Last summer at the Black Hat cybersecurity conference, the DARPA Cyber Grand Challenge pitted automated systems against one another, trying to find weaknesses in the others' code and exploit them. "This is a great example of how easily machines can find and exploit new vulnerabilities, something we'll likely see increase and become more sophisticated over time," said David Gibson, vice president of strategy and market development at Varonis Systems. His company hasn't seen any examples of hackers leveraging artificial intelligence technology or machine learning, but nobody adopts new technologies faster than the sin and hacking industries, he said. "So it's safe to assume that hackers are already using AI for their evil purposes," he said. "It has never been easier for white hats and black hats to obtain and learn the tools of the machine learning trade," said Don Maclean, chief cybersecurity technologist at DLT Solutions.

Almost every day, there's news about a massive data leak -- a breach at Yahoo that reveals millions of user accounts, a compromise involving Gmail phishing scams. Security professionals are constantly moving the chess pieces around, but it can be a losing battle. Yet, there is one ally that has emerged in recent years. Artificial intelligence can stay vigilant at all times, looking for patterns in behavior and alerting you to a new threat. While AI is not anywhere close to being perfect, experts tell CSO that machine learning, adaptive intelligence, and massive data models that can spot hacking much faster than any human are here to help.

AI has become such a huge topic that late last year the White House released a report on the Future of Artificial Intelligence, which focused on the opportunities, considerations, and challenges of AI. As more and more industries, including healthcare and financial services, adopt AI technology, the technology's value will increase its impact on society as a whole. AI, machine learning and other technologies are already making a significant impact in several industries, including e-commerce, hospitality, and retail. While there has always been a slight tension among workers about robots taking over and claiming jobs, there is a lot to be said about how these types of technologies will, in fact, add more value, contribute to economic growth and augment the workplace so employees can work more effectively. It starts with the huge volumes of contracts that define business relationships, capture the rules of engagement and are the foundation of business transactions every day.

Tim Cook had indicated a lot of developments from Apple in his quarterly earnings call last week. He indicated that the company's flagship smartphone, the iPhone still had much more technological evolution to go for. Here is the range of products that the Apple CEO talked about and based on how they are expected to develop in 2017. "I think the smartphone is still in the early innings of the game," Cook said about the iPhone. Could this be an indication of some new technological changes coming to the device so as to keep it in "the game?" Apple generally launches just one phone per year compared to its competitors such as Samsung and LG, which have devices at various price ranges and have round the year launches.

Connected cars and the Internet of Things go together like peanut butter and jelly. But realizing the future of autonomous vehicles will demand close attention to be paid to cybersecurity, functional-safety standards, and other critical factors. IoT will advance the era of self-driving cars, which currently is dominated by Tesla Motors. At the same time, it will change some of the dynamics in this market. On one hand, it will turn automotive manufacturers into technology companies, which could provide new revenue streams for carmakers. On the other hand, it will open the door for new players that have never had a viable entry point in the automotive market. Consider the case of Velodyne LiDAR, a Morgan Hill, Calif.-based company, which last month opened a factory in nearby San Jose to manufacture its LIDAR product.

There has been a lot of hype around machine learning lately. Over the past decades, we've heard about various concepts around machine intelligence that in most cases didn't get anywhere. But more and more frequently, organizations are learning how to bring together all the ingredients needed to leverage machine learning, and there is a simple reason for that: according to Moore's law, the performance of microprocessors has increased since 1980 be a factor of more than 16 million! A program that ran on a 1980 computer for more than half a year today delivers its results in one second! That is why I think Machine Learning will be the story for 2017.

As part of an ongoing effort within Microsoft to improve the accuracy of artificial intelligence (AI) systems, Microsoft Translator is publicly releasing a set of data that includes multiple conversations between bilingual speakers who are speaking French, German and English. This corpus, which was produced by Microsoft using bilingual speakers, aims to create a standard by which people can measure how well their conversational speech translation systems work. It can serve as a standardized data set for testing bilingual conversational speech translation systems such as the Microsoft Translator live feature and Skype Translator. Christian Federmann, a senior program manager working with the Microsoft Translator team, said there aren't as many standardized data sets for testing bilingual conversational speech translation systems. "You need high-quality data in order to have high-quality testing," Federmann said.

Facial recognition technology has come a long way since Facebook first asked you to tag yourself in your uploaded photos. Refined over the years, it now tags you and your friends automatically, and can identify you in photos even when your face is hidden. Face recognition technology has sat comfortably in pop culture for decades, when detectives on TV scanned databases on the hunt for suspects, the faces blending into each other until PING! It took reality a little longer to catch up to the foresight of Hollywood, and while we haven't reached the invasive face analysis-based advertising showcased in Spielberg's'Minority Report', we may be well on our way. As significant advancements are being made in available processing power and deep learning, face recognition tech has taken off.

Computer technology has witnessed a number of moments of transformation. The invention of the IBM PC, the rise of the Windows Operating System and Intel processors ushered in a new era of personal computing and ensured that every average home and office had the opportunity of tapping into the vast possibilities of the Personal Computer. As the world was trying to grasp the full potentials of these amazing innovations, Sir Tim Berners-Lee ushered in the most transformative innovation in the history of mankind with his invention of the World Wide Web. The Web with its endless possibilities and immeasurable potentials, created new industries, transformed existing ones and changed the way we work, play and connect. To complete the chain of technology as we have it today, were the invention of the iPhone, the rise of Cloud Computing, IoT and the rise of Holographic Computing.