Contact centers have experienced overwhelming strain since the onset of the pandemic and for many organizations this chaotic trajectory has continued. In the travel industry, for example, airlines are currently facing record-breaking call volumes and their service agents are struggling to deal with a surge of inquiries. Delta reports call wait times of two to three hours and other major U.S. airlines have call wait times as long as 8 hours and 30 minutes. Extending superior customer experiences in these types of circumstances is challenging, if not impossible, and customer service agents are equally affected. The average customer service agent remains in their job for approximately one year, according to the U.S. Bureau of Labor Statistics.

John Merrill: I think it's important to step back a little bit, take a look at how we came to the point where we are today, because we need to understand that how this aligns with the administration and their goal related to AI. Our AI-ML strategic plan fine, obviously we're the department, DHS AI strategy, which was released back in December 3rd of 2020. And the overarching issues regarding principles associated within that document specified how S&T, the research arm of DHS, would support and address the number of challenges, many of the opportunities with the emerging AI-ML could potentially pose to the department. We're also guided by the principles set forth in the executive order 13859, which states that maintaining American leadership in artificial intelligence, and also executive order 13960, which states the promoting the use of trustworthy artificial intelligence in the federal government. The executive orders were the basis for the development of the department's AI strategy.

The co-founder of Elon Musk's brain-computer interface startup Neuralink has raised more than $47 million for a rival project, according to a report. Max Hodak, who also served as President of Neuralink until earlier this year, also appears to have poached some of his former firm's talent for the "stealth startup" Science Corp. An SEC filing from July, first spotted by Futurism, revealed that 14 investors were involved in the funding round for Science Corp, which also involves Jed McCaleb, the founder of the infamous crypto exchange MtGox. New employees of Mr Hodak's secretive new startup specialise in CRISPR gene-editing technology, according to their LinkedIn profiles, suggesting the Neuralink rival could focus more on bioengineering rather than just neural hardware in order to connect a human brain to a computer. There are currently 10 public job postings for Science Corp, all focussed on either biology or microfabrication.

On a recent afternoon in Maracaibo, Venezuela, Alexander Marinez, who has short-cropped black hair and three-to-four-day stubble, sat in front of his computer tracking herbiboars in the mushroom forests on Fossil Island. He pressed down on his glowing mouse, the newest addition to his otherwise timeworn gaming setup. The pixelated character on his computer screen followed the tracks of a hedgehoglike creature with triangular tusks and herbs growing out of its back. Outside Marinez's one-story house, the sun bore down on the dirt road. His home lies about six miles away from the strait that connects the Caribbean Sea with Lake Maracaibo, one of the world's richest sources of oil. The character inspected a tunnel. Suddenly, the herbiboar appeared, and the character attacked, stunning it.

US federal agencies are planning to expand use of facial recognition systems, according to a report by the Government Accountability Office (GAO) despite continuous backlash over the technology's application for more than a year. The report, published Tuesday, assessed the use of facial recognition systems by federal agencies, and how they plan to expand the use of the technology in the future. Eighteen of the 24 surveyed agencies, including the US Departments of Justice, Defense, Education, Housing and Urban Development, reported using facial recognition technology (FRT) for one or more purposes, the GAO report said. The survey also found that 10 of the agencies plan to broaden their use of the technology by 2023, with two of them investing in its research and development. While most of the facial recognition systems used by the federal agencies are government owned, the report says six such systems come from commercial vendors like Clearview AI, and Acuant FaceID.

NPS SE thesis students are studying other aspects of the cognitive laser concept. One study is widening the scope of the problem beyond laser weapon system decisions (Carr 2021). This study is asking the broader question: how do warfare operators on ships make the determination of which weapon to select when they have kinetic weapons and laser weapons to choose from? For this higher-level kill chain function, the operator needs to be able to compare the predicted performance of the kinetic weapon with that of the laser weapon for a given threat scenario. The threat is not stationary--as it moves, the range between the weapon and target changes and therefore the amount of "atmosphere" that the laser beam must traverse changes.

Artificial Intelligence (AI) can be a useful weapon in the fight against corruption. Its capacity to handle huge data is unrivaled, as is its ability to spot abnormalities or trends, such as in financial transaction data. Some of the ways AI is used in society have skeptics, who fear a society that is more monitored, putting privacy and individual freedom in danger. Let's get into the topic in more detail. Artificial intelligence (AI) refers to technologies that allow machines to simulate human intelligence in order to tackle complicated issues.

AI algorithms that identify maneuvers from trajectory data could play an important role in improving flight safety and pilot training. AI challenges allow diverse teams to work together to solve hard problems and are an effective tool for developing AI solutions. AI challenges are also a key driver of AI computational requirements. The Maneuver Identification Challenge hosted at maneuver-id.mit.edu provides thousands of trajectories collected from pilots practicing in flight simulators, descriptions of maneuvers, and examples of these maneuvers performed by experienced pilots. Each trajectory consists of positions, velocities, and aircraft orientations normalized to a common coordinate system. Construction of the data set required significant data architecture to transform flight simulator logs into AI ready data, which included using a supercomputer for deduplication and data conditioning. There are three proposed challenges. The first challenge is separating physically plausible (good) trajectories from unfeasible (bad) trajectories. Human labeled good and bad trajectories are provided to aid in this task. Subsequent challenges are to label trajectories with their intended maneuvers and to assess the quality of those maneuvers.

Past research has studied social determinants of attitudes toward foreign countries. Confounded by potential endogeneity biases due to unobserved factors or reverse causality, the causal impact of these factors on public opinion is usually difficult to establish. Using social media data, we leverage the suddenness of the COVID-19 pandemic to examine whether a major global event has causally changed American views of another country. We collate a database of more than 297 million posts on the social media platform Twitter about China or COVID-19 up to June 2020, and we treat tweeting about COVID-19 as a proxy for individual awareness of COVID-19. Using regression discontinuity and difference-in-difference estimation, we find that awareness of COVID-19 causes a sharp rise in anti-China attitudes. Our work has implications for understanding how self-interest affects policy preference and how Americans view migrant communities.

This is a remote position. The applicant can be anywhere in the country of the posting and must be eligible to work from there. As a Data Scientist, you will lead the charge on building our data science infrastructure and driving insights that lead to step-function improvements in how we operate. We handle millions of tasks for businesses looking to scale their ML development, and we're looking for a talented data science leader to help us understand it all in the service of building better products. In this role, you will apply statistical models, design and interpret experiments, build mission-critical dashboards, and help structure and order our data in the pursuit of transparency over how we operate and how we can improve.