Amazon has unveiled a convince store in downtown Seattle that replaces cashiers and lines with technology found in self-driving cars. The app uses a range of sensors that detect what shoppers take off shelves and bills it to their Amazon account if they don't put it back Malaria caused'widespread death' in ancient Rome: DNA... Area 51 revealed: Aerial timelapse of America's mysterious... Watch out, Uber! BMW seeks to be'coolest' ride-hailing firm... Malaria caused'widespread death' in ancient Rome: DNA... Area 51 revealed: Aerial timelapse of America's mysterious... Watch out, Uber! BMW seeks to be'coolest' ride-hailing firm... The store, called Amazon Go', lets customers enter using an accompanied app, grab the items they need and are able to walk out without stopping at a register To enter the store, customers simply open the Amazon Go app and place it to a sensor located on what appears to be a turnstyle in the entrance way. This futuristic store uses the same types of technologies found in self-driving cars – computer vision, sensor fusion and deep learning. When you decide not to purchase and item you've grabbed, just put it back and the technology will automatically remove it from your virtual cart The 1,800-square-foot Amazon Go store is located at 2131 7th Ave, Seattle, WA, on the corner of 7th Avenue and Blanchard Street.

Back in early 2015, Google's mysterious DeepMind unveiled an algorithm that could teach itself to play Atari games. Based on deep neural nets, the AI impressively mastered nostalgic favorites such as Space Invaders and Pong without needing any explicit programming -- it simply learned through millions of examples. But the algorithm had a weakness: memory. Without a memory module, it couldn't store away any information it had already mastered. When faced with problems requiring multi-step reasoning, the algorithm faltered.

It is hard to overestimate the importance of the brain. This organ determines who we are, what we do with our bodies, and controls pretty much everything that we find valuable about the human experience. The 97 sections (per hemisphere) that were previously not known will allow scientists to delve much deeper into the brain's functions. The new map can help surgeons and lead to cures for diseases like Alzheimer's and autism as well a fresh understanding of how our most important organ develops and ages. In particular, researchers from Washington University in Saint Louis found 360 sections in the cerebral cortex, the brain's outer layer of neural tissue.

Smoking cigarettes is the leading cause of lung cancer, the most common cause of cancer death in the world. But nearly 20 percent of lung-cancer diagnoses are made in people who are non-smokers. That means in addition to smoking, geographic, demographic and genetic factors play a role in the devastating disease. A project from Microsoft's research labs is exploring the feasibility of using anonymized web search data to learn more about lung-cancer risk factors and provide early warning to people who are candidates for disease screening. The findings, published Thursday in JAMA Oncology, extend research that team members published last June on the feasibility of using the text of questions people ask search engines to predict diagnoses of pancreatic cancer.

When Robert Schapire started studying theoretical machine learning in graduate school three decades ago, the field was so obscure that what is today a major international conference was just a tiny workshop, so small that even graduate students were routinely excluded. But it has become one of the hottest fields in computer science, turning once-obscure academic gatherings like the upcoming Annual Conference on Neural Information Processing Systems in Barcelona, Spain, into a sold-out affair attended by thousands of computer scientists from top corporations and academic institutions. "It's been really something to see this field develop, and to see things that seemed impossible become possible in my lifetime," said Schapire, a principal researcher in Microsoft's New York City research lab whose machine learning research is widely used in the field. The NIPS conference, which starts Monday, is so popular because machine learning has quickly become an indispensable tool for developing technology that consumers and businesses want, need and love. Machine learning is the basis for technology that can translate speech in real time, help doctors read radiology scans and even recognize emotions on people's faces.

The deep penetration of internet among users in India has paved way for digitization. Digital platforms are leveraging new age technologies such as AI to make lives easier and enriching. Parenting too has joined the digital/ AI bandwagon. Today there are several apps that have implemented AI to help parents nurture and groom their children. This was a much needed revolution in assisting parents to understand the needs and psychology of their children. It guides them throughout the parental journey and helps in develop a mutual understanding that results in healthy relationships within the family.

The Telegraph has proclaimed: "The end of apps is here…" TechCrunch, Mashable, VentureBeat, and others also shared their belief that mobile applications as we know them are a dying breed. But how did mobile apps become endangered? Recently, IO's creators changed the app's name to Luka and added several little helpers, meaning it's now in charge of 12 other bots: Foodie (for restaurant recommendations), Weather, Wiki, Video, Gif, Pic, News, Founders, Search, Calculator, Quiz, and QuestHero. As of July 2016, Luka had around 5,000 downloads on App Store, with a monthly income of less than $5,000 (according to Sensor Tower). Nevertheless, having announced the recent close of a $4.42 million Series A funding round, Luka's creators are more than optimistic about the app's future.

I'd love to talk more about Flowcast, but I'm still not able to shake the image of you making a robotic submarine run by San Diego poolside (laughs). As a STEM enthusiast, I have been in awe of IBM Watson's capabilities. And I feel it's an honor to be talking to someone who has contributed to its capabilities. Winnie: Flowcast came about with my friend and co-founder Ken So. We met back when I was at MIT and he was doing his MBA at Berkeley.

I think that having a so much great resources available can sometimes be both a blessing and a curse. It's great that we have so many tools and sources of information to choose from, but to make best use of it -- and our time -- it is really important to actually "choose" and keep "focused." I don't want to say that many resources are "redundant," since "redundant" has a somewhat negative ring to it. However, there are many different books, tools, and courses that cover essentially the same thing, although, the scope and style may be a bit different. So, instead of adding everything that we stumble upon to our reading lists, I'd say that it makes more sense to be absolutely clear about personal goals first ("What skills do I need to learn to solve problem X?," "Do I really to learn this new, shiny tool X instead of Y?").

This piece, written by MWD Advisors' lead analysts Angela Ashenden, Neil Ward-Dutton and Craig Wentworth, provides an overview of the key trends we see organisations facing in 2017 (and beyond). If you're in a technology leadership role, you should be exploring how these trends will impact the ways you plan, design, deliver and support services and capabilities. At MWD Advisors, our research program is focused, at a high level, on how digital technology changes work. The core of our scope of research is the systems and platforms organisations use to share knowledge, make decisions and co-ordinate work; we look at how new technologies are changing the picture, and what distinguishes successful organisations that reap the benefits of new technologies from those that struggle to drive meaningful change. The three trends we outline below are fundamentally changing the relationship between technology and business.