White House press secretary Stephanie Grisham reacts to criticism from Democrats and Republican Sen. Rand Paul on the killing of Iranian Gen. Qassem Soleimani on'America's Newsroom.' Former Vice President Joe Biden on Friday said he would not have given the order to launch the airstrike that killed Iranian Quds Force Gen. Qassem Soleimani if he was the commander in chief. Biden was asked about the attack during the Democratic presidential debate in New Hampshire. "No, and the reason I wouldn't have ordered the strike is there isn't any evidence yet of an imminent strike that was going to come from him," he said while on stage next to his Democratic rivals at Saint Anselm College in Manchester. Soleimani was killed last month in a U.S. drone strike in Baghdad that ordered by President Trump.

Artificial intelligence and machine learning hold great promise for both defenders and attackers, making it one of the most important security trends to follow in 2020, says Gerald Beuchelt, the CISO of LogMeIn.* No matter how many brilliant security professionals and analysts you have in an organization, humans just can't keep up with the data processing, analysis and other tasks required to prevent attacks. That's why, when considering trends in cyber security for 2020, artificial intelligence (AI) and its subset machine learning should not be ignored. Here are some of the machine learning and artificial intelligence trends to pay attention to in 2020. According to a recent Capgemini report, 51% of organizations have a high utilization of AI for detection of cybersecurity threats.

A Dutch court has demanded that an algorithm-based system used by the government to identify and track down potential housing and benefit cheats is dropped with immediate effect. As reported by DutchNews, on Wednesday, the District Court of The Hague ruled that the system conflicts with EU human rights and privacy protections. Dubbed System Risk Indication (SyRI), the automatic, machine-learning (ML) tool was used by local Dutch authorities to draw up profiles and lists of individuals suspected of being at high risk of conducting benefits fraud. According to the publication, SyRI creates risk profiles from individuals that committed social security fraud in the past and then scans for "similar" citizen profiles, creating leads for potential investigations into others that may also be committing fraud, or be of a high risk of doing so in the future. SyRI's pooling of citizen data, otherwise kept in separate silos, gave authorities wide-ranging powers and "has been exclusively targeted at neighborhoods with mostly low-income and minority residents," according to UN human rights and poverty rapporteur Philip Alston.

VentureBeat's second special issue is nigh. Following our first special issue, Power in AI, this next one focuses on AI and security. Each special issue is a package of articles that explores a central topic from a variety of angles, from voices in industry, academia, and our newsroom. Whether we're aware of it or not, both AI and cybersecurity are nearly omnipresent in our daily lives at this point, and together they're of increasing importance as our world becomes more connected, more "intelligent," and more reliant on online or automated systems. Yet both can seem intractably technical, even for tech-savvy people.

The way humans function is changing fundamentally with the advent of new technologies such as Internet of Things (IoT), Cybersecurity, Big Data and Artificial Intelligence (AI). A breakthrough technology amongst these, artificial intelligence, is playing a transformational role in a variety of industries and its adoption is promising efficacy at unprecedented levels. Today, artificial intelligence finds applications across industries ranging from finance, healthcare, retail and defence, among others. The progress of AI in India is at pace with global developments. While other countries such as China and the US have focused their energies on capturing as large a market share of AI as possible, India has focused on becoming an experimental space to explore the potential applications of artificial intelligence and machine learning.[1]

The successive subspace learning (SSL) principle was developed and used to design an interpretable learning model, known as the PixelHop method,for image classification in our prior work. Here, we propose an improved PixelHop method and call it PixelHop++. First, to make the PixelHop model size smaller, we decouple a joint spatial-spectral input tensor to multiple spatial tensors (one for each spectral component) under the spatial-spectral separability assumption and perform the Saab transform in a channel-wise manner, called the channel-wise (c/w) Saab transform.Second, by performing this operation from one hop to another successively, we construct a channel-decomposed feature tree whose leaf nodes contain features of one dimension (1D). Third, these 1D features are ranked according to their cross-entropy values, which allows us to select a subset of discriminant features for image classification. In PixelHop++, one can control the learning model size of fine-granularity,offering a flexible tradeoff between the model size and the classification performance. We demonstrate the flexibility of PixelHop++ on MNIST, Fashion MNIST, and CIFAR-10 three datasets.

Cyber-physical system (CPS) has operated, controlled and coordinated the physical systems integrated by a computing and communication core applied in industry 4.0. To accommodate CPS services, fog radio and optical networks (F-RON) has become an important supporting physical cyber infrastructure taking advantage of both the inherent ubiquity of wireless technology and the large capacity of optical networks. However, cyber security is the biggest issue in CPS scenario as there is a tradeoff between security control and privacy exposure in F-RON. To deal with this issue, we propose a brain-like based distributed control security (BLCS) architecture for F-RON in CPS, by introducing a brain-like security (BLS) scheme. BLCS can accomplish the secure cross-domain control among tripartite controllers verification in the scenario of decentralized F-RON for distributed computing and communications, which has no need to disclose the private information of each domain against cyber-attacks. BLS utilizes parts of information to perform control identification through relation network and deep learning of behavior library. The functional modules of BLCS architecture are illustrated including various controllers and brain-like knowledge base. The interworking procedures in distributed control security modes based on BLS are described. The overall feasibility and efficiency of architecture are experimentally verified on the software defined network testbed in terms of average mistrust rate, path provisioning latency, packet loss probability and blocking probability. The emulation results are obtained and dissected based on the testbed.

The White House is pushing to dedicate an additional billion dollars to fund artificial intelligence research, effectively doubling the budget for that purpose outside of Defense Department spending, Reuters reported today, citing people briefed on the plan. Investment in quantum computing would also receive a major boost. The 2021 budget proposal would reportedly increase AI R&D funding to nearly $2 billion, and quantum to about $860 million, over the next two years. The U.S. is engaged in what some describe as a "race" with China in the field of AI, though unlike most races this one has no real finish line. Instead, any serious lead means opportunities in business and military applications that may grow to become the next globe-spanning monopoly, a la Google or Facebook -- which themselves, as quasi-sovereign powers, invest heavily in the field for their own purposes.

Probably the worst error is thinking there is a correlation when that correlation is purely artificial. Take a data set with 100,000 variables, say with 10 observations. You are almost guaranteed to find one above 0.999. This is best illustrated in may article How to Lie with P-values (also discussing how to handle and fix it.) This is being done on such a large scale, I think it is probably the main cause of fake news, and the impact is disastrous on people who take for granted what they read in the news or what they hear from the government.

The IEEE Standards Association has released a report calling for engineers to consider the impact their work will have on climate change, children, and society. The Institute of Electrical and Electronics Engineers (IEEE) is one of the largest organizations for computer scientists in the world. With hundreds of thousands of members, the group undertakes initiatives to create common standards and often consults organizations like the European Commission and OECD on matters of ethics and design principles. "It is imperative to move beyond business as usual and to prioritize the well-being of our children, starting with protecting their privacy and security online. If we fail to do this, their agency, mental health, and self-actualization as humans in any culture will be reliant on forces beyond their control," reads the report titled "Measuring What Matters in the Era of Global Warming and the Age of Algorithmic Promises." The whitepaper encapsulates change already underway at the IEEE that's in line with AI ethics principles released in spring 2019 after years of work, according to John Havens, director of the IEEE Global Initiative on Ethics of Autonomous & Intelligent Systems.