The marketing industry has experienced a surge of new technologies in the past few years. While this creates the potential for complete transformation, the marketing landscape over the past year has remained fairly steady. As 2017 begins, the question remains whether this will be the year that technology is fully embraced by the marketing community. Will it be a transitional year with common practices being adapted to reflect new technology trends or will it witness major developments that threaten to take marketers by surprise? In a world where customers are constantly demanding more, customer experience (CX) has become difficult and challenging to perfect, putting extra pressure on marketers.

Artificial Intelligence (AI) is often discussed in terms of the threat it poses, whether real (automation disrupting numerous industries) or imagined (AI taking over the human race). The AI for Good Foundation, however, is committed to helping the world through AI, and has partnered with Syngenta, an agrochemical company, to launch the Syngenta AI Challenge. Participants are required'to develop a model that could be used to help scientists analyse large amounts of seed data more efficiently and effectively'. They will be tasked to find out'which soybean varieties will perform better in farmers' fields in 2015 & 2016?'. To do this, entrants will be provided with a large range of data over a four-month period, before officially submitting their efforts by June 1 of this year.

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.

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.

If manufacturers want to sustain and grow their customer bases in a competitive environment, their products need to fulfill increasingly high quality and reliability standards. Automakers, for example, now have a target defect rate for the integrated systems of less than 1 percent. That's putting pressure on the original equipment makers (OEMs) and their suppliers who have to meet these targets at the same time that products and manufacturing processes are becoming increasingly complex and featuring numerous activities that impact quality, performance, and yield. To prevent failures of components, systems, and ultimately the product, these manufacturers need reliable methods to find defects. But quality control today is, in many cases, still performed by human inspectors, which limits its reliability and efficiency.

'The National Highway Traffic Safety Admnnistration, under the U.S. Department of Transportation, has issued its' official report on the crash of a Tesla so-called "Auto-pilot" vehicle which crashed into a big rig last summer. "Problem Description: The Automatic Emergency Braking (AEB) or Autopilot systems may not function as designed, increasing the risk of a crash."'

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.

Rapid7 is a leading provider of security data and analytics solutions that enable organizations to implement an active, analytics-driven approach to cyber security. We combine our extensive experience in security data and analytics and deep insight into attacker behaviors and techniques to make sense of the wealth of data available to organizations about their IT environments and users. Our solutions empower organizations to prevent attacks by providing visibility into vulnerabilities and to rapidly detect compromises, respond to breaches, and correct the underlying causes of attacks. Rapid7 is trusted by more than 4,150 organizations across 90 countries, including 34% of the Fortune 1000. To learn more about Rapid7 or get involved in our threat research, visit www.rapid7.com .

In this special guest feature, Cecilia Pizzurro, Senior Director, Strategic Data Projects at LOGICnow, discusses the convergence of data/machine learning and cybersecurity, and the idea that these two are playing off of each other in a more meaningful way than ever before. Cecilia leads a team of data scientists and software engineers in Cambridge (US) and Newcastle (UK). These teams use machine learning and big data analytics to find business value in the vast amount of customer data gathered from LOGICnow's products. She was also the co-founder and CTO of the The Dolomite Group, a South American mining consortium, pioneering machine learning and big data analyses to improve mining efficiency and reduce environmental impact in Peru. This company is currently finalizing its acquisition by a Chilean mining company.