Fox News White House correspondent Peter Doocy has the latest on the Biden administration revealing plans to train Ukrainian pilots on F-16s on'Special Report.' A U.S. Air Force official said last week that a simulation of an artificial intelligence-enabled drone tasked with destroying surface-to-air missile (SAM) sites turned against and attacked its human user, who was supposed to have the final go- or no-go decision to destroy the site. The Royal Aeronautical Society said it held its Future Combat Air & Space Capabilities Summit in London from May 23-24, which brought together about 70 speakers and more than 200 delegates from around the world representing the media and those who specialize in the armed services industry and academia. An MQ-9 Reaper remotely piloted aircraft (RPA) flies by during a training mission at Creech Air Force Base on Nov. 17, 2015, in Indian Springs, Nevada. The purpose of the summit was to talk about and debate the size and shape of the future's combat air and space capabilities. US MILITARY JET FLOWN BY AI FOR 17 HOURS: SHOULD YOU BE WORRIED?

For more than two decades companies have been striving to improve their supply chain awareness and management through supply chain visibility applications. But companies must take action based on that visibility in order to realize its true value, which is why many companies have deployed supply chain control towers. Today, as new technologies and capabilities are introduced, such as AI and machine learning, are we evolving toward a new type of solution, what some are calling Cognitive Command Centers? What is a Cognitive Command Center? What new or additional benefits does it provide?

Across industries, value chains are facing increasing uncertainty from climatic anomalies, market volatility, and the COVID-19 pandemic, among other factors. Industries as diverse as agriculture, oil and gas, and mining face essentially the same problem: they need the ability to both run with increased efficiency and recover quickly from unforeseen or unexpected challenges. But these two goals often conflict. If companies simply increase production levels, they'll inevitably run into bottlenecks--and if failures occur that worsen those bottlenecks, the entire network can slow down and become less resilient. For more on how COVID-19 has affected supply chains, see Knut Alicke, Richa Gupta, and Vera Trautwein, "Resetting supply chains for the next normal," July 21, 2020. Resolving this conflict presents several challenges.

Many enterprises have already begun using enhanced visibility through "control towers," which provide decision-makers access to real-time manufacturing data aggregated across the organization. These insights enable timely and financially-sound decision making and provide intelligence on tradeoffs. Decision intelligence processes take this process further by applying AI to the "control tower," so that these decisions can be optimized without the need for manual human analysis that may introduce latencies or errors in key decisions that need to be made quickly. An example of this would be when a procurement team learns that an excipient supplier was used in manufacturing a drug and is unable to make their shipment as planned. Through decision intelligence, procurement professionals can quickly respond by sending instructions to the manufacturing floor to slow down production on the line of that drug product.

Despite Tesla's ambitious claims of its vehicles' Full Self-Driving capabilities, today's autonomous navigation technology generally tops out at Level 2. More advanced self-driving systems are in development but likely still years away from being safe and cost-effective enough for everyday use. Seoul Robotics, however, has developed a mesh network that reportedly imparts Level 5 autonomy to vehicle fleets, if only for the "last mile." The company's Level 5 Control Tower system sidesteps some technical challenges of self-driving technology by embedding sensors in the surrounding infrastructure -- traffic lights, nearby buildings, freeway overpasses, etc -- rather than on the vehicles themselves. Instead of each vehicle looking out for itself and responding autonomously to surrounding traffic, the Level 5 Control Tower uses its meshed sensor network to collect data on the overall traffic situation and automate vehicles in the area accordingly, using V2X communications and 4/5G radios.

Across industries, value chains are facing increasing uncertainty from climatic anomalies, market volatility, and the COVID-19 pandemic, among other factors. Industries as diverse as agriculture, oil and gas, and mining face essentially the same problem: they need the ability to both run with increased efficiency and recover quickly from unforeseen or unexpected challenges. But these two goals often conflict. If companies simply increase production levels, they'll inevitably run into bottlenecks--and if failures occur that worsen those bottlenecks, the entire network can slow down and become less resilient. For more on how COVID-19 has affected supply chains, see Knut Alicke, Richa Gupta, and Vera Trautwein, "Resetting supply chains for the next normal," July 21, 2020. Resolving this conflict presents several challenges.

For some companies, it means replacing manual, paper and pencil processes with digital data and process support. For some companies it means using autonomous mobile robots and other forms of robotics in their supply chain. For some, it means applying machine learning and artificial intelligence (AI) to supply chain Big Data. And for some, it means getting better digital data to support an end to end supply chain involving multiple tiers of a company's supply chain. For example, putting a warehouse management system in to replace paper and pencil data in the warehouse would be a limited form of digitization.

This is an opinion piece written by Christian Titze, vice president analyst at Gartner. Opinions are the author's own. Control towers are the artificial intelligence (AI) of supply chain. Everyone wants to have it, but nobody quite knows how it works. Supply chain leaders see the term in vendor presentations, usually connected with the promise that a control tower will make the supply chain better, faster and smarter.

There's no time like the present -- unless you run a supply chain. Shepherding products, parts, food, clothing and other wares across a supply chain in today's digital-powered world requires visibility and the ability to predict the immediate future. As we've written about previously, companies need real-time information and advanced insights to foresee and properly react to oncoming and potential production delays, shortages, market volatility and any other kinks in the supply chain. When supported by cognitive analytics, machine learning and AI capabilities, a supply chain control tower -- a connected hub that monitors and manages the entire process -- enables real-time visibility into key business metrics, drives decisions informed by insights and optimizes costs across the supply chain. A cognitive supply chain allows companies to see the process from end to end.

What does a "journey" mean to you? At IBM, our long standing tradition of journey exploration has led humans to the moon and coined the term machine learning 50 years ago. Now we are helping organizations scale the ladder to AI to reap rewards in growth, productivity and efficiency with IBM Watson. This journey to AI mirrors the history of travel. In this article, I'll explain how IBM Cloud Pak for Data accelerates the journey to AI and delve into the ways AutoAI helps boost the speed of business returns.