With the rapid growth of the applications of machine learning (ML) and other artificial intelligence (AI) techniques, adequate testing has become a necessity to ensure their quality. This paper identifies the characteristics of AI applications that distinguish them from traditional software, and analyses the main difficulties in applying existing testing methods. Based on this analysis, we propose a new method called datamorphic testing and illustrate the method with an example of testing face recognition applications. We also report an experiment with four real industrial application systems of face recognition to validate the proposed approach.

A group called The Campaign to Stop Killer Robots advocates for global treaties to stop AI from waging war without human approval. AI weapons are "grossly unethical and immoral," according to a celebrity advocate quoted in a newspaper. Unfortunately, so are any tools used to wage wars, as there's nothing ethical or moral about a sword, machine gun, or cruise missile. The decision to use them is about a lot of things, some of which can have legitimacy (like survival, freedom from fear or bondage), but weapons doing what they were designed to do have no deeper meaning than that. If the tools of war are unethical and immoral, by definition, to what higher standard should robots be held when it comes to sanctioning violence?

Topics like Artificial Intelligence (AI), the internet of things (IoT), and machine learning are getting lots of hype, but digital twin technology might just be the real game-changer. Digital twin software uses aspects of all the trending tech mentioned (AI, IoT, ML) in a unique way that's changing the way businesses optimize production and investment, and the big boys are already heavily invested. A digital twin is a highly advanced simulation that's used in computer-aided engineering (CAE). It's a digital duplicate that represents a physical object or process, but it is not intended to replace a physical object; it is merely to inform its optimization. Other terms used to refer to digital twin technology include virtual prototyping, hybrid twin technology, and digital asset management, but digital twin is quickly winning out as the most popular name.

The Virginia-class, nuclear-powered, fast-attack submarine, USS North Dakota (SSN 784), transits the Thames River as it pulls into its homeport on Naval Submarine Base New London in Groton, Conn - file photo. Bringing massive amounts of firepower closer to enemy targets, conducting clandestine "intel" missions in high threat waters and launching undersea attack and surveillance drones are all anticipated missions for the Navy's emerging Block V Virginia-class attack submarines. The boats, nine of which are now surging ahead through a new developmental deal between the Navy and General Dynamics Electric Boat, are reshaping submarine attack strategies and concepts of operations -- as rivals make gains challenging U.S. undersea dominance. Eight of the new 22-billion Block V deal are being engineered with a new 80-foot weapons sections in the boat, enabling the submarine to increase its attack missile capacity from 12 to 40 on-board Tomahawks. "Block V Virginias and Virginia Payload Module are a generational leap in submarine capability for the Navy," Program Executive Officer for Submarines Rear Adm. David Goggins, said in a Navy report.

If you thought cybersecurity was a challenging and often weird part of the tech industry, be prepared for it to get even odder. The next couple of years will bring a new range of threats that will take tech security far beyond its traditional boundaries and will require a whole new set of skills and alliances. One example: tech analyst Forrester predicts that deepfakes could end up costing businesses a lot of money next year: as much as $250m. That might happen in a couple of ways. There's the risk to your share price if someone creates a deepfake of your CEO apparently resigning from the company.

Girone: My talk is going to be about what we do and how we process big data and what the challenges are around this. I will be giving a short introduction of CERN. How many people know about CERN here? Ok, so I'll skip the introduction maybe. I will then concentrate on computing and describe a little bit the challenges and the environment that today we work on. Most of my talk is going to be about what comes next in terms of machine, the machine is going to be upgraded, and computing and storage needs, which already are huge today, are going to go even higher. I'm going to discuss a little bit how we have started our R&D program about this. CERN is certainly a wonderful place to work. It has been created, founded by the member states of Europe just after the Second World War to give the opportunity to physicists, scientists, in general, to come together after a big war and work together. This is actually what we still do today. It has been built across two different countries.

Me: "Alexa, tell me what will happen in 2020." Amazon AI: "Here's what I found on Wikipedia: The 2020 UEFA European Football Championship…[continues to read from Wikipedia]" Me: "Alexa, give me a prediction for 2020." Amazon AI: "The universe has not revealed the answer to me." Well, some slight improvement over last year's responses, when Alexa's answer to the first question was "Do you want to open'this day in history'?" As for the universe, it is an open book for the 120 senior executives featured here, all involved with AI, delivering 2020 predictions for a wide range of topics: Autonomous vehicles, deepfakes, small data, voice and natural language processing, human and augmented intelligence, bias and explainability, edge and IoT processing, and many promising applications of artificial intelligence and machine learning technologies and tools. And there will be even more 2020 AI predictions, in a second installment to be posted here later this month. "Vehicle AI is going to be ...

From news outlets to social media sites, there are numerous places that spread fake news, but a study has uncovered a new source – you. Researchers found that people will misremember numerical statistics on a controversial topic in a way that fits their own commonly held beliefs. For example, when people were shown that the number of Mexican immigrants in the United States declined recently during the study--which is true but goes against many people's beliefs--they tended to remember the opposite. And the team also found that as people pass along this misinformation, the numbers can become further and further from the truth. The study was conducted by a team at Ohio State University, who carried out two studies to investigate how people perceive and spread fake news.

Lines of light ranged in the nonspace of the mind, clusters and constellations of data.

Amazon CEO Jeff Bezos warned American technology companies to resist bowing to employee pressure to "turn their backs" on the Pentagon and the defense of the United States. "One of the things happening inside technology companies is there are groups of employees who, for example, think that technology companies should not work with the Department of Defense," said Bezos during a discussion at the Reagan National Defense Forum on Friday, which is also available on Fox Nation. "People are entitled to their opinions," continued Bezos, "but it is the job of the senior leadership team to say, 'No.'" In 2018, Silicon Valley giant Google made the controversial decision to withdraw its bid to work on a Pentagon initiative called Project Maven, which used artificial intelligence to analyze data captured by U.S. government drones. More than 3,000 Google employees signed a letter addressed to company CEO Sundar Pichai protesting Google's involvement.