Fortinet today at the Gartner Security & Risk Management Summit 2018 announced it has infused machine learning algorithms and user-behavioral analytics in its web application firewall to identify nearly 100 percent of all cyberthreats. John Maddison, senior vice president of products and solutions for Fortinet, said version 6.0 of the company's FortiWeb Web Application Firewall (WAF) software employs machine learning algorithms to identify both known and unknown threats. That latter capability is enabled by applying algorithms against the user behavior data being collected to identify anomalies indicative of a new, unknown threat being introduced into the IT environment. Historically, WAFs have relied on application learning (AL) to identify anomalies and known threats. But Maddison said that approach generates too many security alerts, which ultimately leads to a state of alert fatigue that makes it easy for cybersecurity professionals to miss or ignore critical information.

Google has released a set of principles to guide its work in artificial intelligence, making good on a promise to do so last month following controversy over its involvement in a Department of Defense drone project. The document, titled "Artificial Intelligence at Google: our principles," does not directly reference this work, but makes clear that the company will not develop AI for use in weaponry. It also outlines a number of broad guidelines for AI, touching issues like bias, privacy, and human oversight. While the new principles forbid the development of AI weaponry, they state that Google will continue to work with the military "in many other areas." Speaking to The Verge, a Google representative said that had these principles been published earlier, the company would likely not have become involved in the Pentagon's drone project, which used AI to analyze surveillance footage.

Google has created an artificial-intelligence code of ethics that prohibits the development of autonomous weapons. But the principles leave sufficient wiggle room for Google to benefit from lucrative defense deals down the line. The announcement comes in the wake of significant internal protest over the use of Google's AI technology by a Department of Defense initiative called the Algorithmic Warfare Cross-Functional Team. The goal of this venture, known internally as Project Maven, is to improve the accuracy of drone strikes, among other things. Last month a dozen Google workers quit over the scandal, and many more signed an open letter of protest.

In a new 8,000-word set of ethical principles and guidelines, Google outlined how it plans to manage--and in some cases limit--the application of artificial intelligence, a powerful and emerging set of technologies that Google views as key to its growth. Google, the primary business unit of Alphabet Inc., GOOGL -1.09% has recently come under criticism from its own employees for supplying image-recognition technology to the U.S. Department of Defense, in a partnership called Project Maven. Google told employees earlier this month it wouldn't seek to renew its contract for Project Maven, a person familiar with the matter said at the time, and that decision in turn was blasted by some who said the company shouldn't be conflicted about supporting national security. Google's artificial intelligence also recently generated public alarm after the company demonstrated a robotic voice that can trick humans into thinking it is real. Google is having to expand its definition of ethics as its technology seeps more and more into the institutions of public life, from scientific research to military intelligence.

A NASA robot has found more building blocks for life on Mars, the most complex organic matter yet from 3.5 billion-year-old rocks on the surface of the red planet, the US space agency said on Thursday. The unmanned Curiosity rover has also found increasing evidence for seasonal variations of methane on Mars, indicating the source of the gas is likely the planet itself, or possibly its subsurface water. The data, collected through drilling into the lowest point of the red planet's Gale crater, is part of the US space agency's newly widened search for organic molecules that could indicate past life on the surface of Mars. Additional data from the robotic probe confirms the detection of "seasonal patterns" in methane levels, NASA geophysicist Ashwin Vasvada said in the live-streamed announcement. NASA scientist Chris Webster confirmed that water has been found on the martian surface and has been present for "a very long time," which points strongly toward a "habitable environment".

In terms of computer applications, we will see increasing application and adoption of machine learning (ML) and artificial intelligence (AI) techniques. We already see this in shopping recommendations, games, and large social networks. Voice assistants such as Siri, Alexa, and Google Assistant use ML to perform natural language processing and classification to respond appropriately. Such techniques will make interacting with devices increasingly seamless, which will ultimately make technology easier to use while making humans more efficient in finding and managing information. Just like automation and the application of machine learning to businesses and business processes, there are many opportunities to apply similar techniques to government functions.

Google will not allow its artificial intelligence software to be used in weapons or unreasonable surveillance efforts under new standards for its business decisions in the nascent field, the Alphabet Inc. unit said Thursday. The restriction could help Google management defuse months of protest by thousands of employees against the company's work with the United States military to identify objects in drone video. Google instead will seek government contracts in areas such as cybersecurity, military recruitment and search and rescue, Chief Executive Sundar Pichai said in a blog post Thursday. "We want to be clear that while we are not developing AI for use in weapons, we will continue our work with governments and the military in many other areas," he said. Breakthroughs in the cost and performance of advanced computers have carried AI from research labs into industries such as defense and health in the last couple of years.

It seems like just about every security vendor touts some kind of AI or machine learning embedded within their products. But do you really need this technology to have an effective defense? The answer lies in looking at modern methods of attack and seeing whether legacy methods of detection can be successful. In all of these modern-day attacks, the legacy methods of detection -- especially those dependent on historical information, such as signature-based detection and heuristics -- simply won't get the job done. The beauty of machine learning for cybersecurity is right there in the name: It's always learning.

Google will reportedly not extend its controversial contract with the Pentagon for artificial intelligence (AI) work, after it prompted strong opposition in the technology giant's workforce, who feared the program could be used for lethal purposes. During a weekly meeting with employees on Friday, the chief executive of Google's cloud-computing business Diane Greene said there would be no follow-up for the Pentagon contract when it expires in March 2018, The Washington Post cited company sources as saying. Google, however, has not commented on the report and will not say whether it plans to stop working with the Pentagon altogether next year. The 18-month project known as Project Maven, was launched in April 2017 to find ways the US military could use AI to update its national security and defense capabilities "over increasingly capable adversaries and competitors," according to a defense department memo. The program involves using machine learning and engineering talent to distinguish people and objects in drone videos.

You're not the only one nervous about AI -in light of rapid AI growth and adoption, the U.S. Government recently held three Subcommittee Meetings designed to understand the implications posed by the widespread adoption of AI technology in the public and private sectors. So why is the US Government concerned about AI in society, and what role should it be considering in the private sector? Sid Mair, senior vice president of Federal Systems at Penguin Computing, weighs in. Beginning his technology career at NASA, Sid brings more than 30 years of expertise across all aspects of the federal market, including the Department of Defense, Homeland Security, civilian agencies in both classified and unclassified areas, as well the Executive and Congressional branches of government. Penguin Computing most recently built the world's largest AI cluster in the private sector.