Bengaluru-based multi-speciality hospital chain Narayana Hrudyalaya (NH), which announced its IPO at the start of 2016, has 54 facilities all across India. At its different hospitals, Narayana carries out 650 to 700 cardiac surgeries each month. Speaking at the sidelines of a conference organised by Microsoft India last month, Kumar KV, Vice President at NH chatted with Gadgets 360 about how technology was changing the field of medicine, with immediate developments in fields such as 3D printing, along with long term projects such as the use of deep learning to improve the predictive capabilities of hospitals. At the same conference, Sriram Rajamani, Managing Director at Microsoft Research, India, explained that we are now beyond the point of just talking about machine learning, as gradual improvements in algorithms, and gradual increases in computing power, along with distributed and data processing via the cloud are making it possible for machines to have a quantifiable impact in the field of medicine. For example, Microsoft Research is currently running a project called 99Dots to improve medication adherence for tuberculosis patients.

IMAGE: Sandia National Laboratories researchers are drawing inspiration from neurons in the brain, such as these green fluorescent protein-labeled neurons in a mouse neocortex, with the aim of developing neuro-inspired computing... view more ALBUQUERQUE, N.M. - Computation is stuck in a rut. The integrated circuits that powered the past 50 years of technological revolution are reaching their physical limits. This predicament has computer scientists scrambling for new ideas: new devices built using novel physics, new ways of organizing units within computers and even algorithms that use new or existing systems more efficiently. To help coordinate new ideas, Sandia National Laboratories has assisted organizing the Institute of Electrical and Electronics Engineers (IEEE) International Conference on Rebooting Computing held Oct. 17-19. "We're taking a stab at the scope of what neural algorithms can do. We're not trying to be exhaustive, but rather we're trying to highlight the kind of application over which algorithms may be impactful," said Brad Aimone, a computational neuroscientist and co-author of one paper.

What do artificial intelligence, machine learning, and other innovations have in store for the future of marketing? That was a key question addressed by a panel that included the chief marketing officers from Lyft, IBM Watson, and CVS Health. They gathered last week in New York at 1 World Trade Center to discuss changes consumers may see thanks to brands embracing AI, augmented reality, and tracking. Marketing is making more and more use of these emerging technologies--to better anticipate what customers want. But the rise of this trend raises questions about transparency and maintaining control of personal information.

Base isn't the biggest player in a crowded CRM market by any means, but it's not shying away from a fight with industry giants like Salesforce, Microsoft, Oracle and SAP. This week it introduced Apollo, a stand-alone artificial intelligence piece its CEO claims is well ahead of its well-heeled competitors -- and it chose to announce this new product in the middle of Dreamforce, Salesforce's enormous customer conference. Artificial intelligence is the watchword of the day in CRM with both Salesforce and Oracle announcing AI products/features in the same week a couple of weeks ago. The bigger companies are adding smarts to more than just CRM, but Base CEO Uzi Shmilovici thinks his company's singular focus on CRM may be an advantage. Shmilovici claims for instance that his company's predictive scoring is much better than Salesforce's because he has more data.

Today, CircleBack, Inc. announced the launch of 3 APIs based on their artificial intelligence-driven engine, SharedIQ, to revolutionize the state of B2B contact data productivity. Each of the APIs--Email Signature Capture, Contact Append & Company Append--offers enterprise customers the opportunity to build high-accuracy, high-value contact data flow into the hearts of their offerings and bolster the efficiency of the CRM, Marketing Automation Systems, and Account-Based Marketing tools currently on the market. Since the launch of the CircleBack app in early 2015, CircleBack, Inc. has worked to offer businesses the same access to its proprietary AI engine that it offers to over 2 million app users. The CircleBack engine uses artificial intelligence and billions of contact data points to discover, append, and update enterprise contact data. "CircleBack APIs will bring organizations much-needed control of their contact data," explains Manoj Ramnani, CircleBack, Inc. Founder and CEO.

The Spain-headquartered startup, which today is announcing 6 million in Series A funding, is using deep learning to help startups and larger companies recruit developers. Specifically, its AI tech is analysing the code of millions of developers via their open source contributions in order to match them to appropriate job openings. Meanwhile, the company, which is only in its second year of operation, say it's already close to being profitable and on track to close the year something approaching 1 million in revenue. It also plans to further develop its product, including applying its AI-driven analysis of code to other products aimed at developers, both free and paid-for.

San Francisco-based Demandbase, a business-to-business (B2B) marketing company, is putting its Spiderbook acquisition to work by adding a layer of artificial intelligence (AI) to its Account-Based Marketing (ABM) platform. Spiderbook, which Demandbase acquired in May, offers machine learning and data science to analyze web pages and target accounts. Demandbase capitalized on those capabilities to create DemandGraph, an AI-powered business graph designed to help marketing and sales teams collect business data like vendor, customer and partner relationships. Demandbase CEO Chris Golec told CMSWire the DemandGraph AI capabilities take Demandbase's digital footprint of information on companies and "exposes it to a much bigger set of data." "If you think about what Salesforce is doing with Einstein, that's all about applying AI to (customer relationship management) CRM data and the people you're doing business with," Golec said.

Financial markets, throughout their evolution, have always been susceptible to manipulations and various unscrupulous activities. The history can be traced back as far as 600 BC when a Greek merchant borrowed money from public to grow corn. The lenders were assured of repayment along with interest when the product was sold. In case of failure to repay on time, the lenders could acquire merchant's cargo along with the boat. The fraud designed by the borrower was to sink the empty boat and keep both the money and corn.

Artificial intelligence (AI) made the leap from science fiction to the corporate world some time ago. Amazon and Netflix use it routinely to make purchasing recommendations, iPhone users speak to Siri every day, and banks give investment advice or calculate risks thanks to these technologies. But these are only the first hesitant steps of AI, which is due to have a major impact on the financial sector, as revealed in this report in the magazine Euromoney, and featuring an interview with Marco Bressan, Chief Data Scientist at BBVA. Artificial Intelligence has been present in the financial industry for many years now, Marco Bressan, Chief Data Scientist at BBVA, tells Euromoney: "Currently it denotes a vision of the future; an aspect of the sci-fi imagination; something that you still can't do. But the truth is senior financial executives have been doing AI-related work, research and deployment of products for years", he notes. When we talk about Artificial Intelligence we refer to a set of technologies –many created decades ago– rather than one single product or system.

How many robots does it take to open a door? If the robots are trying to figure out how to do the task from scratch, then it helps to have as many as possible involved. In three separate research papers posted online Monday, researchers at Google and other Alphabet subsidiaries showed several ways in which robots can learn to perform simple tasks more quickly by sharing different types of learning experiences. The researchers are training teams of industrial robots to perform simple tasks using a technique called reinforcement learning, which combines trial and error with positive feedback. For the moment, these tasks are extremely simple, like opening doors or nudging objects around.