AI.Reverie, company specializing in synthetic data for improved artificial intelligence (AI), announced that it has won a $1.5 million Phase 2 Small Business Innovation Research (SBIR) contract by AFWERX to build AI algorithms and improve navigation capabilities for the U.S. Air Force. According to the company, AI.Reverie will be supporting the 7th Bomb Wing at Dyess Air Force Base through their Rapid Capabilities office by leveraging synthetic data to train and improve the accuracy of vision algorithms for navigation. The use of synthetic data, or computer-generated images, aims to solve the resource barriers associated with real data: the high cost and slow turnaround of hand-labeled photos stalls deployment of vision algorithms needed to save lives. AI.Reverie's Phase 2 SBIR contract closely follows its co-publication with the IQT Lab CosmiQ Works of a paper highlighting the value of synthetic data to train computer vision algorithms. The research partners also released RarePlanes, the largest open dataset of real and synthetic overhead imagery for academic and commercial use.

As social media is increasingly being used as people's primary source for news online, there is a rising threat from the spread of malign and false information. With an absence of human editors in news feeds and a growth of artificial online activity, it has become easier for various actors to manipulate the news that people consume. Finding an effective way to detect malign information online is an important part of addressing this issue. RAND Europe was commissioned by the UK Ministry of Defence's (MOD) Defence and Security Accelerator (DASA) to develop a method for detecting the malign use of information online. The study was contracted as part of DASA's efforts to help the UK MOD develop its behavioural analytics capability.

These being pandemic times, a recent visit to the Silicon Valley offices of drone startup Skydio involved slipping past dumpsters into the deserted yard behind the company's loading dock. Moments later, a black quadcopter eased out of the large open door sounding like a large and determined wasp. Skydio is best known for its "selfie drones," which use onboard artificial intelligence to automatically follow and film a person, whether they're running through a forest or backcountry skiing. The most recent model, released last fall, costs $999. The larger and more severe-looking machine that greeted WIRED has similar autonomous flying skills but aims to expand the startup's technology beyond selfies into business and government work, including the military.

Robotic process automation startup UiPath today announced it has closed a $225 million funding round, bringing its total raised to over $1.2 billion. While the new round is roughly half the $568 million UiPath raised last April, it catapults the New York-based company's post-money valuation to $10.2 billion, up from $7 billion in 2019 and $3 billion in 2018. CEO Daniel Dines says the funding will be used to scale UiPath's platform and deepen its investments in "AI-powered innovation" as it expands its cloud software-as-a-service (SaaS) offerings. The round will also likely lay the groundwork for future strategic deals, following UiPath's acquisition of startups StepShot and ProcessGold last October. RPA -- technology that automates monotonous, repetitive chores traditionally performed by human workers -- is big business.

AI is increasingly being put to use in the technology stacks of cybersecurity companies, but not at the expense of human experts who guide the rollout and work alongside the smart tools. Before 2019, one in five cybersecurity software and service providers were employing AI, according to a study last year by Capgemini Research Institute, in a review of recent research published in DarkReading. Adoption was found to be "poised to skyrocket" by the end of 2020, with 63% of the firms planning to deploy AI in their solutions. Planned use in IT operations and the Internet of Things are predicted to see the most uptick. Increased adoption of AI does not mean that security professionals on IT staffs are ready to hand off their responsibilities.

People want increased regulation and more accountability in the field of artificial intelligence (AI), new research by Fountech.ai The AI firm commissioned an independent survey among 2,000 UK adults to uncover their attitudes towards the current state of AI development. It found that the majority (64%) want to see more regulation introduced so that the technology is safer to use and does not pose threats to society. Those aged over 55 appear more sceptical of AI, with almost three quarters (73%) keen to see additional guidelines introduced to improve safety standards. This is in comparison to just over half (53%) of those aged between 18 and 34 who held this view.

Researchers at NASA have been hard at work on a pilot AI system intended to help future exploration missions find evidence of life on other planets in our solar system. Machine learning algorithms will help exploration devices analyze soil samples on Mars and return the most relevant data to NASA. The pilot program is currently slated for a test run during the ExoMars mission that will see its launch in mid-2022. As IEEE Spectrum reports, the decision to use machine learning and artificial intelligence to aid the search for life on other planets was driven largely by Erice Lyness, the head of the Goddard Planetary Environments Lab at NASA. Lyness needed to come up with ways of automating aspects of geochemical analyses of samples taken in other parts of our solar system.

AI has become the buzzword of the world, and an integral part of almost every company's digital transformation agenda. AI users have become producers of AI tools and services. Corporate leaders and even the White House have come with forward with a directive on promotion, promulgation, and advancement of artificial intelligence. On February 11, 2019, President Trump signed Executive Order 13859 announcing the American AI Initiative. Executive Order 13859 is the United States' national strategy on artificial intelligence.

Testing for pathogens is a critical component of maintaining public health and safety. Having a method to rapidly and reliably test for harmful germs is essential for diagnosing diseases, maintaining clean drinking water, regulating food safety, conducting scientific research, and other important functions of modern society. In recent research, scientists from University of California, Los Angeles (UCLA), have demonstrated that artificial intelligence (AI) can detect harmful bacteria from a water sample up to 12 hours faster than the current gold-standard Environmental Protection Agency (EPA) methods. In a new study published yesterday in Light: Science and Applications, the researchers created a time-lapse imaging platform that uses two separate deep neural networks (DNNs) for the detection and classification of bacteria. The team tested the high-throughput bacterial colony growth detection and classification system using water suspensions with added coliform bacteria of E. coli (including chlorine-stressed E. coli), K. pneumoniae and K. aerogenes, grown on chromogenic agar as the culture medium.

Researchers from Google's DeepMind and the University of Oxford recommend that AI practitioners draw on decolonial theory to reform the industry, put ethical principles into practice, and avoid further algorithmic exploitation or oppression. The researchers detailed how to build AI systems while critically examining colonialism and colonial forms of AI already in use in a preprint paper released Thursday. The paper was coauthored by DeepMind research scientists William Isaac and Shakir Mohammed and Marie-Therese Png, an Oxford doctoral student and DeepMind Ethics and Society intern who previously provided tech advice to the United Nations Secretary General's High-level Panel on Digital Cooperation. The researchers posit that power is at the heart of ethics debates and that conversations about power are incomplete if they do not include historical context and recognize the structural legacy of colonialism that continues to inform power dynamics today. They further argue that inequities like racial capitalism, class inequality, and heteronormative patriarchy have roots in colonialism and that we need to recognize these power dynamics when designing AI systems to avoid perpetuating such harms.