DENVER – In this post-impeachment era of divisiveness and deadlock in the nation's capital, Uncle Sam has a message for top U.S. technologists: A Washington-based nerd strike force called the U.S. Digital Service is seeking private-sector coders, programmers and software engineers to make government user-friendly for a tech-savvy U.S. public. Launched after the 2013 crash of the Obama administration's Healthcare.gov website, the USDS recruits the nation's top tech talent for Peace Corps-style tours of duty to tackle the government's most pressing information management and online security problems. It has an increasingly rare distinction as an initiative supported by both the Obama and Trump administrations, according to current and former USDS staff and White House officials. "We've been enthusiastic about USDS since Day One," said Mathew Lira, a special assistant to Trump in the White House Office of American Innovation. Early USDS projects -- fixing the public-facing website of Obama's Affordable Care Act, helping green card holders apply for renewals electronically -- might not be top Trump administration priorities today.
One of the best performers on the ASX on Monday was the BrainChip Holdings Ltd (ASX: BRN) share price. The artificial intelligence company's shares rocketed 25% higher to 6.9 cents at one stage before closing the day 14.5% higher. Investors were buying the company's shares after it announced the receipt of an EAR99 classification for its Akida Neuromorphic System-on-Chip (NSoC), Akida Software Development Environment (ADE), and related technologies from the U.S. Government. The Export Administration Regulations (EAR) classification of EAR99, which BrainChip has now formally received, removes the barriers for exporting Akida to non-U.S. The EAR99 designation means the company does not require a pre-approval, or a license from the U.S. Department of Commerce, before delivering its solutions globally as part of sales and market expansion activities.
The world never changes quite the way you expect. But at The Verge, we've had a front-row seat while technology has permeated every aspect of our lives over the past decade. Some of the resulting moments -- and gadgets -- arguably defined the decade and the world we live in now. But others we ate up with popcorn in hand, marveling at just how incredibly hard they flopped. This is the decade we learned that crowdfunded gadgets can be utter disasters, even if they don't outright steal your hard-earned cash. It's the decade of wearables, tablets, drones and burning batteries, and of ridiculous valuations for companies that were really good at hiding how little they actually had to offer. Here are 84 things that died hard, often hilariously, to bring us where we are today. Everyone was confused by Google's Nexus Q when it debuted in 2012, including The Verge -- which is probably why the bowling ball of a media streamer crashed and burned before it even came to market.
Dave Aitel is the founder and CTO of Immunity. You can follow him @daveaitel. Export control on AI and machine learning algorithms is becoming a more important part of national security strategy as the world moves to a great-power competition landscape and technological changes force accommodation and rapid change to many national interests. However, like security software before it, AI presents unique challenges to how export control has traditionally worked, and these should be considered before being codified into international regulatory frameworks. As an example, on January 6, 2020, The Bureau of Industry and Security (BIS) in the U.S. Department of Commerce released the following rule, which imposed a license requirement on a particular kind of software useful for automatically identifying objects from drone or other imagery: "Geospatial imagery "software" "specially designed" for training a Deep Convolutional Neural Network to automate the analysis of geospatial imagery and point clouds, and having all of the following: Technical Note: A point cloud is a collection of data points defined by a given coordinate system. A point cloud is also known as a digital surface model."
This study demonstrates that it is possible to generate a highly accurate model to predict inpatient and emergency department utilization using data on socioeconomic determinants of care. ABSTRACT Objectives: To determine if it is possible to risk-stratify avoidable utilization without clinical data and with limited patient-level data. Study Design: The aim of this study was to demonstrate the influences of socioeconomic determinants of health (SDH) with regard to avoidable patient-level healthcare utilization. The study investigated the ability of machine learning models to predict risk using only publicly available and purchasable SDH data. A total of 138,115 patients were analyzed from a deidentified database representing 3 health systems in the United States.
The General Services Administration expects that its new partnership with the Pentagon's Joint Artificial Intelligence Center will ultimately lead to significant benefits for civilian agencies. The GSA is working with JAIC, which was established last year to speed up AI adoption across the Pentagon, to accelerate the center's process by adding AI into acquisition work, which GSA officials said they hope to turn around and offer civilian government. "We're able to utilize a lot of that educational material [and] best practices that they're getting and scale it up, standardize it in a sense so it can be spread among civilian agencies," said Omid Ghaffari-Tabrizi, acquisition lead at the GSA Centers of Excellence, speaking Dec. 5 at the GovernmentCIO AI and RPA in Government conference. "All of the AI that we're procuring for them, we're also hoping to procure for ourselves," Ghaffari-Tabrizi added. One frustration with the acquisition process is the time it takes from the start of the project to the end.
MUNICH ― U.S. Defense Secretary Mark Esper on Saturday called out China as America's main adversary and warned allies that letting the Chinese firm Huawei build its next-generation, or 5G, network risks their security cooperation and information sharing arrangements with the U.S. "Reliance on Chinese 5G vendors, for example, could render our partners' critical systems vulnerable to disruption, manipulation and espionage," Esper said in a speech at the high-level Munich Security Conference. "It could also jeopardize our communication and intelligence sharing capabilities, and by extension, our alliances." Adopting Huawei's equipment on allies' 5G networks, Esper said, "could inject serious risk into our defense cooperation." It was a tough statement partially at odds with other U.S. officials, including Secretary of State Mike Pompeo, who offered assurances last week that U.S.-U.K. intelligence sharing remained strong despite Britain's decision to include Huawei in some parts of its nascent 5G network. A day earlier, the White House's point person for international telecommunications policy, Robert Blair, told reporters: "There will be no erosion in our overall intelligence sharing."
Imagine getting to a courthouse and seeing paper signs stuck to the doors with the message "Systems down." What about police officers in the field unable to access information on laptops in their vehicles, or surgeries delayed in hospitals? That's what can happen to a city, police department, or hospital in a ransomware attack. Ransomware is malicious software that can encrypt or control computer systems. Criminals who launch these attacks can then refuse to return access until they get paid.
Artificial Intelligence (AI) is permeating across various sectors. This includes even the defense sector. With this, it is important to identify the implications of this rising technology in our current way of handling national security and what must be done in order to ensure that the nation remains safe if AI continues to assert domination. This matter is the central issue in the published book, The Department of Defense Posture for Artificial Intelligence, made by the RAND Corporation as mandated by the US Department of National Defense (DoD). If you want to read the book, you may download the free ebook.
The White House released a budget proposal this week that at first glance, looks like a big win for the fields of artificial intelligence and machine learning. The budget for fiscal year 2021 (which begins in October) would ramp up spending for AI research at DARPA (the Pentagon's research arm) and the National Science Foundation by roughly $549 million. The budget request, which still needs to be approved by Congress, increases AI funding from $50 million to $249 million at DARPA, and from $500 million to $850 million at NSF. But while technologists applaud the increased investment in AI, the White House budget proposal is giving many in the science community pause. Overall, the budget proposes $142.2 billion in spending for research and development, a 9% cut from current levels.