Even though security solutions are becoming modern and robust, cyber threats are ever-evolving and always on the peak. The main reason for this is because the conventional methods to detect the malware are falling apart. Cybercriminals are regularly coming up with smarter ways to bypass the security programs and infect the network and systems with different kinds of malware. The thing is, currently, most antimalware or antivirus programs use the signature-based detection technique to catch the threats, which is ineffective in detecting the new threats. This is where Artificial Intelligence can come to rescue.

Corruption has again been exposed at Los Angeles City Hall, with one council member under indictment in a development scandal and another having pleaded guilty to his part in it. The transgressions highlight the real-world consequences of failing to modernize outdated planning codes and leaving decision-making power over development projects in the hands of City Council members. To try to prevent future corruption, the city needs to fix what's broken about L.A. planning -- by fully updating planning and zoning laws according to the recommendations of an outside commission, not the council. Some City Council members have proposed incremental reforms in reaction to the indictment of council member Jose Huizar, who has been charged with a running a "pay-to-play" scheme to shake down real estate developers for cash bribes and campaign donations in exchange for his help getting high-rise development projects approved. Former council member Mitch Englander pleaded guilty to falsifying material facts related to the scheme.

While zero-trust cybersecurity architectures are in trend, everyone in federal IT security seems to be holding onto it. What underpins the move to zero-trust is automation. Experts, including inside and outside the government are addressing for accelerated adoption of cybersecurity automation. Automation tools can identify if a user is accessing a network or a piece of data, and also can automate response sending alerts to analysts. This could save time and money of an agency and allow cybersecurity analysts to focus on analysing data and come up with new security strategies.

Pasadena, CA – Sometime between March 2010 and May 2012, a meteor streaked across the Martian sky and broke into pieces, slamming into the planet's surface. The resulting craters were relatively small – just 13 feet (4 meters) in diameter. The smaller the features, the more difficult they are to spot using Mars orbiters. But in this case – and for the first time – scientists spotted them with a little extra help: artificial intelligence (AI). It's a milestone for planetary scientists and AI researchers at NASA's Jet Propulsion Laboratory in Southern California, who worked together to develop the machine-learning tool that helped make the discovery.

The government is running artificial intelligence (AI)-based pilot projects in six Union territories in the field of health care, and such projects in education, agriculture, social justice, criminal justice as well as investigation are also being worked out, Electronics and IT Secretary Ajay Sawhney said on Tuesday. McKinsey Head (Global Analytics) Noshir Kaka said the development in the field of AI in India can add around USD 500 billion to the economy over the next four-and-a-half years based on Prime Minister Narendra Modi's aspiration to make the country a USD 5-trillion economy. Speaking at the RAISE 2020 summit, Sawhney said AI is moving towards being an ecosystem that includes the database, authorised service provider, authorised service agency and authorised registrar, among others. "We are trying to move forward to make this happen in all the important domains in the economy, starting with health care. It's not just announced but being rolled out in pilot phase in six Union territories," Sawhney said.

The TRW Defense Systems Group develops large man-machine networks that solve problems for government agencies. Until a few years ago these networks were either tightly-coupled humans loosely supported by machines -- like our ballistic missile system engineering organization, which provides technical advice to the Air Force, or tightly-coupled machines loosely controlled by humans- like the ground station for the NASA Tracking and Data Relay Satellite System. Because we have been producing first-of- a kind systems like these since the early 1950s, we consider ourselves leaders in the social art of assembling effective teams of diverse experts, and in the engineering art of conceiving and developing networks of interacting machines. But in the mid-1970s we began building systems in which humans and machines must be tightly coupled to each other-systems like the Sensor Data Fusion Center. Then we found that our well-worked system development techniques did not completely apply, and that our system engineering handbook needed a new chapter on communication between people and machines.

Limited fielding began in 1994 to select U.S. Army National Guard units and complete fielding to all M1 Abrams tank maintenance units started in 1997 and will finish by the end of 1998. The Army estimates that TED will save roughly $10 million a year through improved diagnostic accuracy and reduced waste. The development and fielding of the TED program represents the Army's first successful fielded maintenance system in the area of AI. Several reasons can be given for the success of the TED program: an appropriate domain with proper scope, a close relationship with the expert, extensive user involvement, and others that are discussed in this article.

The RoboCup Rescue Physical Agent League Competition was held in the summer of 2001 in conjunction with the AAAI Mobile Robot Competition Urban Search and Rescue event, eerily preceding the September 11 World Trade Center (WTC) disaster. Four teams responded to the WTC disaster through the auspices of the Center for Robot-Assisted Search and Rescue (CRASAR), directed by John Blitch. The four teams were Foster- Miller and iRobot (both robot manufacturers from the Boston area), the United States Navy's Space Warfare Center (SPAWAR) group from San Diego, and the University of South Florida (USF). Blitch, through his position as program manager for the Defense Advanced Research Projects Agency (DARPA) Tactical Mobile Robots Program, was a supporter of the competition; he also served as a member of the rules committee and a judge. USF participated by chairing the rules committee, judging, assisting with the logistics, providing commentary, and demonstrating tethered and wireless robots whenever entrants had to skip around during the competition.

The Electrical Systems Division at the NASA Kennedy Space Center has developed and deployed an agent-based tool to monitor the space shuttle's ground processing telemetry stream. The agent provides autonomous monitoring of the telemetry stream and automatically alerts system engineers when predefined criteria have been met. Efficiency and safety are improved through increased automation. Sandia National Labs' Java Expert System Shell is employed as the rule engine. The shell's predicate logic lends itself well to capturing the heuristics and specifying the engineering rules of this spaceport domain.

This article is my personal account on the work at Stanford on Stanley, the winning robot in the DARPA Grand Challenge. Between July 2004 and October 2005, my then-postdoc Michael Montemerlo and I led a team of students, engineers, and professionals with the single vision of claiming one of the most prestigious trophies in the field of robotics: the DARPA Grand Challenge (DARPA 2004). The Grand Challenge, organized by the U.S. government, was unprecedented in the nation's history. It was the first time that the U.S. Congress had appropriated a cash price for advancing technological innovation. My team won this prize, competing with some 194 other teams.