MIM Software Inc., a leading global provider of medical imaging software, announced it has received 510(k) clearance from the US Food and Drug Administration (FDA) for its deep learning auto-contouring software, Contour ProtégéAI . Contour ProtégéAI is an auto-contouring solution that seamlessly integrates into any department's workflow and can be rapidly implemented into virtually any environment. User feedback and a determination to continuously improve auto-segmentation were key drivers in developing the product. "Our customers are under continual pressure to improve their practices while facing escalating time constraints," said Andrew Nelson, Chief Executive Officer of MIM Software Inc. "Our deep learning auto-segmentation product, Contour ProtégéAI, will play a critical role in reducing the burden of contouring." Auto-contouring is an ideal use case for deep learning algorithms because it is one of the most time-consuming clinical tasks.
The U.S. Air Force plans to have an operational combat drone by 2023. The service plans to build out a family of unmanned aircraft, known as Skyborg, capable of carrying weapons and actively participating in combat. The Air Force's goal is to build up a large fleet of armed, sort-of disposable jets that don't need conventional runways to take off and land. The Air Force, according to Aviation Week & Space Technology, expects to have the first operational Skyborg aircraft ready by 2023. Skyborg will be available with both subsonic and supersonic engines, indicating both attack and fighter jet versions.
In a move that caused a ripple effect across the Middle East, Iranian General Qassem Soleimani was killed in a US drone strike near Baghdad's international airport on January 3. On that day, the Pentagon announced the attack was carried out "at the direction of the president". In a new report examining the legality of armed drones and the Soleimani killing in particular, Agnes Callamard, UN special rapporteur on extrajudicial and arbitrary killings, said the US raid that killed Soleimani was "unlawful". Callamard presented her report at the Human Rights Council in Geneva on Thursday. The United States, which is not a member after quitting the council in 2018, rejected the report saying it gave "a pass to terrorists". In Callamard's view, the consequences of targeted killings by armed drones have been neglected by states.
From startups to enterprises racing to get new products launched, AI and machine learning (ML) are making solid contributions to accelerating new product development. There are 15,400 job positions for DevOps and product development engineers with AI and machine learning today on Indeed, LinkedIn and Monster combined. Capgemini predicts the size of the connected products market will range between $519B to $685B this year with AI and ML-enabled services revenue models becoming commonplace. Rapid advances in AI-based apps, products and services will also force the consolidation of the IoT platform market. The IoT platform providers concentrating on business challenges in vertical markets stand the best chance of surviving the coming IoT platform shakeout.
Artificial intelligence (AI) presents an opportunity to transform how we allocate credit and risk, and to create fairer, more inclusive systems. AI's ability to avoid the traditional credit reporting and scoring system that helps perpetuate existing bias makes it a rare, if not unique, opportunity to alter the status quo. However, AI can easily go in the other direction to exacerbate existing bias, creating cycles that reinforce biased credit allocation while making discrimination in lending even harder to find. Will we unlock the positive, worsen the negative, or maintain the status quo by embracing new technology? This paper proposes a framework to evaluate the impact of AI in consumer lending. The goal is to incorporate new data and harness AI to expand credit to consumers who need it on better terms than are currently provided. It builds on our existing system's dual goals of pricing financial services based on the true risk the individual consumer poses while aiming to prevent discrimination (e.g., race, gender, DNA, marital status, etc.).
In 2018, Congress established the National Security Commission on Artificial Intelligence (NSCAI)--a temporary, independent body tasked with reviewing the national security implications of artificial intelligence (AI). But two years later, the commission's activities remain little known to the public. Critics have charged that the commission has conducted activities of interest to the public outside of the public eye, only acknowledging that meetings occurred after the fact and offering few details on evolving commission decision-making. As one commentator remarked, "Companies or members of the public interested in learning how the Commission is studying AI are left only with the knowledge that appointed people met to discuss these very topics, did so, and are not yet releasing any information about their recommendations." That perceived lack of transparency may soon change.
Earlier this week, the President's Council of Advisors on Science and Technology (PCAST) released a report outlining what it believes must happen for the U.S. to advance "industries of the future." Several of the committee's suggestions touched on the field of AI as it relates to federal, state, and private-sector partnerships, as well as departmental budgetary considerations. In particular, the report recommends that the U.S. grow nondefense federal investments in AI by 10 times over the next 10 years and for the federal government to create national AI "testbeds," expanding the National Science Foundation's (NSF) AI Institutes with at least one AI Institute in each state and creating a "National AI Consortia" to share capabilities, data, and resources. Loosely, PCAST -- which lives in the Office of Science and Technology -- provides advice to the president on science and technology policy. In the report, the committee argues the U.S. will need to boost AI R&D investments from $1 billion a year in 2020 to $10 billion a year by 2030 in order to remain competitive.
As NASA gears up to send humans to the moon and Mars it is also working on new advances to protect the space terrains from human germs. The American space agency released updates to its Planetary Protection Policies that provide new requirements for both astronaut and robotic missions. The added policies note that no biological matter is left on or around the moon, along with humans are to not contaminate any part of Mars with biological materials or return to Earth with germs from the Red Planet. The first woman and next man are set to head to the moon in 2024 and the first crewed mission to Mars is planned for the 2030s – and as early as 2035. The added policies note that no biological matter is left on or around the moon.
TS may look like a simple data object and easy to deal with, but the reality is that for someone new it can be a daunting task just to prepare the dataset before the actual fun stuff can begin. Every single time series (TS) data is loaded with information; and time series analysis (TSA) is the process of unpacking all of that. However, to unlock this potential, data needs to be prepared and formatted appropriately before putting it through the analytics pipeline. TS may look like a simple data object and easy to deal with, but the reality is that for someone new it can be a daunting task just to prepare the dataset before the actual fun stuff can begin. So in this article we will talk about some simple tips and tricks for getting the analysis-ready data to potentially save many hours of one's productive time.
Deadly Premonition 2: A Blessing in Disguise is a conflicting experience. On one hand, the game's narrative revolving around the mysterious murder of a young woman in a small Louisiana town is deeply intriguing with its constant twists and surprises that spin an ever-widening web of sadism, death, and terror until the very end. On the other hand, the game looks and plays like shit. As the sequel to perhaps the most critically polarizing game of all time, 2010's Deadly Premonition, this duality fits like a glove and developer SWERY somehow manages to fulfill this game's unique expectations. Both games center around mysteries with similar beginnings that only get more interesting as they go on, but just like its sequel, the first game is also pretty awful to look at, even for 10 years ago. That earlier game follows FBI Special Agent Francis York Morgan as he works to solve a murder mystery in the small, rural town Greenvale, Wash. in the mid-2000s. Morgan runs into paranormal threats and wild characters as he divines answers from cups of coffee and frequently converses and consults with a voice in his head named Zach.