Autonomous vehicles and vehicles with automated driving functions now have their own set of motor vehicle safety standards, a U.S. federal agency ruled on Thursday. The ruling begins to provide clarity on how passenger safety should be defined in vehicles that are designed without things like driver's seats and steering wheels. The U.S. Department of Transportation's National Highway Traffic and Safety Administration (NHTSA) issued the first-of-its-kind final rule that updates the safety requirements for occupants in vehicles that don't have traditional manual controls associated with a human driver. The rule, which, among other modifications, changes terminology in the Federal Motor Vehicle Safety Standards (FMVSS) to reflect the spatial layout of automated vehicles, builds on the agency's previous efforts to ensure public safety as automation evolves. Last year, NHTSA issued an order that required AV operators and manufacturers to report crashes to the agency, and in 2020, it launched an AV testing initiative that allows states and companies to submit information about AV testing that can be viewed by the public.

Can anyone deny the very fact that robots are taking over the world in ways that surpass our imagination levels. From defence to healthcare, every sector has relied on robotics in one form or the other. Irrespective of the objective achieved, one thing is for sure – robotic inventions are changing the way we are leading our lives. Have a look at what are the top 10 robotech companies that are set to change robotics. The company boasts of a portfolio that includes various innovations for smart homes and various concepts in visualization, navigation, mobility, and artificial intelligence. Sastra robotics is an Indian robotech company that aims at delivering and creating robotics solutions to allow human-like automated functional testing of real equipment.

Recent developments in artificial intelligence (AI) and computer vision have resulted in the ability to create'fake people.' These people are either generated entirely from scratch by an AI or are made by digitally altering the appearance of actors that appear similar to them. A movement called RepresentUS recently tried to publish deep fake advertisements on several news outlets such as CNN and Fox News. The advertisements depicted Russian President Vladimir Putin and North Korean leader Kim Jong-un, both stating that Americans need to act in order to protect their democracy. The news station did not let these advertisements run and took them down shortly before being posted.

Researchers at The University of Texas at Dallas have used automated machine learning in a new way to forecast state violence in Africa, and they expect the technology to have even wider predictive applications. Dr. Vito D'Orazio, associate professor of political science in the School of Economic, Political and Policy Sciences, and his team created the dynamic forecasting model as part of a competition sponsored by the Violence Early-Warning System (ViEWS) project at Uppsala University's Department of Peace and Conflict Research. The research was subsequently published online Jan. 15 in the journal International Interactions. The ViEWS contest challenged competitors to forecast -- up to six months out -- the change in the number of fatalities in a country or region stemming from state-based violence, which is armed conflict in which at least one party is a government. Forecasts from the UT Dallas team were so accurate on the subnational level -- consisting of randomly gridded map areas that don't take countries' borders into account -- that they won that part of the competition for predictive accuracy and split the win for originality.

Consider an alternative history for the war in Ukraine. Intrepid Ukrainian Army units mount an effort to pick off Russian supply convoys. But rather than rely on sporadic air cover, the Russian convoys travel under a blanket of cheap drones. The armed drones carry relatively simple artificial intelligence (AI) that can identify human forms and target them with missiles. The tactic claims many innocent civilians, as the drones kill nearly anyone close enough to the convoys to threaten them with anti-tank weapons.

Most representative decision tree ensemble methods have been used to examine the variable importance of Treasury term spreads to predict US economic recessions with a balance of generating rules for US economic recession detection. A strategy is proposed for training the classifiers with Treasury term spreads data and the results are compared in order to select the best model for interpretability. We also discuss the use of SHapley Additive exPlanations (SHAP) framework to understand US recession forecasts by analyzing feature importance. Consistently with the existing literature we find the most relevant Treasury term spreads for predicting US economic recession and a methodology for detecting relevant rules for economic recession detection. In this case, the most relevant term spread found is 3 month to 6 month, which is proposed to be monitored by economic authorities. Finally, the methodology detected rules with high lift on predicting economic recession that can be used by these entities for this propose. This latter result stands in contrast to a growing body of literature demonstrating that machine learning methods are useful for interpretation comparing many alternative algorithms and we discuss the interpretation for our result and propose further research lines aligned with this work.

Cybersecurity has always been a never-ending race, but the rate of change is accelerating. Companies are continuing to invest in technology to run their businesses. Now, they are layering more systems into their IT networks to support remote work, enhance the customer experience, and generate value, all of which creates potential new vulnerabilities. This article is a collaborative effort by Jim Boehm, Dennis Dias, Charlie Lewis, Kathleen Li, and Daniel Wallance, representing views from McKinsey's Risk & Resilience Practice. At the same time, adversaries--no longer limited to individual actors--include highly sophisticated organizations that leverage integrated tools and capabilities with artificial intelligence and machine learning. The scope of the threat is growing, and no organization is immune.

Since the start of Russia's invasion of Ukraine, more than 2.5 million people have fled the country, making it Europe's worst refugee crisis since World War II. In trying to find shelter in neighboring countries like Romania, some Ukrainian refugees have turned to an unexpected place for help: Tinder. The New York Times recounts the tale of one such individual, Anastasia Tischchenko. She and her friend Natalia Masechko posted their plight to the dating app when they fled their home of Ivano-Frankivsk, a city of approximately 230,000 located in western Ukraine, south of Lviv. "I'm thinking there are a lot of honest people in the world, and some of them are on Tinder," Tischchenko told The Times.

Women's day and Women's History Month are especially meaningful to me as a proud father of a daughter. I want my daughter to understand how wonderful and invaluable she is, not only to me and her mother, but also to everyone else in the world. Second, I want her to be exposed to amazing women who are accomplishing great things on a daily basis. I live, work and breathe AI and Technology. Through my work and research, I have encountered the work of countless amazing women in this sector.

Artificial intelligence (AI) and its subsectors like machine learning are set to transform the way we do business. Some companies are already leveraging these advanced technologies to carry out complex tasks instantaneously, removing the need for countless hours of human input. AI offers predictive capabilities unlike any tools we've seen in the past, helping organizations anticipate critical failures in their equipment, software, and overall processes. The AI industry had an estimated addressable market of $93 billion in 2021, but that's expected to soar tenfold to $997 billion annually by 2028. These five stocks can help you ride that explosive AI industry growth and turn it into stock price growth. C3.ai ( AI -9.82%) is a first-of-its-kind enterprise AI company.