Artificial intelligence is the next big military advantage. For example, in early 2019, the U.S. announced a strategy for harnessing AI in many parts of the military including. Intelligence analysis, decision-making, vehicle autonomy, logistics, and weaponry, reports Technology Review. In fact, according to the U.S. Army, "The AI market was more than $21 billion in 2018, and it is expected to grow almost nine times larger by 2025. AI systems provide predictive analysis to interpret human inputs, determine what we most likely want, and then provide us with highly relevant information."

But also: 'AI will deepen my research and bring it a step further than it is now.' There is a wide range of opinions. Nevertheless, four out of five Dutch scientists foresee that AI will have a considerable impact on society. Two thirds also believe that AI will have a radical impact on science. The figures come from a survey that the editorial board of Research commissioned among researchers in various disciplines at Dutch knowledge institutions.

As economies begin to re-open post-COVID-19, data will be essential to understanding changed human movement patterns and business opportunities in the "new normal." Starting today, Gravy Analytics becomes the exclusive foot traffic data provider to the Nitrogen.ai Now, data scientists can use Nitrogen.ai The result is faster and more predictive insights about where people are going in the physical world and how that intersects with other economic and demographic data models. Gravy Visitations data, the company's foundational data product, has provided 17,000 different features capturing visits to an array of brands and place categories, as well as visits per 10,000 people at the zip code geography level.

WASHINGTON (The Borowitz Report)--Accusing it of treating him "very unfairly," Donald Trump lashed out on Wednesday at the widely used spelling tool spell-check. "Almost every time I type a word, spell-check puts a red squiggly line under it," he tweeted. "It never put a red squiggly line under Obama's words." "Spell-check is rigged against conservatives," he charged. Trump accused spell-check of infringing on his First Amendment rights by interfering with what he called "freedom of spelling."

With Dark Matter founder Faisal Abdulaziz Al Bannai appointed as its Secretary General, the ATRC will be responsible for setting the technological priorities and driving R&D, reporting to the Abu Dhabi Executive Council.

Air power has played an increasingly important role in the Libyan conflict. The relatively flat featureless desert terrain of the north and coast means that ground units are easily spotted, with few places to hide. The air forces of both the United Nations-recognised Government of National Accord (GNA) and eastern-based commander Khalifa Haftar and his self-styled Libyan National Army (LNA) use French and Soviet-era fighter jets, antiquated and poorly maintained. While manned fighter aircraft have been used, for the most part the air war has been fought by unmanned aerial vehicles (UAVs) or drones. With nearly 1,000 air strikes conducted by UAVs, UN Special Representative to Libya Ghassan Salame called the conflict "the largest drone war in the world".

NASA has shared new details about the sensors used on the Perseverance rover as it travels the surface of Mars in search for signs of past microbial life. The instruments, a high powered camera and an ultraviolet laser, will work in tandem to take readings of the soil to help determine its chemical and mineral makeup. The main instrument, called SHERLOC (or Scanning Habitable Environments with Raman & Luminescence for Organics & Chemicals), will be mounted on the end of one of the rover's robotic arms. NASA's Persevernce rover will travel across Mars using an ultraviolet laser to determine what minerals and compounds are present in the soil, based on the way the light scatters SHERLOC will emit a quarter-sized ultraviolet laser at the ground, and scientists will measure the way the light scatters when it hits the ground to infer what kind of minerals and chemical compounds it's made of. The technique will also be used to identify the unique spectral'fingerprint' that certain organic material might give off in the hopes of tracking down potential signs of past life.

A group of bipartisan, bicameral politicians have drafted a bill that would "dramatically" increase investment in tech research and development. The Endless Frontiers Act would commit $100 billion over five years toward research in artificial intelligence, high-performance computing, robotics, automation and more. Another $10 billion would go towards creating regional technology hubs across the US. Senate Democractic Leader Chuck Schumer, Senator Todd Young and Congressmen Ro Khanna and Mike Gallagher unveiled the legislation today. They say it's partly in response to the coronavirus, which they claim "magnified weakness from decades of US underinvestment in scientific research," and competition from countries like China.

Deep learning (DL) has been applied extensively in a wide range of fields. However, it has been shown that DL models are susceptible to a certain kinds of perturbations called \emph{adversarial attacks}. To fully unlock the power of DL in critical fields such as financial trading, it is necessary to address such issues. In this paper, we present a method of constructing perturbed examples and use these examples to boost the robustness of the model. Our algorithm increases the stability of DL models for candlestick classification with respect to perturbations in the input data.

New crisis response and management approaches that incorporate the latest information technologies are essential in all phases of emergency preparedness and response, including the planning, response, recovery, and assessment phases. Accurate and timely information is as crucial as is rapid and coherent coordination among the responding organizations. We are working towards a multi-pronged emergency response tool that provide stakeholders timely access to comprehensive, relevant, and reliable information. The faster emergency personnel are able to analyze, disseminate and act on key information, the more effective and timelier their response will be and the greater the benefit to affected populations. Our tool consists of encoding multiple layers of open source geospatial data including flood risk location, road network strength, inundation maps that proxy inland flooding and computer vision semantic segmentation for estimating flooded areas and damaged infrastructure. These data layers are combined and used as input data for machine learning algorithms such as finding the best evacuation routes before, during and after an emergency or providing a list of available lodging for first responders in an impacted area for first. Even though our system could be used in a number of use cases where people are forced from one location to another, we demonstrate the feasibility of our system for the use case of Hurricane Florence in Lumberton, a town of 21,000 inhabitants that is 79 miles northwest of Wilmington, North Carolina.