A hierarchical Bayesian classifier is trained at pixel scale with spectral data from the CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) imagery. Its utility in detecting rare phases is demonstrated with new geologic discoveries near the Mars-2020 rover landing site. Akaganeite is found in sediments on the Jezero crater floor and in fluvial deposits at NE Syrtis. Jarosite and silica are found on the Jezero crater floor while chlorite-smectite and Al phyllosilicates are found in the Jezero crater walls. These detections point to a multi-stage, multi-chemistry history of water in Jezero crater and the surrounding region and provide new information for guiding the Mars-2020 rover's landed exploration. In particular, the akaganeite, silica, and jarosite in the floor deposits suggest either a later episode of salty, Fe-rich waters that post-date Jezero delta or groundwater alteration of portions of the Jezero sedimentary sequence.

Industry 4.0 - the fourth industrial revolution – is upon us. Artificial intelligence (AI) is forever changing the way information is used across all business lines of the Government and private sector alike. An important DoD priority is to use AI to improve maintenance activities. However, AI depends on the quality of data, so the DoD must first be able to capture data on maintenance activities that is complete, structured, and readily accessible. DoD maintenance faces growing challenges that threaten the strategic advantage the United States Military has long held in both combat and humanitarian missions.

The U.S. Army is developing data surveillance and analysis technology in Pittsburgh, though an offshoot of the controversial Department of Defense initiative Project Maven within Carnegie Mellon University's Army AI Task Force. CMU's involvement comes after the project made headlines last year when Google employees signed a petition en masse to cease work on the initiative. The project, the second undertaken by the Task Force, is seeking to develop an algorithm to analyze drone, overhead, and ground data to identify targets and objects of interest. The military does so much reconnaissance that human analysts simply can't keep up. Their image and sensor networks generate tons of data daily, which the Department of Defense says necessitates the use of artificial intelligence to do effective analysis.

PACAF's Integration Division Deputy Chief Ryan Raber revealed at the Genius Machines event on 3 September that the aim is to better and more rapidly predict a potential enemy's possible intentions. The planned mechanism will be used to improve PACAF's decision-making process and will focus on events taking place in the Pacific region, which means Russia and China could be the potential objects of study, the media outlet Defense One pointed out. PACAF itself didn't specify which countries' actions the planned system will try to predict. The system is expected to forecast a potential adversary's actions by detecting irregularities in its routines based on analysis of past and current actions. The process takes days when done by humans, but by computer with AI it can theoretically handle the result in "just minutes".

Today, every man, women and child no matter his or her origin, race, or economic circumstance can enrich their lives through educational made available through AI/ML educational learning systems. The caveat is connectivity access. Education assures equality and I believe is a better use of appropriated inequality funds rather than doling them out. I am a proponent of "teaching to fish" for the long-term. Education for all peoples in all countries with all languages will be as equally disseminated depending on the availability of connectivity and AI/ML educational systems.

A man from Cardiff, UK, says the police breached his human rights when they used facial recognition technology, but today a court ruled that the police's actions were lawful. That is, however, hardly the end of the matter. South Wales Police has been trialling automated facial recognition (AFR) technology since April 2017. Other forces around the country are trialling similar systems, including London's Metropolitan Police. Bridges may have been snapped during a pilot called AFR Locate.

There's no denying the crisis created by a sudden rise in automated phishing attacks. And while IT leaders are using AI to take security to the next level, what if this technology falls into the wrong hands- the bad guys? The dawn of the internet and advances in computing means we're able to trigger an exact solution to complex problems in diverse areas – ranging from astrophysics and biological systems to automation and precision. But at the same time, these systems are inherently vulnerable to cyber threats. In this fast-paced world where innovations come and go in the blink of the eye, cybersecurity remains top-of-mind, especially for companies dabbling with data-rich transformations such as the Internet of Things (IoT).

"When you start looking at connecting points, those intersections across the different siloed data collections and siloed departments, you might just be amazed at what you could discover." Most businesses have siloed departments that are pursuing digital transformation independently, creating "islands of innovation" throughout the enterprise. This episode discusses how to unify these efforts into a cohesive strategy to develop an intelligent enterprise. What could your business do if you had total control over your data? In NASA's case, a data transformation is what made the Hubble telescope and countless other amazing discoveries possible. Our guest this episode, Kirk Borne, was there when it happened. He began his career as an astrophysicist, combining datasets from multiple fields in unprecedented ways. Now Kirk's work is more down to earth. In this episode, he shares how businesses can "democratize data" across the enterprise. And he explains how data transparency plus intelligent analytics can lead to new efficiencies, better customer experiences, even entire new business models. "The key is this concept of the culture of experimentation, that you allow people to experiment with data." Kirk Borne is a Principal Data Scientist and Executive Advisor at Booz Allen Hamilton.

This Jan. 22, 2018, file still frame from video provided by KCBS-TV shows a Tesla Model S electric car that has crashed into a fire engine on Interstate 405 in Culver City, Calif. DETROIT – A government report says the driver of a Tesla that slammed into a firetruck near Los Angeles last year was using the car's Autopilot system when a vehicle in front of him suddenly changed lanes and he didn't have time to react. The National Transportation Safety Board said Tuesday the driver never saw the parked firetruck and didn't brake. The report raises further questions about the effectiveness of Tesla's system, which was in operation before several other crashes including two fatalities in Florida and one in Silicon Valley. Tesla warns drivers that the system is not fully autonomous and drivers must be ready to intervene.

With so many questions surrounding artificial intelligence's effect on the workplace and workforce, one wonders whether future Labor Day celebrations will take on new meaning. Employers in Illinois may face these questions sooner than others following passage of a new Illinois law that regulates the use of artificial intelligence ("AI") to analyze and evaluate job applicants' video interviews. The Artificial Intelligence Video Interview Act imposes duties of transparency, consent and data destruction on organizations using AI to evaluate interviewees for jobs that are "based in" Illinois. The measure, passed unanimously in the Illinois legislature and approved by the Governor in early August, becomes effective January 1, 2020. Applying AI-based analytics to job interviews is an increasingly common practice.