After an almost year-long buyout process, Microsoft has completed the acquisition of Nuance, folding the latter's voice biometrics and conversational AI capabilities into its portfolio. The $19.7 billion acquisition had to pass several regulatory roadblocks since it was revealed in April 2020. The EU held up the acquisition in December 2021, after receiving permission from U.S. and Australian regulatory bodies prior. Though the EU would eventually give the green light for the deal in the same month. It is the second-largest acquisition by Microsoft, only behind the $27 billion buyout of LinkedIn in 2016.

Director of National Intelligence Avril Haines has selected Adele Merritt to serve as chief information officer for the Intelligence Community. Haines announced the news in a statement Monday. Merritt has held several positions in the intelligence community during a career spanning more than two decades. She began her career at the National Security Agency, served as principal deputy CIO for cyber at the Department of Energy, and director and acting senior director for intelligence programs on the National Security Council during the Obama administration, according to ODNI. Merritt was most recently program manager at DreamPort, a cyber innovation nonprofit created by U.S. Cyber Command.

NHS Shared Business Services (NHS SBS) has announced a procurement framework for "pioneering" AI software to diagnose strokes. Breakthroughs in medical AIs are helping to reduce patient suffering, the likelihood and/or severity of long-term complications, and even save lives across a number of ailments. Some of the benefits from medical AI breakthroughs are achieved through improved understanding leading to better treatment, while others are due to reducing the amount of time healthcare professionals have to spend on repetitive tasks. Over 100,000 people in the UK suffer from a stroke per year; with over 32,000 deaths as a result. NHS SBS sought out how AI can help tackle one of the UK's leading causes of death and disability.

The objective of this article is to introduce a fairness interpretability framework for measuring and explaining the bias in classification and regression models at the level of a distribution. In our work, we measure the model bias across sub-population distributions in the model output using the Wasserstein metric. To properly quantify the contributions of predictors, we take into account the favorability of both the model and predictors with respect to the non-protected class. The quantification is accomplished by the use of transport theory, which gives rise to the decomposition of the model bias and bias explanations to positive and negative contributions. To gain more insight into the role of favorability and allow for additivity of bias explanations, we adapt techniques from cooperative game theory.

As they explain in a study published in the journal, Entropy, Garibay and UCF PhD student Ramya Akula have built --an interpretable deep learning model using multi-head self-attention and gated recurrent units. The multi-head self-attention module aids in identifying crucial sarcastic cue-words from the input, and the recurrent units learn long-range dependencies between these cue-words to better classify the input text.--

Researchers at Texas A&M AgriLife are using artificial intelligence (AI) to set a new world record for creating algae as a dependable, economic source for biofuel that can be employed as an alternative fuel source for jet aircraft and other transportation requirements. Joshua Yuan, Ph.D., AgriLife Research scientist, professor and chair of Synthetic Biology and Renewable Products in the Texas A&M College of Agriculture and Life Sciences Department of Plant Pathology and Microbiology, is directing the study. The team's findings have been reported in the January issue of Nature Communications. Ongoing research is sponsored by the U.S. Department of Energy Fossil Energy Office. The study is also being financially supported by a gift from Dr. John '90 and Sally '92 Hood, who recently met with Yuan to talk about his biofuels research program.

The start of the Democratizing AI Newsletter which focuses in the first edition on "Artificial Intelligence a Key Exponential Technology in the Smart Technology Era" coincides with the launch of BiCstreet's "AI World Series" Live event, which kicks off both virtually and in-person (limited) from 10 March 2022, where this theme, amongst others, will be discussed in more detail over a 10-week AI World Series programme. The event is an excellent opportunity for companies, startups, governments, organisations and white collar professionals all over the world, to understand why Artificial Intelligence is critical towards strategic growth for any department or genre. See the 10 Weekly Program here: https://www.BiCstreet.com)). We live in tremendously exciting times where we already experience the disruptive and far-reaching impact of a smart technology revolution that seems to be on track to comprehensively change how we live, work, play, interact, and relate to one another.

If the fall of insects' tiny empires causes whole ecosystems to unravel, toppling previously solid certainties about the way our world functions, what then? It's easy to foresee how diminishing supplies of certain foods and crashing wildlife populations will heap cascading suffering on the poor and vulnerable, given the lopsided nature of societies, and perhaps even stoke embers of resentment and nationalism as foundational resources become scarcer. It's also reasonable to anticipate that we will reflexively grasp for a technological fix to the mess we've created. If you buy something using links in our stories, we may earn a commission. This helps support our journalism.

The average business receives 10,000 alerts every day from the various software tools it uses to monitor for intruders, malware, and other threats. Cybersecurity staff often find themselves inundated with data they need to sort through to manage their cyber defenses. Cyberattacks are increasing and affect thousands of organizations and millions of people in the U.S. alone. These challenges underscore the need for better ways to stem the tide of cyber-breaches. Artificial intelligence is particularly well suited to finding patterns in huge amounts of data.

While both navigation and manipulation are challenging topics in isolation, many tasks require the ability to both navigate and manipulate in concert. To this end, we propose a mobile manipulation system that leverages novel navigation and shape completion methods to manipulate an object with a mobile robot. Our system utilizes uncertainty in the initial estimation of a manipulation target to calculate a predicted next-best-view. Without the need of localization, the robot then uses the predicted panoramic view at the next-best-view location to navigate to the desired location, capture a second view of the object, create a new model that predicts the shape of object more accurately than a single image alone, and uses this model for grasp planning. We show that the system is highly effective for mobile manipulation tasks through simulation experiments using real world data, as well as ablations on each component of our system.