Military veteran Travis Decker's remains were found in Washington wilderness, ending a three-month manhunt after he murdered his daughters Paityn, Evelyn and Olivia.

The Los Angeles Police Commission on Tuesday said it would review the city Police Department's use of facial recognition software and how it compared with programs in other major cities. The commission did so after citing reporting by The Times this week that publicly revealed the scope of the LAPD's use of facial recognition for the first time -- including that hundreds of LAPD officers have used it nearly 30,000 times since 2009. Critics say police denials of its use are part of a long pattern of deception and that transparency is essential, given potential privacy and civil rights infringements. Commission President Eileen Decker said a subcommittee of the commission would "do a deeper dive" into the technology's use and "work with the department in terms of analyzing the oversight mechanisms" for the system. "It's a good time to take a global look at this issue," Decker said.

As part of his keynote for The Manufacturer's Industrial Data Summit, Bala Amavasai, Head of AI and Lead AI Architect at Stanley Black & Decker, explored the benefits of artificial intelligence for manufacturers and some of the ways it can be implemented into businesses. Stanley Black and Decker are at the forefront of delivering digital solutions to industry and operate across manufacturing verticals, with a vision for digital transformation to bring in cutting-edge technology to solve the hardest problems. The ambition is to build connected factories across the globe using technologies including: AI and machine learning; robotics; digital apps and digital twins. Bala Amavasai Head of AI and Lead AI Architect, Stanley Black & Decker Bala explained, "Among these technologies, AI is at the centre of building connected factories; but when we speak about AI, we are not only referring to deep learning AI, in fact it is much more than deep learning. It is machine learning, statistics and all those technologies that fall within the AI domain".

As part of his keynote for The Manufacturer's Industrial Data Summit, Bala Amavasai, Head of AI and Lead AI Architect at Stanley Black & Decker, explored the benefits of artificial intelligence for manufacturers and some of the ways it can be implemented into businesses. Stanley Black and Decker are at the forefront of delivering digital solutions to industry and operate across manufacturing verticals, with a vision for digital transformation to bring in cutting-edge technology to solve the hardest problems.

However, one issue that still persists is how to avoid printing objects that don't meet expectations and thus can't be used, leading to a waste in materials and resources. Scientists at the University of Southern California's (USC's) Viterbi School of Engineering has come up with what they think is a solution to the problem with a new machine-learning-based way to ensure more accuracy when it comes to 3D-printing jobs. Researchers from the Daniel J. Epstein Department of Industrial and Systems Engineering developed a new set of algorithms and a software tool called PrintFixer that they said can improve 3D-printing accuracy by 50 percent or more. The team, led by Qiang Huang, associate professor of industrial and systems engineering and chemical engineering and materials science, hopes the technology can help make additive manufacturing processes more economical and sustainable by eliminating wasteful processes, he said. "It can actually take industry eight iterative builds to get one part correct, for various reasons," said Qiang, who led the research.

In 2017, artificial intelligence attracted $12 billion of VC investment. We are only beginning to discover the usefulness of AI applications. Amazon recently unveiled a brick-and-mortar grocery store that has successfully supplanted cashiers and checkout lines with computer vision, sensors, and deep learning. Between the investment, the press coverage, and the dramatic innovation, "AI" has become a hot buzzword. But does it even exist yet?

Climbing teams spent over two weeks laser scanning Mount Rushmore in May 2010. High atop the Thomas Jefferson Memorial in Washington, D.C., is a layer of biofilm covering the dome, darkening and discoloring it. Biofilm is "a colony of microscopic organisms that adheres to stone surfaces," according to the U.S. National Park Service, which needed to get a handle on its magnitude to get an accurate cost estimate for the work to remove it. Enter CyArk, a non-profit organization that uses three-dimensional (3D) laser scanning and photogrammetry to digitally record and archive some of the world's most significant cultural artifacts and structures. CyArk spent a week covering "every inch" of the dome, processed the data, and returned a set of engineering drawings to the Park Service "to quantify down to the square inch how much biofilm is on the monument," says CEO John Ristevski.

In 2017, artificial intelligence attracted $12 billion of VC investment. We are only beginning to discover the usefulness of AI applications. Amazon recently unveiled a brick-and-mortar grocery store that has successfully supplanted cashiers and checkout lines with computer vision, sensors, and deep learning. Between the investment, the press coverage, and the dramatic innovation, "AI" has become a hot buzzword. But does it even exist yet?

Knowledge portals provide views onto domain-specific information on the World Wide Web, thus helping their users find relevant, domain-specific information. The construction of intelligent access and the contribution of information to knowledge portals, however, remained an ad hoc task, requiring extensive manual editing and maintenance by the knowledge portal providers. To diminish these efforts, we use ontologies as a conceptual backbone for providing, accessing, and structuring information in a comprehensive approach for building and maintaining knowledge portals. We present one research study and one commercial case study that show how our approach, called seal (semantic portal), is used in practice.

Agent-based systems technology has generated lots of excitement in recent years because of its promise as a new paradigm for conceptualizing, designing, and implementing software systems. This promise is particularly attractive for creating software that operates in environments that are distributed and open, such as the internet. Currently, the great majority of agent-based systems consist of a single agent. However, as the technology matures and addresses increasingly complex applications, the need for systems that consist of multiple agents that communicate in a peer-to-peer fashion is becoming apparent. Central to the design and effective operation of such multiagent systems (MASs) are a core set of issues and research questions that have been studied over the years by the distributed AI community. In this article, I present some of the critical notions in MASs and the research work that has addressed them. I organize these notions around the concept of problem-solving coherence, which I believe is one of the most critical overall characteristics that an MAS should exhibit.