There's a lot of buzz about machine learning in government today, given its potential to improve operations, cut costs and produce better program outcomes. But what exactly is it? Machine learning, or ML, is a collection of algorithms and mathematical models used by computer systems to progressively improve their performance on a specific task. Machine learning algorithms build a mathematical model of sample data, known as training data, in order to make predictions or decisions, without being explicitly programmed to perform the task. Put more simply, machine learning is when computer systems use data to train themselves to perform certain actions – rather than requiring humans to do the same work. Machine learning is part of a larger discipline called artificial intelligence (AI).

White House plans to cut funding for science couldn't come at a worse time for the country's ambitions to lead the world in artificial intelligence. The most detailed analysis of Chinese AI research papers yet suggests that China is gaining on the US more quickly than previously thought. China's vibrant tech scene has come up with a number of recent breakthroughs, and the government has recently launched a major initiative to dominate the development of the technology within a matter of years (see "China's AI awakening"). Still, it isn't easy to measure progress in a broad and complex area of technology like artificial intelligence. Previous studies have shown that China already produces a larger number of research papers mentioning AI terms like "deep learning."

Shah Alam, Malaysia – The attorney general is pushing ahead with the trial of Vietnamese Doan Thi Huong in the murder of Kim Jong Nam despite the unexpected decision this week to free her co-accused. The prosecution told the Shah Alam court on Thursday the attorney general had considered "all reasons" but 30-year-old Huong's trial for killing the half-brother of North Korea's leader would proceed. The prosecutor did not elaborate. Indonesian Siti Aisyah was freed on Monday after the prosecution suddenly withdrew the charge against her. She is now back in Indonesia.

As an ontologist, I'm often asked about the distinctions between taxonomies and ontologies, and whether ontologies are replacing taxonomies. The second question is easy to answer: "No." Both taxonomies and ontologies serve vital, and often complementary, roles ... if they are used right. A taxonomy is, to put it simply, a categorization scheme. Most readers should be familiar with a few critical taxonomies such as the Linnaeus Taxonomy used to represent how animals are related to one another, and the Dewey Decimal System for libraries, which represents subject areas of interest.

In February, President Donald Trump showed his administration's commitment to keeping America at the forefront of technological advancements by signing an executive order directing federal agencies to allocate resources to expand the use of artificial intelligence as part of a new "American AI Initiative." With a renewed focus on innovation, the U.S. has a unique opportunity to invest in the technologies that can unlock the full potential of data. Information is generated at a rate that far surpasses our ability to process and measure it. To bridge that gap, we must develop technologies that help identify and mitigate risks within datasets. This process, however, is complicated.

Facebook is under criminal investigation by federal prosecutors examining its data-sharing deals with other major technology companies, according to the New York Times. A New York grand jury has subpoenaed records from "at least two prominent makers of smartphones and other devices", the Times reported, citing two unnamed sources. The two companies are among more than 150, including Amazon, Apple and Microsoft, that have entered into partnerships with Facebook for access to the personal information of hundreds of millions of its users, according to the report. "We are cooperating with investigators and take those probes seriously," a Facebook spokesman told the Times. "We've provided public testimony, answered questions and pledged that we will continue to do so."

Attribution methods have been developed to explain the decision of a machine learning model on a given input. We use the Integrated Gradient method for finding attributions to define the causal neighborhood of an input by incrementally masking high attribution features. We study the robustness of machine learning models on benign and adversarial inputs in this neighborhood. Our study indicates that benign inputs are robust to the masking of high attribution features but adversarial inputs generated by the state-of-the-art adversarial attack methods such as DeepFool, FGSM, CW and PGD, are not robust to such masking. Further, our study demonstrates that this concentration of high-attribution features responsible for the incorrect decision is more pronounced in physically realizable adversarial examples. This difference in attribution of benign and adversarial inputs can be used to detect adversarial examples. Such a defense approach is independent of training data and attack method, and we demonstrate its effectiveness on digital and physically realizable perturbations.

He has demanded "goddamned steam" to power the Navy's aircraft carriers and prefers a wall to drones and other technology to secure the country's southern border. He has rejected the scientific consensus on climate change and repeatedly, wrongly, pointed to occasional wintry weather as proof that he's right. And this week, amid a safety scare involving Boeing's 737 MAX 8 and MAX 9 airplanes, President Trump complained that modern jets are "too complex to fly." He added: "I see it all the time in many products. Always seeking to go one unnecessary step further, when often old and simpler is far better."

The Navy has previously said the LDUSVs might fill the role of "arsenal ships" packed with stand-off missiles to provide additional firepower for a surface task force. Rear Admiral Crites said that a vertical launch system capability would be one requirement for the LDUSV. Crites comment that these ships will also be "sensors" indicates that they could also pack capable and diverse sensors suites, potentially including those not necessary found on manned ships. Doing so would offer commanders increased situational awareness across a broad front. The Navy over-arching unmanned surface vessel plan has three tiers – small, medium, and large – and the service has been very clear in the past that it expected the medium-sized types to fill the requirement for unmanned scouts operating ahead of larger surface action groups.

TRANSIT takes place beyond our home planet, allowing you to traverse the unlimited depths of space and explore worlds outside our own galaxy. Your role as an Artificial Intelligence is to inhabit an interplanetary vessel, manage your resources, and direct your crew. You'll deploy your ship's officers into the field, hunt down criminals, engage in interstellar combat, and deliver supplies and colonists to remote settlements. You must rely on your resources to complete missions by acting through your ship, tech, and crew. Three different AI types – Combat, Command, and Support – lend themselves to varied and interesting game play, but it's when an AI is paired with a ship that the real diversity in character creation comes to the fore.