This post is by Joseph Sirosh, Corporate Vice President of the Data Group at Microsoft. Online transaction processing (OLTP) database applications have powered many enterprise user-cases in recent decades, with numerous implementations in banking, e-commerce, manufacturing and many other domains. Today, I'd like to highlight a new breed of applications that marry the latest OLTP advancements with advanced insights and machine learning. In particular, I'd like to describe how companies can predict a million events per second with the very latest algorithms, using readily available software. Take credit card transactions or loan applications, for instance.

Mumbai: ICICI Bank, India's largest private sector bank, today announced the deployment of'Software Robotics' in over 200 business processes across various functions of the bank. The bank is the first in the country and among few, globally, to deploy'Software Robotics' that emulates human actions to automate and perform repetitive, high volume and time consuming business tasks cutting across multiple applications. At ICICI Bank, software robots have reduced the response time to customers by up to 60% and increased accuracy to 100% thereby sharply improving the bank's productivity and efficiency. It has also enabled the bank's employees to focus more on value-added and customer-related functions. The software robots now perform over 10 lakh banking transactions every working day.

While robots and computers will probably never completely replace doctors and nurses, machine learning/deep learning and AI are transforming the healthcare industry, improving outcomes, and changing the way doctors think about providing care. Machine learning is improving diagnostics, predicting outcomes, and just beginning to scratch the surface of personalized care. Imagine walking in to see your doctor with an ache or pain. After listening to your symptoms, she inputs them into her computer, which pulls up the latest research she might need to know about how to diagnose and treat your problem. You have an MRI or an xray and a computer helps the radiologist detect any problems that could be too small for a human to see.

Goliath takes a holistic view of people and it has four scales covering: mindset, physical fitness, professional performance, and energy management. Each scale is concise and consists of 10 items and the entire assessment takes about ten minutes to complete. The visual presentation of results on our wheel allows an individual to take in a quick snapshot of how they measure up against our criteria. The overall objective is to move towards a position of balance across the four domains, and in particular across the individual elements. More specifically, the closer one is to the outside edge of the wheel the better the result.

Conversational UI is getting a lot of buzz out in the world, and for good reason. We are in an exciting moment as we observe existing technology, design zeitgeist, and user needs aligning around leaner, more immediate, and human ways to engage with digital services. SMS is going through a renaissance, and designers are looking at this medium and interaction model to create new services and experiences. The immediacy and accessibility of SMS make it an ideal channel for building services in a world where systems continue to converge and apps are no longer the medium for digital experiences. As technology becomes more complex, users will need even more simplicity to engage with digital experiences.

Exoskeletons are mechanical structures applied externally to the body and its functions is the improve movement, hold the body of people suffering from an injury or increase physical strength to lift heavy objects. To improve and extend the functionality of these devices, graduates of Technology Monterrey (ITESM) develop an exoskeleton that works with artificial intelligence and is made up of several independent parts to rehabilitate specific body parts as joints through augmented reality. The device acquires motion with brain or muscle signals and measures simultaneously translated by the apparatus noninvasively. Dr. Ernesto Rodríguez Leal, professor at the ITESM, explained that the device can acquire motion by a headband containing electrodes themselves are responsible for receiving and calculate the electroencephalographic signals emitted by the brain and electromyographic produced by muscles. These electrical impulses go to a microprocessor which makes the task of sorting and translate the signals that move the device using artificial intelligence algorithms.

Suddenly the era of driverless cars seems very near indeed. Uber began testing driverless cars in Pittsburgh last week, and this week, the Obama administration endorsed the push to develop these vehicles. Adding to the momentum, Ford and BMW say they will produce autonomous cars by 2021. Driverless cars will create some big winners -- imagine how Uber's and Lyft's profits will jump when they can keep 100% of fares instead of letting drivers keep 70%. But they will produce some big losers too, notably the 5 million people nationwide -- including 600,000 in California -- who make their living driving taxis, buses, vans, trucks and e-hailing vehicles.

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.

Last last year, Adidas began rolling out its plans for Speedfactory, a set of robot-staffed manufacturing facilities located in Germany and, soon, the US. Today, the sportswear giant revealed the first silhouette developed through this new project, known as Futurecraft M.F.G. It's a sleek running shoe that features Adidas' trademark Primeknit upper and Boost midsole, similar to what you see on popular models like Kanye West's Yeezy 350s. While there is some human assistance during the assembly process, as shown in the video below, the majority of the crafting is done by the machines. What's more, the design itself relies heavily on data from ARAMIS, a motion capture technology that maps an individual's skin, bone and muscle to create a more comfortable shoe.

Hacking into a phone is unlikely to physically hurt the victim. A security research team in China hacked into a Tesla Model S and said they took over the car's brakes from 12 miles away. A video released this week shows members of the research team being thrust forward as the remote hacker slammed the brakes on command. The demonstration took place in an empty parking lot. The team from Keen Security Lab, an arm of Tencent, also used a laptop computer to turn on the windshield wipers, retract the side view mirror and pop open the trunk, all while the car was moving.