In 2010, I hired two engineers from an Indian college to help me develop a product that could automatically grade the spoken English ability of job applicants. About a year later, they knocked on my office door with concern etched on their brows. "We are doing machine learning here, but all our friends are doing software engineering," they explained. "Do we have a future?" Most businesses have a top-down mandate to incorporate AI into their processes and products.

In the latest installment of the simmering trade war, the Trump administration reportedly plans to impose restrictions on Chinese investments in US technology companies and American technology exports to China. If implemented as rumored, any company with more than 25 percent Chinese ownership would be barred from investing in US companies that produce "industrially significant technology." Exports of US-made technology deemed important to national security, ranging from chips to robotics to cryptography, would face restrictions as well. Zachary Karabell is a WIRED Contributor. Karabell is the head of Global Strategies Envestnet and the president of River Twice Research.

Building so-called Smarter Cities has long been touted as a major goal for municipalities around the globe. But building systems capable of responding to events in real time is a major challenge for any government operating on a limited IT budget. The hope is that processes will become integrated enough to create a massive pool of data that will then be employed to drive any number of artificial intelligence (AI) applications. The problem is that while city governments typically have access to massive amounts of data, most of it resides in isolated systems run by departments that are often at odds with one another. In fact, Daniel Newman, principal analyst with Futurum, says smart cities are mostly a figment of vendor marketing imagination. "The trouble with smart cities is they don't exist yet," says Newman.

DETROIT – A Tesla Model S electric car that crashed and burned last month in Florida, killing two teenagers, was traveling 116 miles per hour (187 kph) three seconds before impact and only slowed to 86 mph (138 kph) as the air bags were inflated, according to federal investigators. The National Transportation Safety Board, in a preliminary report on the crash, also said that the car missed a curve with a speed limit of 25 mph (40 kph), crashed into a wall twice, and witnesses reported that it erupted in flames. The driver and front-seat passenger, both 18, were killed in the May 8 crash in Fort Lauderdale. A rear-seat passenger was ejected and injured. According to the report released Tuesday, the car's lithium-ion battery re-ignited twice after firefighters extinguished the flames, once as the car was being loaded for removal from the scene and again in a storage yard.

At its core, innovation is about solving problems and building solutions to address common challenges. At the risk of stating the obvious, the enactment of the most comprehensive tax reform in more than 30 years has created a host of new challenges for companies. Technology -- including artificial intelligence, machine learning, and natural language processing -- is absolutely part of the solution that enables companies to evolve and meet the challenges brought on by tax reform. All it takes is a little automation inside the finance function. The impact of tax reform goes well beyond re-calculating taxes owed.

The South Bend Tribune reports the lawsuit was filed Tuesday in U.S. District Court for Northern Indiana. In addition to Notre Dame's abortion policies, it challenges the Trump administration's interim rules allowing universities to disregard a requirement of the Affordable Care Act that health plans cover birth control for women without out-of-pocket costs.

The Pistoia Alliance has released results of a survey that found that 72 per cent of science professionals believe their sector is lagging behind other industries in the development of AI. To accelerate the successful use of AI, The Pistoia Alliance has launched its Centre of Excellence for AI in Life Sciences, aiming to encourage greater collaboration between stakeholders to bridge the gap between technology and science. The aim of the centre is to bring together best practice, adoption strategy, events, and hackathons covering a range of challenges. The survey found adoption of AI is high, with 69 per cent of companies using AI, machine learning, deep learning, and chatbots; an increase from when the same question was asked in September 2017, where 44 per cent of respondents were using or experimenting with AI. This survey shows interest in AI remains strong, but there is still a challenge with moving past the hype to a reality where AI is delivering insights with the power to truly augment researchers' work," commented Dr Steve Arlington, president of The Pistoia Alliance. "It is significant that a majority of people in our own industry believe we are trailing other sectors in the use of AI, and we must address this issue by working closely with each other and with stakeholders in other sectors.

The US Navy is planning a major upgrade to its most commonly used torpedo. Military bosses are hoping to build a new'advanced capabilities' version of the submarine launched Mk48 with longer range and improved stealth capabilities. This will boost is ability to destroy enemy ships, submarines and small boats, especially in shallow water, they hope. The new version will be known as the Mk 48 (advanced capability) torpedo, and it is hoped it will feature an array of new technologies including improved sonar, stealth and control systems. Navy weapons developers are looking for a high-tech, longer range and more lethal submarine-launched heavyweight for use in US submarines.

The government signed a peace accord in late 2016 with the Revolutionary Armed Forces of Colombia (FARC), which was heavily involved in coca production and cocaine trafficking. Since the group demobilized, many new gangs have moved in and taken over its lucrative business and trafficking routes.

Comment on: Decomposition of structural learning about directed acyclic graphs [1] Abstract We propose an alternative proof concerning necessary and sufficient conditions to split the problem of searching for d-separators and building the skeleton of a DAG into small problems for every node of a separation tree T. The proof is simpler than the original [1]. The same proof structure has been used in [2] for learning the structure of multivariate regression chain graphs (MVR CGs). Keywords: Conditional independence, Structural learning, Decomposition, Directed acyclic graph, d-separation tree 1. Introduction In this paper we consider directed acyclic graphs (DAGs) and largely use the terminology of [1], where the reader can also find further details. For the reader's convenience we just recall the definition of d-separation tree here: Definition 1.1. Corresponding author Email addresses: javidian@email.sc.edu (Mohammad Ali Javidian), mgv@cse.sc.edu (Marco Valtorta) Preprint submitted to ArXiv July 2, 2018 2. Necessary and sufficient condition for decomposing structural learning of DAGs First we give several lemmas (Lemma 2.1-2.4) from [1, Appendix A] to be used in the proof of the main theorem in [1, Theorem 1].