AI is poised to revolutionize medicine. An overview of the field, with selected applications in ophthalmology. From the back of the eye to the front, artificial intelligence (AI) is expected to give ophthalmologists new automated tools for diagnosing and treating ocular diseases. This transformation is being driven in part by a recent surge in attention to AI's medical potential from big players in the digital world like Google and IBM. But, in ophthalmic AI circles, com puterized analytics are being viewed as the path toward more efficient and more objective ways to interpret the flood of images that modern eye care practices produce, according to ophthalmologists involved in these efforts. The most immediately promising computer algorithms are in the field of retinal diseases.

The need to provide an enhanced customer experience is the primary factor augmenting the growth of the AI in BFSI market. As the competition among the market players is mounting day-by-day, companies have started to focus on providing a better experience to the customers to gain the customer loyalty. This encourages financial institutes to integrate advanced analytics tools and solutions to analyze customer data to fulfil their requirement, understand the customer experience, and to make smarter predictions about their behavior and requirements. Furthermore, companies are also looking forward to connecting with the customers on their choice of channels to provide a more seamless experience. Furthermore, as digitalization is spreading across the globe, customers are becoming more empowered.

According to the DJI's report, around 65 people have been rescued by drones in the last year. The report, "More Lives Saved: A Year Of Drone Rescues Around The World," features the innovative drone technology, and the rapid adoption by first responders to increase the pace of drone use in critical public safety missions. Reports have also stated that drones have dropped buoys to struggling swimmers in Australia and Brazil, and found helpless people in fields, rivers, and mountains. Approximately, 22 out of 65 "were at great risk of death, such as stranded in a body of water or exposed to hazardous weather." "Drones allow rescuers a way to find missing people, deliver supplies like food and life vests, and cut search and response times from hours to minutes," says Brendan Schulman, DJI's Vice-President of policy and legal affairs.

When it comes to artificial intelligence, NASA and other space agencies are nowhere near building a "Terminator" in space. So, you can rest easy -- Arnold Schwarzenegger isn't about to hunt you down because you're leading a rebellion against the machines. Artificial intelligence is in its infancy, but scientists have used it to find alien planets, classify galaxies and create spacecraft capable of dodging debris. But some critics, like SpaceX founder Elon Musk and the renowned physicist Stephen Hawking (recently deceased), have warned that artificial intelligence could be dangerous if left unchecked. While AI is a popular theme in space exploration, its use (and misuse) has been discussed by several people in other applications as well.

Doppler spectroscopy (also known as the radial-velocity method, or colloquially, the wobble method) is an indirect method for finding extrasolar planets and brown dwarfs from radial-velocity measurements via observation of Doppler shifts in the spectrum of the planet's parent star. Otto Struve proposed in 1952 the use of powerful spectrographs to detect distant planets. He described how a very large planet, as large as Jupiter, for example, would cause its parent star to wobble slightly as the two objects orbit around their center of mass.[2] He predicted that the small Doppler shifts to the light emitted by the star, caused by its continuously varying radial velocity, would be detectable by the most sensitive spectrographs as tiny red shifts and blue shifts in the star's emission. However, the technology of the time produced radial-velocity measurements with errors of 1,000 m/s or more, making them useless for the detection of orbiting planets.[3]

Society's operating system needs an upgrade. The model we have been using is simply not up to the challenges of the Fourth Industrial Revolution. A new era is unfolding at breakneck speed. It has huge potential to address some of the world's most critical challenges, from food security, to reducing congestion in big cities, to increasing energy efficiency, to accelerating cures to the most intractable diseases. But it also raises a host of social and governance issues that need addressing.

These venture bets on startups that "returned the fund," making firms and careers, were the result of research, strong convictions, and patient follow-through. Here are the stories behind the biggest VC home runs of all time. In venture capital, returns follow the Pareto principle -- 80% of the wins come from 20% of the deals. Great venture capitalists invest knowing they're going to take a lot of losses in order to hit those wins. Chris Dixon of top venture firm Andreessen Horowitz has referred to this as the "Babe Ruth effect," in reference to the legendary 1920s-era baseball player. Babe Ruth would strike out a lot, but also made slugging records. Likewise, VCs swing hard, and occasionally hit a home run. Those wins often make up for all the losses and then some -- they "return the fund." "If you do the math around our goal of returning the fund with our high impact companies, you will notice that we need these companies to exit at a billion dollars or more," he wrote.

Spanish treasure fleets that traversed the Atlantic Ocean to the Americas and back were a 16th-century invention as important as free two-day shipping. Organized 70 years after Columbus's first voyage, the fleet was made up of several specialized ships with one primary goal: Exploiting the riches of the New World as efficiently as possible. The San José, the largest galleon and the flagship of one group of Spanish ships that started sailing in the 16th century, was big and -- thanks to 62 bronze cannons engraved with dolphins -- deadly enough to deter or destroy ships, whether pirates or rival nations. On June 8, 1708, during the War of the Spanish Succession, the San José's gunpowder ignited during a battle with British ships, sending 600 sailors to the bottom of the Atlantic Ocean -- along with gold, silver and emeralds from mines in Peru, a total haul valued at some $17 billion in today's dollars. It stands as one of the most expensive maritime losses in history.

I recently read an article (paywall) in the WSJ about Paul Allen's Vulcan initiative to curb illegal fishing. It's insightful and sheds light on Big Data techniques to address societal problems. After thinking on the story, it struck me that it could be used as a pedagogical tool to synthesize data science with domain knowledge. To me, this stands as the biggest limitation of what I refer to as'data science thinking'– letting technical skills drive the analysis, only later incorporating domain understanding. This post somewhat reads like a case note from business school and the idea is to get data scientists, product managers and engineers talking earlier on in the process.

MajorMajor CyberCyber--AttackAttack UK Internet Service ProviderUK Internet Service Provider EstimatedEstimated $$$$$$ Loss Loss $55$55 MillionMillion 12. 1717thth Nov 2015Nov 2015: "Islamic State is Plotting: "Islamic State is Plotting Deadly CyberDeadly Cyber--Attacks":Attacks": George OsborneGeorge Osborne 12CyberVision: 2015CyberVision: 2015 -- 20252025 *** 21stC Cybersecurity Trends *** London, UK:: 15th December 2015 Dr David E. Probert: www.VAZA.com