The US military is massively speeding the development of AI to reduce soldier casualties, according to Fox News on Thursday. The establishment of high-speed, multi-domain warfare by 2030, in which AI technology can take advantage of'networks' to hit multiple targets with Hellfire missiles as a means of decreasing the risk faced by soldiers in the field is a primary objective of the Army's emerging AI Task Force. Easely outlined the current difficulty of amalgamating data, explaining that today's methods have "stovepiped" sensor systems, which organise vast amounts of incoming data. AI will streamline and "fuse" disparate sources to build a "sensor fusion" throughout multiple combat platforms. The Brigadier General included Multi-Spectral sensors and Synthetic Aperture Radar (SAR) as examples of technologies that will benefit from AI-empowered data processing.

The corporate war to provide cloud computing for US warfighters is over. Late Friday, the Department of Defense announced that Microsoft has won the Joint Enterprise Defense Infrastructure contract, known as JEDI. The decision was the culmination of a two-year process that also included Google, IBM, and Oracle, and where Amazon was long seen as the favorite. JEDI, potentially worth $10 billion over 10 years, has been positioned by the Pentagon as crucial to modernizing its use of technology--and making the US military more deadly. "We must improve the speed and effectiveness with which we develop and deploy modernized technical capabilities to our women and men in uniform," DoD Chief Information Officer Dana Deasy said in a statement.

Throughout history, there have been moments when the progress of technology has taken great steps forward, when a combination of the right tools, a capacity for innovation, and sparks of ingenuity lead to breakthroughs that transform how we live our lives. How we produce and process information is critical to innovation – and our methods of recording and communicating information have themselves undergone great leaps. From the development of writing, to Gutenberg's printing press – which advanced the spread of knowledge to the masses and ushered in the enlightenment and scientific revolution – to the first programmable digital computer Colossus, the cost of reproducing and communicating information, or data, has fallen again and again. At the same time, tools for processing and making sense of large quantities of data have developed exponentially – with artificial intelligence (AI) representing the latest leap. In the same way that Gutenberg's press ushered in a new era of growth, data-driven technologies such as AI will underpin our future prosperity. There is no doubt that machine learning and AI is already improving peoples' lives, from intelligent personal assistants that can prepare us for changes in the weather, to systems that protect our money from criminals, or devices that offer medical advice from the comfort of our own home. And this is only the start; the potential of AI is undeniable. Our next challenge will be to harness this technology to transform how we diagnose diseases, manufacture goods and build our homes. Using advanced algorithmic techniques such as'deep learning', AI has the potential to solve complex problems fast, and in so doing, free up time and raise productivity. But we also need to make sure AI benefits everyone in the UK, which is why – in addition to this Sector Deal – the government is establishing a Centre for Data Ethics and Innovation to advise on the ethical use of data, including for AI. The huge global opportunity AI presents is why the Industrial Strategy white paper identified AI and data as 1 of 4 Grand Challenges – in which the UK can lead the world for years to come.

A Cleveland Clinic-backed XR medical visualization startup, MediView XR, Inc., has launched with $4.5 million in funding. The company uses the HoloLens and their custom software to help doctors visualize patient anatomy, and anchor it precisely on their body, giving the doctor, in essence, x-ray specs. The fundamental holographic visualization technology was initially developed at the Lerner Research Institute at the Cleveland Clinic to help surgeons better visualize and plan for the face transplant. Karl West led the team, using a HoloLens to create 3D holographic representations of the donor's skull and other anatomy to assess and refine their surgical plans. Jeffrey Yanof, PhD, created the software.

The corporate war to provide cloud computing for US warfighters is over. Late Friday, the Department of Defense announced that Microsoft has won the Joint Enterprise Defense Infrastructure contract, known as JEDI. The decision was the culmination of a two-year process that also included Google, IBM, and Oracle, and where Amazon was long seen as the favorite. JEDI, potentially worth $10 billion over 10 years, has been positioned by the Pentagon as crucial to modernizing its use of technology--and making the US military more deadly. "We must improve the speed and effectiveness with which we develop and deploy modernized technical capabilities to our women and men in uniform," DoD Chief Information Officer Dana Deasy said in a statement.

