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.

We think of AI as an arbiter of neutrality, but when fed biased data it churns out biased results. At the beginning of 2017, Amazon's machine learning division shuttered an artificial intelligence (AI) project it had been working on for the past three years. A team in its machine learning wing had been building computer programmes designed to review job applicants' resumes, giving them star-ratings from one to five – not unlike the way shoppers can rate products purchased from Amazon online. However, within a year of the project beginning, the company realised its system was biased against female applicants. The software was trained to vet applicants by observing patterns in resumes submitted to the company over a ten-year period, the majority of which – due to the male-dominance of the tech industry – came from men.

Artificial intelligence (AI) and intelligent technologies in general are inseparable in our daily lives and because of this broad spectrum, AI is often referred to as general purpose technology. It may take time until steering wheels and pedals are no longer necessary, but AI already plays a significant role in so many other contexts within the automotive sector. From production planning to design and development, and from logistics to sales, nearly every aspect of car manufacturing and distribution is or will be enhanced in the mid- and long-term through the use of AI. The automotive industry is facing the dawn of the second machine age. Let's take a look at how AI has changed and will change the automotive industry.

Apple has announced that it will be attending the 33rd Conference and Workshop on Neural Information Processing Systems (NeurIPS) in Vancouver, Canada from Sunday, December 8 through Saturday, December 14. In a new entry to its Machine Learning Journal, Apple said its product teams are "engaged in state of the art research in machine hearing, speech recognition, natural language processing, machine translation, text-to-speech, and artificial intelligence, improving the lives of millions of customers every day." Apple employees will be making a series of presentations at the conference. A schedule is provided in Apple's Machine Learning Journal. Machine learning algorithms play a role in virtually every Apple product and service, ranging from Apple Maps and Apple News to Siri and the QuickType keyboard on iPhone and iPad.

Daimler is testing robotaxis in the U.S. despite new CEO Ola Kallenius saying that the automaker will "rightsize" its spending level on self-driving technologies. Daimler's autonomous-driving technology will more likely be apply to commercial vehicles for freight companies on long haul routes than taxis, Kallenius told journalists at the company's investor day in London last month. The company has started robotaxi tests in California to gather user feedback, sources familiar with the matter told Automotive News Europe. "We have not put the project on ice. We are looking at where we can improve efficiency and gain synergies so we don't unnecessarily duplicate or triplicate our development work," said one of the sources.

In late September, Beijing unveiled to the world Daxing, a glimmering $11 billion airport showcasing technologies such as robots and facial recognition scanners that many other airports worldwide are either adopting or are now considering. Daxing fits the description of what experts hail as a "smart airport." Just as a smart home is where internet-connected devices control functions like security and thermostats, smart airports use cloud-based technologies to simplify and improve services. Of course, many of the nearly 4,000 scheduled service airports across the world are still embarrassingly antiquated. The good news for aviation is that more facilities are investing, finally, to better serve airlines, suppliers, and travelers. This year, airports worldwide will spend $11.8 billion -- 68 percent more than the level three years ago -- on information technology, according to an estimate published this month by SITA (Société Internationale de Telecommunications Aeronautiques, an airline-owned tech provider). A few trends are driving the rise of smart airports. Flight volumes are increasing, so airports need better ways to process flyers. Airports need better ways to make money, too, by encouraging passengers to spend more in their shops and restaurants. Data is growing in importance. Everything happening at an airport, from where passengers are flowing to which items are selling in stores, generates data. Airports can analyze this data to spot opportunities for eking out fatter profits. They can sell the data to third-parties as well.

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.

Artificial Intelligence is here to transform everything from our daily business lives. It is impacting both positively and negatively. The experts, the tech-savvy, and even the common people are fully aware by now that AI is surely going to replace humans. The questions and concerns have shifted to when and how, and which jobs will be replaced first. If we look at the current situation, we are in the middle of the AI development phase.