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Here Come the iPhone 7 and iOS 10 Apps: What to Try First - NYTimes.com
APPLE released the iPhone 7 last week along with iOS 10, a major upgrade for its popular mobile operating system. What better time to download some apps to take the new hardware and software for a spin? In one update, Apple's messaging system, iMessage, got a turbo boost. It now lets people embellish conversations with stickers, interactive drawings and animations. The messaging system even gets its own App Store for downloading third-party stickers and games.
Microsoft announces new AI-powered health care initiatives targeting cancer
Microsoft has announced a quartet of new initiatives focusing on using artificial intelligence in health care. The company says its researchers are effectively working to "solve" cancer, deploying machine learning techniques for tasks like analyzing tumors and designing new medication regimes. Another projects wants to construct detailed simulations of how cancer develops in different patients' bodies, while one particularly ambitious project -- which Microsoft is calling its "moonshot" effort -- aims to create biological cells that are programmable like computers. Now, creating cells designed to fight cancer is obviously an ambitious task (if it's even possible) and Microsoft is not offering much detail about this particular project. However, personalizing medicine using AI is a much more attainable -- and hopefully effective -- goal.
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Those microphones are backed by Intel's Real Audio technology, a natural language processing system that can respond to commands and questions, and follow context. The Oakley Radar Pace system responded with the beats per minute measurement. It even includes touch sensitive controls, which you can use to access music and talk to Intel Real Audio. For all the built-in technology and sensors, the Radar Pace lacks a heart rate monitor, which means that, if you want to track that key workout metric, you'll need to wear and connect to a third party device.
Large Scale Machine Learning
Dr. Yoshua Bengio's current interests are centered on a quest for AI through machine learning, and include fundamental questions on deep learning and representation learning, the geometry of generalization in high-dimensional spaces, manifold learning, biologically inspired learning algorithms, and challenging applications of statistical machine learning. He is the author of two books and more than 200 publications, with the most influential being from the areas of deep learning, recurrent neural networks, probabilistic learning algorithms, natural language processing, and manifold learning. Dr. Bengio received a Ph.D. from McGill University in 1991, before completing two post-doctoral years at M.I.T. and AT&T Bell Laboratories. He is the Canada Research Chair in Statistical Learning Algorithms. For more, read the white paper, "Computing, cognition, and the future of knowing" https://ibm.biz/BdHErb
Google Drive gets machine-learning search features
Google this week debuted new search and natural-language-processing (NLP) features in its Drive cloud storage service. The key NLP features, which Google has invested in for many years, will be familiar to Google Search users. The search bar in Drive now shows suggestions and retrieves files based on commonly used phrases. NLP is a "fancy way of saying'search like you talk,'" wrote Google Product Manager Josh Smith, in a blog post. "Drive will understand what you mean and give you the option to click for those specific search results."
DeepMind wants its healthcare AI to charge by results -- but first it needs your data
Mark your Google calendars because from today'Don't be evil' rides again, via the DeepMind AI division of the Alphabet ad giant, as a Hippocratic assurance to'Do no harm'. It's no small irony that DeepMind's new mantra for its healthcare push, voiced by co-founder Mustafa Suleyman at an outreach event today for patients to hear what the Google-owned company wants to build with U.K. National Health Service data, is uncomfortably close to its old one -- i.e. the one that embarrassingly fell out of favor. Suleyman cited the Hippocratic oath when discussing his takeaways from patient feedback on the company's plans. "[Do no harm] has to be a mantra we repeat and becomes an inherent part of our process," he said towards the end of the three hour discussion session which was live streamed on YouTube (with a call for comments via a #DMHpatients Twitter hashtag). "And [do no harm] should be the first measure of success before any deployment or before we attempt to demonstrate any utility and patient benefit," he added.
Salesforce Einstein Announced–Artificial Intelligence for Everyone
In a major initiative that has been in the works for two years, Salesforce is integrating artificial intelligence into all of its CRM cloud platforms. It enables any business to use clicks or code to build AI-powered apps that get smarter with every interaction. Their AI system learns from all of the data you enter about your customers and prospects (CRM data, email, calendar, social, ERP, and IoT), and makes predictions and recommendations on actions you should consider. Salesforce Einstein is designed to help their customers take advantage of the huge amounts of data produced by making sense of it and seeing trends before humans typically do. What Salesforce has done is to make the use of artificial intelligence possible for all businesses, without have to employ their own data science teams.
Detecting Well Liquid loading with, Azure IoT, ML, and Pi
Legacy IIoT devices can be modernized utilizing edge of network devices to send data to the Azure IoT hub and Machine Learning. This can create cost and efficiency improvements and reduced downtime. I will try to quickly explain the issue of liquid loading and slow legacy communications. Keep in mind there are many other issues that can be alleviated with this solution and there is no way I could mention them all. Oil & Gas Wells can "Load Up" with liquid reducing production and possibly incurring costly intermediation to relieve the issue.
Why This Machine Learning Engineer Joined a Startup - StartupGDL
Like many aspiring software engineers and entrepreneurs, Haydé Martinez started her career working at large, established enterprises. In her case, she first worked at Intel as an intern -- then at Hewlett-Packard Enterprise as a software engineer. During these early days, she also had the opportunity to study artificial intelligence and machine learning at the renowned Kanazawa Institute of Technology in Japan. But this wasn't enough for Haydé -- she had big dreams and wanted to solve big challenges. When she was presented with the opportunity to work at Rever, she knew that the startup life was for her.
Disrupting Industries With Cognitive Computing
Next-generation cognitive computing is rapidly changing how we live and work. Thousands of brands like 1-800-Flowers and Sesame Street are already using cognitive solutions like IBM Watson to redefine how they improve performance, customer service and revenue. Today's business challenges have never been more complex, and the critical insights that can help address these challenges are often buried in an avalanche of data. With cognitive computing, we are now able to unlock the value in ALL the data -- from internal, external and even publicly available sources -- available to a business. Much of this data was previously inaccessible as it existed in was unstructured (documents, emails, social media posts and images etc.), or was dispersed among any many systems and silos.