Estimating the conditional average treatment effects (CATE) is very important in causal inference and has a wide range of applications across many fields. In the estimation process of CATE, the unconfoundedness assumption is typically required to ensure the identifiability of the regression problems. When estimating CATE using high-dimensional data, there have been many variable selection methods and neural network approaches based on representation learning, while these methods do not provide a way to verify whether the subset of variables after dimensionality reduction or the learned representations still satisfy the unconfoundedness assumption during the estimation process, which can lead to ineffective estimates of the treatment effects. Additionally, these methods typically use data from only the treatment or control group when estimating the regression functions for each group. This paper proposes a novel neural network approach named \textbf{CrossNet} to learn a sufficient representation for the features, based on which we then estimate the CATE, where cross indicates that in estimating the regression functions, we used data from their own group as well as cross-utilized data from another group. Numerical simulations and empirical results demonstrate that our method outperforms the competitive approaches.

Computer scientist Lynne Parker made breakthroughs in getting robots to work together so they could perform difficult missions, like cleaning up after a nuclear disaster, waxing floors or pulling barnacles off a ship. Her job now is getting the U.S. government working together -- alongside American businesses, research universities and international allies -- as director of a new national initiative on artificial intelligence. She's America's first AI czar, at a time of rising promise and a heavy dose of both hype and fear about what computers can do as they think more like humans. "There's an increased need for education and training so that people know how to use AI tools, they know sort of what the capabilities are of AI so that they don't treat it as magic," Parker said in an interview with The Associated Press. A first task for Parker, who took on the role in the waning days of the Trump administration, is adapting to priorities set by the Biden administration.

In 2021, it might be simpler to ask what can't be mapped. Just as Google and social media have enabled each of us to reach into the figurative diaries and desk drawers of anyone we might be curious about, law enforcement agencies today have access to powerful new engines of data processing and association. Ogden is hardly the tip of the spear: police agencies in major cities are already using facial recognition to identify suspects--sometimes falsely--and deploying predictive policing to define patrol routes. "That's not happening here," Ogden's current police chief, Eric Young, told me. "We don't have any kind of machine intelligence."

Last week's breaking news story on The Robot Report was unfortunately the demise of Helen Greiner's company, CyPhy Works (d/b/a Aria Insights). The high-flying startup raised close to $40 million since its creation in 2008, making it the second business founded by an iRobot alum that has shuttered within five months. While it is not immediately clear why the tethered-drone company went bust, it does raise important questions about the long-term market opportunities for leashed robots. The tether concept is not exclusive to Greiner's company, there are a handful of drone companies that vie for marketshare, including: FotoKite, Elistair, and HoverFly. The primary driver towards chaining an Unmanned Ariel Vehicle (UAV) is bypassing the Federal Aviation Administration's (FAA) ban on beyond line of sight operations.

In the future, personalized AI assistants will use knowledge of our behaviors to inform us of goings-on and do chores, and as we grow older, they'll provide companionship and assistance when caregivers aren't around. These assistants will not only chart our calendars and supply answers to questions, but will help administer medical treatments, assist us in making difficult decisions, and connect us with the people we care deeply about. That's the vision the Computing Community Consortium (CCC), an organization representing over 220 North American academic departments, industrial research labs, and professional societies, articulated in a draft of its 20-year roadmap for AI research in the U.S., which was published this month. Its organizers -- who include University of Southern California director of knowledge technologies Yolanda Gil and Dr. Fei-Fei Li, a Stanford professor and formerly Google's chief AI scientist -- picture personal assistants that will fundamentally transform human lives around the world for the better. "[AI] will enable an elderly population to live longer independently, AI health coaches will provide advice for lifestyle choices, [and] customized AI tutors will broaden education opportunities," according to the report.

Women are redefining the boundaries set by age-old prejudices in almost every field. The arena of technology is no exception. The domain of technology is evolving every day owing to various entrepreneurs and inventors leading the way. In this backdrop, female entrepreneurs are making a significant contribution to the field of robotics. Women are altering the way humans will interact with robots in the future. From sophisticated drones to projecting and implementing symbiotic ideas, women are reshaping the future of the industry.

Nearly 20 years earlier, a young roboticist named Helen Greiner was lecturing at a tech company in Boston. Standing in front of the small crowd, Greiner would have been in her late 20s, with hooded eyes, blonde hair, and a faint British accent masked by a lisp. She was showing off videos of Pebbles, a bright-blue robot built out of sheet metal. For many years, the field of AI struggled with a key problem: How do you make robots for the real world? A robot that followed a script was simple; but to handle the unforeseen (say, a pothole or a fence), programmers would have to code instructions for every imaginable scenario.

After they were all seated, Tyson had the lights dimmed, and then promptly undermined why the panelists were there in the first place. Tyson played a video from Boston Dynamics showing two four-legged robots, one with a long arm that opened a door for the other. The crowd murmured and cheered as the robots overcame the obstacle. Tyson implored the audience to read the comments on the video at home later. "The first comment was'We're all going to die!' but then the second comment was'Those were polite robots!'" he said.

Helen Greiner, of US company iRobot Corp, is here promoting a carpet cleaning robot. They're small, unobstrusive, and seem happy to do a job few if any of us enjoy. Such is the appeal of iRobot Corporation's vacuum cleaner known as Roomba that the Massachusetts-based company has already sold more than a million of them in the US. Some, says iRobot chairwoman Helen Greiner, have been named. "Rosie is a highly popular (name) and so is Abby or Agnes," Ms Greiner says.

One of the world's largest package delivery companies is stepping up efforts to integrate drones into its system. UPS has partnered with robot-maker CyPhy Works to test the use of drones to make commercial deliveries to remote or difficult-to-access locations. The companies began testing the drones on Thursday, when they launched one from the seaside town of Marblehead. The drone flew on a programmed route for 3 miles over the Atlantic Ocean to deliver an inhaler at Children's Island. The successful landing was greeted by jubilant shouts from CyPhy Works and UPS employees on the island to witness the test. "I thought it was fantastic," said John Dodero, UPS vice president for industrial engineering.