CAPE CANAVERAL, FLORIDA – SpaceX launched a 3-ton shipment to the International Space Station on Thursday, including "mighty mice" for a muscle study, a robot sensitive to astronauts' emotions and a miniature version of a brewery's malt house. The Dragon capsule also is delivering holiday goodies for the six station residents. NASA's Kenny Todd isn't giving any hints, but said, "Santa's sleigh, I think, is certified for the vacuum of space." The recycled capsule should arrive Sunday. The Falcon rocket blasted off from Cape Canaveral a day late because of high winds.

But new estimates from the Center for Security and Emerging Technology (CSET) show that China is likely spending far less on AI than previously assumed. Additionally, most of its AI money seems to be going to non-military-related research, such as fundamental algorithm development, robotics research, and smart-infrastructure development. By contrast, the US's planned spending for fiscal year 2020 allocates the majority of its AI budget to defense, which means it will likely outspend China in that category. In other words, the numbers directly oppose the prevailing narrative.

NASA has captured an incredible close-up shot of plumes of dust and rocks erupting from the surface of near-Earth asteroid Bennu as it spins through the solar system. Researchers from the University of Arizona have been studying the images taken by the navigation camera on the OSIRIS-REx spacecraft. The high-resolution images were taken as part of a NASA mission to bring samples of the asteroid - that is about 300,000miles away - back to Earth for scientists to study. These images offer a detailed look at small-scale rock and particle loss from an active asteroid for the first time, say researchers. Previous studies have been limited to only the largest ejections seen from Earth. More than 20,000 known near-Earth asteroids are travelling around the solar system at any given time according to NASA.

SpaceX successfully launched the'Dragon' capsule on top of its Falcon 9 rocket from Cape Canaveral Air Force Station, Florida for its 19th commercial resupply mission to the International Space Station. The craft took off at 12:29 PM Thursday carrying a 5,700-pound payload that includes genetically-edited'mighty-mice' and Budweiser barley seeds. The Dragon safely deployed from the rocket and is coasting towards the International Space Station– it will reach the craft in three days and spend a total of 30 before returning to Earth with other research and cargo. The mission had been scheduled to launch yesterday, but rough winds detected in the upper atmosphere forced a one-day delay for safety reasons. However, it was a beautiful day in Cape Canaveral with low wind speeds, allowing SpaceX to give the launch another go.

As use of artificial intelligence and machine learning (AI/ML) in medicine continues to grow, regulators face a fundamental problem: After evaluating a medical AI/ML technology and deeming it safe and effective, should the regulator limit its authorization to market only the version of the algorithm that was submitted, or permit marketing of an algorithm that can learn and adapt to new conditions? For drugs and ordinary medical devices, this problem typically does not arise. But it is this capability to continuously evolve that underlies much of the potential benefit of AI/ML. We address this "update problem" and the treatment of "locked" versus "adaptive" algorithms by building on two proposals suggested earlier this year by one prominent regulatory body, the U.S. Food and Drug Administration (FDA) (1, 2), which may play an influential role in how other countries shape their associated regulatory architecture. The emphasis of regulators needs to be on whether AI/ML is overall reliable as applied to new data and on treating similar patients similarly. We describe several features that are specific to and ubiquitous in AI/ML systems and are closely tied to their reliability.

Do you trust Amazon with your life? You might have to, because the big tech companies of Silicon Valley are looking to do for medicine what they've already done for retail, publishing, finance and other sectors of modern life: they want to bring on another digital revolution. Ever since the Federal government began encouraging health care providers to adopt electronic health records a decade ago, Apple, Google and a slew of Silicon Valley startups have sought to bring about their own vision of telemedicine--turbocharged by data from wearable health-monitoring devices, artificial intelligence and smartphone apps. Apple's bio-monitoring watches and Fitbit, the wearable exercise monitor recently bought by Google, are two prominent examples of products in the market now. Other companies are readying artificial-intelligence products that could augment or replace advice from medical professionals. So far all these promising technologies have failed to bring about the kind of sweeping change that Silicon Valley has wrought in so many other industries.

The guide traces the significance of activity for Australia to catch the advantages of AI, which is evaluated to be worth AU$ 22.17 trillion to the worldwide economy by 2030. The guide is proposed to help control future interest in AI and AI and goes with Artificial Intelligence: Australia's Ethics Framework, an exchange paper arranged by CSIRO's Data61 and distributed by the Australian Government in April 2019. Dr. Stefan Hajkowicz, the senior research researcher at CSIRO's Data61 and lead creator of the guide, disclosed that the way into Australia's AI-empowered future is through mechanical specialization.CSIRO's Chief Executive, Dr. Larry Marshall, shared how AI quickened the pace and size of settling the best difficulties through inventive science and innovation. Man-made intelligence speaks to a noteworthy chance to convey social, natural, and financial advantages. It can help profitability through its solid potential to empower the industry to improve items, convey better administrations, quicker, less expensive, and more secure. It uses the skill of CSIRO's information science and computerized arm, Data61.

Genetically-edited'mighty mice' are being sent up to the International Space Station today as experts investigate how to limit muscle and bone loss in low gravity. Tweaked to have enhanced muscle growth, the ripped rodents will ride on-board a ship being launched by Elon Musk's rocket company, SpaceX. The mission had been scheduled to launch yesterday, but rough winds detected in the upper atmosphere forced a one-day delay for safety reasons. Lift-off of the Falcon 9 rocket is now expected to take place at 12:29 EST (19:29 GMT) from NASA's Kennedy Space Center in Florida. It's'Dragon' capsule will go on to dock with the space station on Sunday.

The following keynote speakers have been confirmed for IEEE GLOBECOM 2019. Abstract: We are well into the "Internet of Things" era for the Internet. Billions of devices are expected and it is not uncommon to find a dozen or even a score of Internet-enabled devices in residences and offices around the world. These systems run on software - some of which has not been well tested for safety and security. We need to introduce and promote an ethic of software safety and extended maintenance to protect the users of these devices.

Description Job Description: The Leidos Innovations Center (LInC) seeks a Machine Learning Research Engineer primarily focused on cognitive signal processing, to work in our Arlington, VA office. The candidate will research & develop new, state-of-the-art machine learning algorithms and implement them across the RF domain (e.g., communications, radar, electronic warfare, spectrum sensing, and signals intelligence [SIGINT]), in both modelling and simulation environments and real time software embed systems. The candidate will also contribute to technology developments in signal processing, optimization, detection & estimation, deep learning, and adaptive decision and control. Requires basic knowledge of and ability to apply machine learning and radar/signal processing principles, theories, and concepts in support of direct programs, IR&D, and marketing efforts. Primary Responsibilities Designs and develops methods, algorithms, and systems that apply machine learning technologies to support advanced signal processing concepts.