TOPSHOT - Irish rock band U2 singer Bono gestures at Lyon's city hall, central eastern France, on ... [ ] October 9, 2019, during the funding conference of Global Fund to Fight AIDS, Tuberculosis and Malaria. The fund has asked for $14 billion, an amount it says would help save 16 million lives, avert "234 million infections" and place the world back on track to meet the UN objective of ending the epidemics of HIV/AIDS, tuberculosis and malaria within 10 years. An FDA-cleared smart thermometer powered with artificial intelligence (AI) from Kinsa can estimate influenza-like illness across the US in real-time and predict a pattern three weeks before it's identified. To create a real-time illness-signal Kinsa aggregates tens of millions of anonymized data inputs from close to a million US households with a Kinsa thermometer and applies AI to triage illnesses based on severity, duration and contagiousness. From this data, Kinsa was able to create a real-time health map using their smart thermometer which serves as a geo-precise signal for tracking illness.

Human brain development is rapid during infancy and early childhood. Many disease processes impair this development. Therefore, brain developmental age estimation (BDAE) is essential for all diseases affecting cognitive development. Brain magnetic resonance imaging (MRI) of infants shows brain growth and morphologic patterns during childhood. Therefore, we can estimate the developmental age from brain images. However, MRI analysis is time-consuming because each scan contains millions of data points (voxels). We investigated the three-dimensional convolutional neural network (3D CNN), a deep learning algorithm, to rapidly classify neurodevelopmental age with high accuracy based on MRIs. MRIs from normal newborns were obtained from the National Institute of Mental Health (NIMH) Data Archive. Age categories of pediatric MRIs were 3 wks + 1 wk, 1 yr + 2 wks, and 3 yrs + 4 wks. We trained a BDAE method using T1, T2, and proton density (PD) images from MRI scans of 112 individuals using 3D CNN. Compared with the known age, our method has a sensitivity of 99% and specificity of 98.3%. Moreover, our 3D CNN model has better performance in neurodevelopmental age estimation than does 2D CNN.

Such 2D representations have lower dimensionality than audio waveforms and they easily fit advanced deep learning architectures mainly developed for computer visi on applications. Mel frequency cepstral coefficient (MFCC), short-time Fourier transformation (STFT), discrete wavel et transformation (DWT) are among the most pervasive 2D signal representations which essentially visualize frequ ency-magnitude distribution of a given reconstructed signal ove r time. Thus far, the best sound classification accuracy has been achieved for deep learning algorithms trained on 2D signal representations [1, 2]. However, it has been shown th at despite achieving high performance, the approaches based on 2D representations are very vulnerable against adversar ial attacks [3]. Unfortunately, this poses a strict security is sue because crafted adversarial examples not only mislead the target model toward a wrong label, but also, they are transfe r-able to other models including conventional algorithms suc h as support vector machines (SVM) [3].

Illinois continues to lead the way in privacy and security legislation. The Prairie State is home to the Biometric Information Privacy Act, first of its kind legislation regulating the collection and possession of biometric information, and also the Personal Information Protection Act, considered one of the more expansive data breach notification laws in the nation. And now, in what has been described as "the momentous legislative session in decades", the Illinois state legislature unanimously passed the Artificial Intelligence Video Interview Act ("the AIVI Act"), HB2557, which imposes consent, transparency and data destruction requirements on employers that implement AI technology during the job interview process. The AIVI Act, the first state law to regulate AI use in video interviews, will take effect January 1, 2020. Notification – The employer must notify the job applicant that AI will be used during the video interview for the purpose of analyzing the applicant's facial expressions and consider the applicant's fitness for the position.

NASA says it will put a robotic rover on the moon that can aid the agency in its search for lunar water. The four-wheeled vehicle, which NASA has dubbed the Volatiles Investigating Polar Exploration Rover, or VIPER, will be the size of a golf-cart and use various science instruments to probe the moon's surface for evidence of water and ice. VIPER is set to be delivered to the moon's surface by December 2022 and once there it will collect 100 days worth of data designed to map potential water sources. NASA's VIPER rover (rendering above) will explore the moon for water and help to guide an ongoing plan to return humans to the lunar surface A mobility'testbed' (pictured above) is was created to evaluate the rover's mobility system. It's toolkit for detecting water will include a drill able to bore beneath the surface and a spectrometer than can detect moisture.