Fox News Flash top headlines for Oct. 21 are here. Check out what's clicking on Foxnews.com When confronted with a swarming drone attack, defenders need to operate with the understanding that each mini-drone could itself be an incoming explosive, a surveillance "node" for a larger weapons system or even an electronic warfare weapon intended to disrupt vital command and control systems. Defenders under drone attack from medium and large drones need to recognize that the attacking platform can be poised to launch missiles or find targets for long-range ground based missiles, air assets or even approaching forces. Modern technology enables drones to use high-resolution sensors and targeting systems to both find and attack targets at very long ranges, thus compounding the threat.

Any business looking to implement emerging technologies has one primary goal: to generate revenue. Deploying advanced digital technologies into business functions is no small undertaking; it requires a large financial investment, a reskilling of the workforce and a cleaning of vast amounts of data to ensure it's prepared to be analyzed. Simply put, if you take this on, you want to see the return. However, there's a fundamental problem with the approach many companies are taking with machine learning. They are using it to superficially enhance the customer experience, but stop short of transforming it into a true revenue-generating engine.

The next generation of emerging AI apps for construction can analyze these expansive new data pools to generate high-value, actionable insights that enable contractors to optimize their marketing, sales, field operations, and prefabrication operations. However, as the Visual Capitalist findings show, only a few early adopters have begun to use these advanced machine learning apps effectively. As a result, these emerging technologies have barely penetrated the industry at this point. The report cites: "While building information modeling and data analytics are widespread among the most innovative construction companies, a host of emerging technologies are starting to have an impact on the sector, and it is the early adopters who are racing ahead of the competition." Of those surveyed, 89% believe that digitization in the construction industry will "transform the way they work."

This example will show how an object can be detected and tracked in a video. Use ImageContainsQ to find whether a dog is detected in the scene. This is a plot showing in which frames of the video a dog is detected. Alternatively, you can assemble a visual representation of the marked frames. Using ImagePosition, you can track the movement of the dog.

Bias and Variance are amongst the more misunderstood concepts in ML, as they're usually described using superficial explanations of under-fitting and over-fitting. In this post, we lay down the statistical groundwork to understand where they come from. The maths is thoroughly explained, so you won't need to be an expert in Statistics to understand it. That said, you should be familiar with the basic concepts of a probability distribution and its Expected Value (average). We'll also assume you're familiar with the ML ideas of regression and supervised learning.

In January, Liz O'Sullivan wrote a letter to her boss at artificial intelligence startup Clarifai, asking him to set ethical limits on its Pentagon contracts. WIRED had previously revealed that the company worked on a controversial project processing drone imagery. O'Sullivan urged CEO Matthew Zeiler to pledge the company would not contribute to the development of weapons that decide for themselves whom to harm or kill. At a company meeting a few days later, O'Sullivan says, Zeiler rebuffed the plea, telling staff he saw no problems with contributing to autonomous weapons. Clarifai did not respond to a request for comment.

It also made me wonder how applicable other metaphors might be: rationalizing, performing, adapting, mocking up?

IBM this afternoon issued several updates to its public cloud and Watson AI portfolios, including news that Aegean Airlines, BNP Paribas, ExxonMobil, Elaw Tecnologia SA (a Brazil-based legal management company) and Home Trust "are selecting IBM public cloud as their preferred destination for mission critical workloads," Big Blue said. On the AI front, IBM announced updates to its "Watson Anywhere" strategy designed to scale AI across any cloud and to ease AI implementations, according to the company. Drift Detection – Intended to address the concerns about data privacy and algorithm accountability, IBM announced the "Drift Detection" capability within Watson OpenScale, an AI platform launched last year to detect bias and to enable understanding of how AI arrived at its results. IBM said Drift Detection Drift Detection indicates how far a model has "drifted" by comparing production and training data and the resulting predictions it creates. Alerts are issued when a user-defined drift threshold is exceeded.

Verint Systems today introduced "knowledge anywhere" enhancements to the Verint Knowledge Management Professional solution. The enhancements include artificial intelligence and automation designed to provide a seamless, intelligent, and efficient way to connect people to knowledge. "With traditional knowledge management solutions, it's kind of like finding a needle in a haystack," says Kelly Koelliker, Verint's director of content marketing. "They require a lot of tagging and linking to bring everything together." She noted that unlike many other AI solutions that require large data sets and months of machine learning training, the new automated, cloud-based solution from Verint leverages AI to understand industry-specific concepts out of the box.

Artificial Intelligence is changing banking, health, business, and the military. But so far, it has been slow to go big in K-12 education, said Scott Garrigan, a professor at Lehigh University at a session at the International Society for Technology in Education's annual conference here. But that is likely to change in the coming years, he said. No sector will be untouched by AI. It will produce changes as big as the automobile," Garrigan said. "We have no idea what's going to happen as AI rolls out massively.