Close on the heels of Amazon's Alexa-powered devices, which can answer health-related questions, Lybrate has empowered its Facebook Messenger chatbot to answer health queries. Users of Lybrate in India will be able to get health advice and tips from the online platform's chatbot. "It is exciting to be India's first healthcare company to be on Messenger Platform and be able to provide smooth doctor access to people and enable them to consume health information that is shared by doctors who have amassed a wealth of medical knowledge over so many years. It is one more step towards letting people in the country be more serious about their health," noted Saurabh Arora, Lybrate's CEO and Founder. Lybrate is essentially an online-based doctor consultation platform that has now protracted its offerings to the popular messaging service from Facebook.

Here are this week's top stories in fraud and big data technology: Thanks to its huge network of users, Sprint has access to vast amounts of user data. Three years ago it established subsidiary Pinsight Media to investigate ways of capitalizing on that data. Since then it has gone from serving zero to six billion ad impressions per months, based on "authenticated first party data" which it alone has access to. The fact that plain passwords are no longer safe to protect our digital identities is no secret. For years, the use of two-factor authentication (2FA) and multi-factor authentication (MFA) as a means to ensure online account security and prevent fraud has been a hot topic of discussion.

Researchers recently demonstrated how an informatics-based adaptive design strategy, tightly coupled to experiments, can accelerate the discovery of new materials with targeted properties, according to a recent paper published in Nature Communications. "What we've done is show that, starting with a relatively small data set of well-controlled experiments, it is possible to iteratively guide subsequent experiments toward finding the material with the desired target," said Turab Lookman, a physicist and materials scientist in the Physics of Condensed Matter and Complex Systems group at Los Alamos National Laboratory. Lookman is the principal investigator of the research project. "Finding new materials has traditionally been guided by intuition and trial and error," said Lookman."But with increasing chemical complexity, the combination possibilities become too large for trial-and-error approaches to be practical." To address this, Lookman, along with his colleagues at Los Alamos and the State Key Laboratory for Mechanical Behavior of Materials in China, employed machine learning to speed up the process.

The IBM Watson IoT Platform allows people to securely and easily connect devices, from chips and intelligent appliances, to applications and industry solutions, and use cognitive services including natural language processing and machine learning for deep insights into hidden or "dark" data for innovation and transformation. The platform also provides the ability to analyze sensor data from billions of devices, to better forecast weather events, for example. During the hackathon, developers will use IBM Watson IoT cognitive APIs and smart devices to create conversational interfaces like chatbots. "People are excited about chatbots because they see the potential to interact with technology using conversational language," said Damian McCabe, VP Engineering at Connected Lab. "As an IBM alumni, I'm excited about the potential of the IBM Watson's cognitive capabilities including natural language processing and machine learning. At the hackathon, developers will use this powerful platform to build more human ways for people to use innovative technology."

The space and renewable energy tycoon has launched yet another pioneer non-profit project which can change the world of robotics today. Elon Musk developed a 1 billion-program "Robot Gym" to train artificial intelligence. He says he wanted the robots to be as versatile as humans when it comes to thinking. Our reinforcement learning toolkit, OpenAI Gym, is now in public beta: https://t.co/8fMRLjSJQb. Tesla's CEO, together with Sam Altman, created the artificial intelligence non-profit research company.

There has been a great deal of talk about the use of Artificial Intelligence chatbots in the last few weeks, especially given the news that Facebook are looking to implement AI into their Messenger and WhatsApp platforms, which are currently used by more than 1.8 billion people worldwide. However, does this bode well for the relationship between humans and Artificial Intelligence programs? Would you rather speak to an intelligent algorithm rather than a fellow human being? We've compiled some pros and cons of the potential'chatbot' revolution, and what it could mean for the future. Customer Service is likely to be the most common use of AI chatbots, but could also prove to be the most divisive.

ETFdb: The Magha CGI 30 index consists of large-cap U.S. equities with an average market cap of about 150 billion. Furthermore, the index is said to comprise socially responsible holdings. What determines if a company is socially responsible or not based on your methodology? In other words, what is the criteria for a company to be included in the index? All corporations give back in some way or another.

Technically Incorrect offers a slightly twisted take on the tech that's taken over our lives. The problem with our education system might be the system part. Where once education used to be a life experience, now it seems more like a business investment, there to guarantee you a certain job and a certain future lifestyle. But if it's there to send young people along a conveyor belt, why do you need teachers? I only reach for this philosophical question because I've learned that students at the Georgia Institute of Technology were recently fooled by one of their teaching assistants.

"Science has not yet mastered prophecy. We predict too much for the next year and yet far too little for the next ten." These words, articulated by Neil Armstrong at a speech to a joint session of Congress in 1969, fit squarely into most every decade since the turn of the century, and it seems to safe to posit that the rate of change in technology has accelerated to an exponential degree in the last two decades, especially in the areas of artificial intelligence and machine learning. Artificial intelligence is making an extreme entrance into almost every facet of society in predicted and unforeseen ways, causing both excitement and trepidation. This reaction alone is predictable, but can we really predict the associated risks involved?

That's the projected galaxy haul of the Large Synoptic Survey Telescope, currently under construction in Chile. Starting around 2023, the LSST camera's 3,200 megapixels will soak up 15 terabytes of data every night, which will fill the biggest astronomical database ever built. Computer scientist Lior Shamir of Lawrence Technological University in Michigan says the amount of data defies comprehension. "With just a mountain of images, no one will ever inspect them one by one. You can never make a discovery," he says. "You need to convert it into something that machines can understand."