The past few months were full of exciting announcements around two key topics: artificial intelligence and mobile messaging. Both have made significant leaps in progress, and together will make a very exciting year ahead for businesses. This year, Google announced Click-to-Message; Amazon released the Lex bot building toolkit; and mobile messaging platforms like Facebook Messenger and WhatsApp surpassed 1 billion monthly active users. To keep up with the massive growth of these messaging channels companies are scrambling to develop both an AI strategy and a messaging strategy. However, 2017 will show that both strategies are extremely intertwined.

The speed of a system like ScenGen is powerful, but it's also an incredibly sturdy shield. AI systems can take cyber security to the next level by processing every possible threat and fortifying your system in advance. Using your teams, you can operate the same way in a more general sense by, instead of searching outward for marketing possibilities and risks, searching inward for weaknesses and potential problem areas. By making sure that structural integrity is sound, business owners can fortify structures to withstand anything, giving peace of mind both to brands and their customers.

Artificial intelligence is changing and improving the ways we manage our money. Research suggests Australians are ready to embrace fintech banking solutions, and the launch of three new London-based chatbot startups may be a sign the rest of the world is gearing up for a revolution too. Artificial intelligence (AI) has been rapidly progressing over the past two decades, with machines reaching and exceeding human performance on an increasing number of tasks. Just this week, the White House released a report entitled Preparing for the future of Artificial Intelligence, which describes the ways in which AI has and continues to yield new opportunities for progress in critical areas such as health, education, energy, and the environment. Another important area of business, ripe for disruption, is finance and banking.

Intelligent software could "eat" into diagnostic radiology, just as it has eaten countless other industries. We think the result, deep learning based diagnostics software, will likely lead to faster, cheaper, and more accurate diagnoses on a global scale. The key enabling technology is deep learning, a form of artificial intelligence (AI) that has established benchmarks in a broad range of applications.[1] ARK estimates that the total global addressable market for computer aided diagnostics (CADx) software could be $16B, as shown below. From a $1B base today, we think medical software companies and imaging device manufacturers have a strong and long revenue runway ahead, ready to revolutionize radiology.

In the software development industry, 2016 was truly transformative. The way software is developed, what it is being created for, and where it resides and is used all changed to a large degree last year. More development teams adopted agile and DevOps techniques, while QA "moved left" and integrated into the process, rather than being a post-development effort. The definition of the application life cycle changed (or expanded, depending on your point of view) to include deployment. Development shifted from doing nightly builds to Continuous Integration. Software release went from a major one-time event to Continuous Delivery.

There is no doubt that the technology landscape is changing at a frenetic pace and staying ahead of the major trends reshaping today's world will ultimately separate the winners from the losers. We have all heard the mantra of these days, "you either disrupt yourself or you will get disrupted". The risk of becoming irrelevant has never been greater. It's the role of CIOs to look beyond today's solutions and be ready for what lies ahead. However, the list of innovations can be endless and keeping up with the latest emerging technologies and new tools is no easy task.

A lot of companies have job titles that include "Research" and/or "Scientist." Be aware that these tend to have stricter requirements on graduate degrees. But, also know that the same company may have Engineering roles which aren't as strict. Take a look at this pair from Recursion Pharma: Machine Learning Engineer vs Deep Learning Scientist. The requirement for a PhD is going to change over time. These techniques have been so cutting-edge that a graduate degree has been about the only way for employers to find candidates with a few years of experience.

Earlier this month, Apple's Director of AI Research, Russ Salakhutdinov, announced that the company was getting into publishing research. The six researchers who published the paper belong to a recently formed machine learning group. Synthetic images and videos are being used to train machine learning models. They are readily available, less costly, and customizable. Although the new technique reportedly has a lot of potential, it is risky because generated images do not meet the same quality standards as real images.

GE was still essentially a startup when its managers hired young MIT chemistry professor Willis Whitney to open the company's first laboratory in 1900. Unlike Thomas Edison's Menlo Park "invention factory" in New Jersey, the place was a modest affair. It was located in a wooden barn behind the house of GE's resident polymath and engineering wizard Charles Steinmetz in Schenectady, New York, where GE co-founder Edison moved in the 1880s. The lab -- dedicated to "fundamental research" -- went up in flames the next spring, but Whitney's career and momentum continued. He rebuilt the lab and brought in researchers such as Nobel Prize-winning chemist Irving Langmuir.

MANGALURU: To provide continued access to world-class treatment to the people of Mangaluru, KMC Hospital announced the launch of a new block at Dr B R Ambedkar Circle. The new block, which is equipped with state-of-the-art multidisciplinary facility to cater to people with all types of ailments, will be inaugurated by defence minister Manohar Parrikar on Sunday. Dr Krishna Prasad, medical oncologist at KMC Hospital Mangaluru, said, "On the occasion, the IBM Watsons for oncology will be inaugurated at the hospital. "The supercomputer uses artificial intelligence as a tool for diagnosis and treatment of cancer," said Dr Prasad. Manipal Hospitals is only the second hospital chain in the world to deploy the technology, the first being Memorial Sloan Kettering Cancer Centre, New York," he claimed.