vive from HTC and Valve. Reporters and bloggers from around the world will attend, ensuring that whatever the company unveils will also be featured in stories, pictures and video delivered to a vast audience of consumers. The three-day showcase also attracts thousands of computer programmers, giving Google an opportunity to convince them why they should design applications and other services that work with its gadgets and an array of software that includes the Chrome Web browser and Android operating system for mobile devices.

Dozens of companies who fancy their technologies as a great fit for the automotive market are on the hunt for alliances. For example, Kyocera and FotoNation announced Tuesday (May 17) a partnership agreement to develop intelligent automotive camera technology -- deemed critical in the coming era of semi- and fully autonomous cars. Kyocera has already dabbled in the auto sector with its rearview camera modules. FotoNation, with the lion's share of computational imaging solutions for mobile phones, entered the driver monitoring system market last year. "The two companies' interests are aligned," Sumat Mehra, senior vice president of marketing and business development at FotoNation, told EE Times, "to expand each company's presence in the automotive market" -- well beyond what they offer today.

Google relies heavily on AI to help with its search functions as well as features like Google Now. However it looks like Google could soon be thinking of applying their AI to other features, such as chatbots and potentially integrate them into their other services like Google Hangouts, a messaging platform for Google users. The idea of chatbots aren't new, although recently they seem to have undergone a resurgence in popularity and are being used by the likes of Facebook and Microsoft. This is according to a report from The Information (paywall; via USA Today) in which it reads, "Essentially, Google wants to get into the bot-making business more broadly than people realized, and in a way that's similar to Microsoft's strategy, and relying on its strengths in artificial intelligence to convince developers to use its tools." Last year there were reports that Google was planning something similar and that by integrating it into messenger services like Hangouts, users could pose questions to the bot and have it answered for them without having to leave the app itself.

Sony Corp. said Wednesday it has invested in U.S. artificial intelligence startup Cogitai, aiming to develop new AI technologies and release products using them within the next three years. Sony is believed to have obtained a roughly 20 percent stake in the company, founded in September by three AI researchers, in a move that could lead to the Japanese electronics giant's return to the robot business. Sony was an AI pioneer, known for producing robotic dog AIBO and humanoid QRIO featuring AI technologies. But it withdrew from the robot business in 2006 to improve profitability and restructure its consumer electronics business. The company has continued AI research itself, however, and its technologies, including face and speech recognitions, have been applied to other Sony products, such as digital cameras and smartphones.

"I didn't expect the machine could learn to do the experiment itself, from scratch, in under an hour," said co-lead researcher Paul Wigley from the Australian National University (ANU) Research School of Physics and Engineering in a statement. "A simple computer program would have taken longer than the age of the universe to run through all the combinations and work this out," he added. Scientists wanted to recreate an experiment that won the 2001 Nobel Prize in Physics, which involved extremely cold gas trapped in a laser beam known as a Bose-Einstein condensate. The condensates "are some of the coldest places in the Universe, far colder than outer space, typically less than a billionth of a degree above absolute zero (-273.15 The experiment involved trapping 40 million atoms at the intersection between two laser beams. The team used magnetic fields to cool the atoms down to about five millionths of a degree above absolute zero. Scientists then used the AI algorithm to control the lasers during cooling, carefully tuning the power of the two lasers to allow the most energetic atoms to escape without losing hold of the coldest ones. The AI algorithm was able to do this ten times faster than a regular non-AI program. "It is cheaper than taking a physicist everywhere with you.

Advances in technology continue to change the workplace. Forty years ago, the first cell phone was introduced, enabling a virtual working environment. In 1989, the World Wide Web surfaced, soon followed by Google and other search engines. And more than a decade ago, Facebook launched, connecting users from around the globe in a digital community with a level of detail and dialogue that hadn't been seen before. Today's data-rich work environment continues to change, and successful business leaders understand the role that technology will play in simplifying business processes and increasing employee productivity.

While a huge segment of the planet is still struggling to grasp the various concepts revolving around the rapidly emerging cryptocurrency industry, those that do grasp said concepts are going on a wild shopping frenzy over the currencies. Case in point, Decentralized Autonomous Organization (DAO) recently launched a crowdsale for DAO tokens and nabbed over a hundred million dollars within a few weeks, making them the largest crowdfunded project in history. DAO, a platform developed by German company Slock.it, is a self-governing company built upon an irrefutable mathematical code that is free for everyone to use. It's main mission is "to blaze a new path in business organization for the betterment of its members, existing simultaneously nowhere and everywhere and operating solely with the steadfast iron will of unstoppable code." It runs on the platform Ethereum, which in turn runs on a blockchain, essentially resulting in a system which allows fast and direct trade, and records all transactions for everyone to see in absolute transparency.

If God created his universe in 7 days; what could AI do to ours? The arrival of artificial intelligence promises the Intelligence Explosion - where singularity would lead to an exponential increase in A.I. capabilities. This Super Intelligence could lead to the arrival of an omniscient, omnipresent, omnipotent being. How would humanity receive this new entity? This multimedia essay comes is in two parts.

My name is Jonathan Armoza and I am a data science intern at Neustar and a PhD candidate in English Literature at New York University. My work focuses on the development of computational text mining and visualization methods in the emerging field of digital humanities. The era of big data has created the need to develop techniques and mechanisms to not only handle large datasets, but to understand them as well. Much of this influx of information is about people, places, and things. Although some of that data is anonymized, there are a number of reasons we might want to understand how to associate those real world "entities" with their data points.

Secondary use of electronic health records (EHRs) promises to advance clinical research and better inform clinical decision making. Challenges in summarizing and representing patient data prevent widespread practice of predictive modeling using EHRs. Here we present a novel unsupervised deep feature learning method to derive a general-purpose patient representation from EHR data that facilitates clinical predictive modeling. In particular, a three-layer stack of denoising autoencoders was used to capture hierarchical regularities and dependencies in the aggregated EHRs of about 700,000 patients from the Mount Sinai data warehouse. The result is a representation we name "deep patient".