What is new is the growing ubiquity of AI in large organizations. In fact, by the end of this year, I believe nearly every type of large organization will find AI-based cybersecurity tools indispensable. Artificial intelligence is many things to many people. One fairly neutral definition is that it's a branch of computer science that focuses on intelligent behavior, such as learning and problem solving. Now that cybersecurity AI is mainstream, it's time to stop treating AI like some kind of magic pixie dust that solves every problem and start understanding its everyday necessity in the new cybersecurity landscape.

Is 2020 the year that AI technology takes hold in SMBs? According to a study from Zix-AppRiver, the answer is yes. Nearly 9 out of 10 SMBs report they have a high interest in adopting AI this year; for businesses with more than 150 employees, the interest in AI jumps to 99%. For many, this is the logical next step in their digital transformation, adding automation to tasks from data analysis to inventory management to human resources assistance to improving cybersecurity systems. When you add new digital technologies, you also increase your chance of a cyberattack.

Is 2020 the year that AI technology takes hold in SMBs? According to a study from Zix-AppRiver, the answer is yes. Nearly 9 out of 10 SMBs report they have a high interest in adopting AI this year; for businesses with more than 150 employees, the interest in AI jumps to 99%. For many, this is the logical next step in their digital transformation, adding automation to tasks from data analysis to inventory management to human resources assistance to improving cybersecurity systems. When you add new digital technologies, you also increase your chance of a cyberattack.

Texas Republican Senator Ted Cruz weighs in on the impeachment trial as it nears the final vote. Sen. Ted Cruz, R-Texas, appeared to have some fun at the expense of Democrats, particularly House Speaker Nancy Pelosi, at the Senate impeachment trial of President Trump. In a 51-49 vote Friday, the GOP successfully blocked Democrats' efforts to add additional witnesses to the trial. It was also determined that both the House impeachment managers and Trump's defense team would make closing arguments Monday, with the Senate likely to vote Wednesday to acquit the president of charges of abuse of power and obstruction of Congress. However, during a recess, Cruz was seen talking to colleagues and making a particular hand gesture.

As facial recognition systems become increasingly accurate, more governments and law enforcement organizations are tapping them to verify people's identities, nab criminals and keep transactions secure. In recent months, France's government announced a nationwide facial recognition ID program, a UK court ruled that live facial recognition doesn't violate privacy rights and research revealed that the US Immigration and Customs Enforcement (ICE) agency and the FBI are using facial recognition to apprehend undocumented immigrants. Most of this activity is undertaken in the name of safety and security, but it is also raising major red flags among privacy advocates. They argue that the technology--which can scan and identify faces without consent in crowded streets, retail stores and sports stadiums--is predatory and invasive. Among consumers, the jury is still out.

One of the most difficult of tasks on the modern battlefield is predicting where the enemy will attack next. Although the Army has plenty of ways to find the enemy, figuring out his intentions are something else entirely. Now the U.S. Army plans to use drones, target recognition, artificial intelligence, and machine learning to tell the colonels and generals where an attack appears imminent. The Army's Aided Threat Recognition from Mobile Cooperative and Autonomous Sensors (ATR-MCAS) program aims to operate autonomous air and ground drones throughout the battle zone, keeping a continuous watch on the enemy. The drones identify the enemy weapons systems, such as tanks or infantry fighting vehicles, then pass on the sightings to the AI.

This week, DARPA shared footage of an experimental new program that uses large drones swarms to locate targets and gather situational intelligence in urban raid missions. Part of DARPA's Offensive Swarm-Enabled Tactics (OFFSET) program, the test featured a coordinated group of 250 autonomous air and ground vehicles. Those vehicles were sent into to a simulated urban environment, providing live information about sight lines, enemy positioning, environmental hazards, and general layout as part of a simulated military raid. The test was conducted at DARPA's Camp Shelby Joint Forces Training Center, a facility in Hattiesburg, Mississippi. The missions tasked the drone swarm with finding several AprilTags, a kind of QR code, that had been placed inside buildings in the training compound, which was designed to approximate a city block.

Existing simulations designed for cultural and interpersonal skill training rely on pre-defined responses with a menu option selection interface. Using a multiple-choice interface and restricting trainees' responses may limit the trainees' ability to apply the lessons in real life situations. This systems also uses a simplistic evaluation model, where trainees' selected options are marked as either correct or incorrect. This model may not capture sufficient information that could drive an adaptive feedback mechanism to improve trainees' cultural awareness. This paper describes the design of a dialogue-based simulation for cultural awareness training. The simulation, built around a disaster management scenario involving a joint coalition between the US and the Chinese armies. Trainees were able to engage in realistic dialogue with the Chinese agent. Their responses, at different points, get evaluated by different multi-label classification models. Based on training on our dataset, the models score the trainees' responses for cultural awareness in the Chinese culture. Trainees also get feedback that informs the cultural appropriateness of their responses. The result of this work showed the following; i) A feature-based evaluation model improves the design, modeling and computation of dialogue-based training simulation systems; ii) Output from current automatic speech recognition (ASR) systems gave comparable end results compared with the output from manual transcription; iii) A multi-label classification model trained as a cultural expert gave results which were comparable with scores assigned by human annotators.

Face recognition and similar technologies make it possible to identify and track people in real time, including at lawful political protests and other sensitive gatherings. Widespread use of face recognition by the government--especially to identify people secretly when they walk around in public--will fundamentally change the society in which we live. It will, for example, chill and deter people from exercising their First Amendment protected rights to speak, assemble, and associate with others. Countless studies have shown that when people think the government is watching them, they alter their behavior to try to avoid scrutiny. And this burden falls disproportionately on communities of color, immigrants, religious minorities, and other marginalized groups.

A debate on the future of artificial intelligence (AI) in Europe drew a full house at the European Parliament - with MEPs and Commission leaders keen to find the best way to regulate and make the most of AI, while protecting us against its worst aspects, too. "We want to discuss this because you have to be cautious. Some artificial intelligence is simple, low risk, no risk, but some artificial intelligence may be life or death for you," says Margrethe Vestager, the Executive Vice-President of the European Commission. "So if it is very risky we have to be cautious, and all the rest of it, just go, go, go." And AI is already go, go, going fast, revolutionising areas like voice recognition and translation.