An Associated Press investigation finds that Russian cyber spies exploiting a national vulnerability in cybersecurity are trying to break into the emails of scores of people working on military drone technology. An accused Russian hacker blamed for attacking LinkedIn, Dropbox and Formspring is finally facing American prosecutors after a lengthy extradition fight in the Czech Republic. Yevgeniy Aleksandrovich Nikulin is due to appear in U.S. federal court in California on Thursday for a detention hearing. It's unclear whether Nikulin has any connection to the Russian troll farm the Internet Research Agency, which is widely blamed by American authorities for interfering in the 2016 presidential election. But only two days after Nikulin's arrest, American officials for the first time publicly warned that the Russian government was directing efforts to influence the election by hacking and releasing private information.

ARLINGTON, Va.--(BUSINESS WIRE)--The Consumer Technology Association (CTA) today announced that CES Asia 2018 will highlight advancements in artificial intelligence (AI) as a new dedicated product category on the show floor, building on the successful demonstration of AI applications across the latest consumer tech products showcased at CES earlier this year. Alibaba A.I. Labs, Baidu DuerOS and iFLYTEK, among others, will exhibit the latest in big data analytics, speech recognition and predictive technology. With China setting the pace to become a global innovation leader in AI, CES Asia will bring together the biggest players shaping the future of artificial intelligence. "Artificial intelligence is one of those exciting technologies that will become ubiquitous in the next decade as it becomes more deeply embedded in the products that we use day in and day out to make our lives better, " said John T. Kelley, senior director, international programs and show director, CES Asia. "AI is already being incorporated in everyday consumer technology products that provide practical benefits, including cars, smart homes, robotics, health and wellness devices and home security. China is leading the way in AI, embracing innovation and setting global standards and it will be front and center during CES Asia 2018!" More, ARM Accelerator and the Hong Kong University of Science and Technology will bring several cutting-edge companies to CES Asia.

We prove a \emph{query complexity} lower bound for approximating the top $r$ dimensional eigenspace of a matrix. We consider an oracle model where, given a symmetric matrix $\mathbf{M} \in \mathbb{R}^{d \times d}$, an algorithm $\mathsf{Alg}$ is allowed to make $\mathsf{T}$ exact queries of the form $\mathsf{w}^{(i)} = \mathbf{M} \mathsf{v}^{(i)}$ for $i$ in $\{1,...,\mathsf{T}\}$, where $\mathsf{v}^{(i)}$ is drawn from a distribution which depends arbitrarily on the past queries and measurements $\{\mathsf{v}^{(j)},\mathsf{w}^{(i)}\}_{1 \le j \le i-1}$. We show that for every $\mathtt{gap} \in (0,1/2]$, there exists a distribution over matrices $\mathbf{M}$ for which 1) $\mathrm{gap}_r(\mathbf{M}) = \Omega(\mathtt{gap})$ (where $\mathrm{gap}_r(\mathbf{M})$ is the normalized gap between the $r$ and $r+1$-st largest-magnitude eigenvector of $\mathbf{M}$), and 2) any algorithm $\mathsf{Alg}$ which takes fewer than $\mathrm{const} \times \frac{r \log d}{\sqrt{\mathtt{gap}}}$ queries fails (with overwhelming probability) to identity a matrix $\widehat{\mathsf{V}} \in \mathbb{R}^{d \times r}$ with orthonormal columns for which $\langle \widehat{\mathsf{V}}, \mathbf{M} \widehat{\mathsf{V}}\rangle \ge (1 - \mathrm{const} \times \mathtt{gap})\sum_{i=1}^r \lambda_i(\mathbf{M})$. Our bound requires only that $d$ is a small polynomial in $1/\mathtt{gap}$ and $r$, and matches the upper bounds of Musco and Musco '15. Moreover, it establishes a strict separation between convex optimization and \emph{randomized}, "strict-saddle" non-convex optimization of which PCA is a canonical example: in the former, first-order methods can have dimension-free iteration complexity, whereas in PCA, the iteration complexity of gradient-based methods must necessarily grow with the dimension.

Hypergraph is a general way of representing high-order relations on a set of objects. It is a generalization of graph, in which only pairwise relations can be represented. It finds applications in various domains where relationships of more than two objects are observed. On a hypergraph, as a generalization of graph, one wishes to learn a smooth function with respect to its topology. A fundamental issue is to find suitable smoothness measures of functions on the nodes of a graph/hypergraph. We show a general framework that generalizes previously proposed smoothness measures and also gives rise to new ones. To address the problem of irrelevant or noisy data, we wish to incorporate sparse learning framework into learning on hypergraphs. We propose sparsely smooth formulations that learn smooth functions and induce sparsity on hypergraphs at both hyperedge and node levels. We show their properties and sparse support recovery results. We conduct experiments to show that our sparsely smooth models have benefits to irrelevant and noisy data, and usually give similar or improved performances compared to dense models.

China has seen incredible economic and social changes over the past few decades. But could the impact of artificial intelligence take the country by surprise? I recently spent a few weeks in the country, talking to researchers and entrepreneurs developing cutting-edge AI technologies and products. What stuck with me--beyond the growing ambition of China's researchers and the overall vibrancy of its tech scene--is how much people are starting to talk about the potential for AI to eliminate jobs across the country. Just a few years ago this seemed like much less of a concern.

In China, face-recognition technology is being used for lots of things, from surveillance to ride-hailing and shopping. NPR's Shanghai correspondent Rob Schmitz tried it out and met with manufacturers.

The Linux Foundation launched a deep learning initiative this week designed to create a "neutral space for harmonization and acceleration" of AI, machine learning and deep learning technologies. The initial focus will be an AI standardization effort. The open source project called LF Deep Learning Foundation seeks to make the emerging AI technologies widely available to data scientists and developers, the group said during this week's Open Networking Summit in Los Angeles. Founding members include several Chinese technology giants that are pouring huge sums into AI research as part of a national strategy to dominate AI. They are: China's search giant Baidu; networking giant Huawei (SHE: 002502); Tencent, often referred to as China's Facebook; and telecommunications equipment vendor ZTE (SHE: 000063).

South Korea media outlets are now saying that LG Electronics will likely adopt an advanced type of liquid crystal diode (LCD) display for its upcoming G7 flagship phone. The move is seen as the company's way to make the premium device more affordable and attractive to consumers. Korea Herald reported Monday that the LG G7 is now predicted to feature an advanced LCD panel, called M LCD. The panels will reportedly be manufactured by the tech firm's very own LG Display. An M LCD panel has pixels that are composed of green, red, blue and white colors. The pixels of such an advanced LCD panel are said to emit more light than standard LCD panels, but they consume 40 percent less power.

The US will levy trade tariffs on China this week designed to target "largely high-technology products." In retaliation for the taxation, China announced it would raise duties on 128 US imports. Begun, the trade wars have. President Trump, over Easter weekend, let loose on Twitter with his usual barrage of attacks. Jeff Bezos, Amazon, and The Washington Post took a moderate amount of vitriol, as did other usual suspects like immigrants and journalists.

The odds of getting venture capital funding for an early stage startup is about one in one thousand. It's unsurprising that every now and then startups seek the best way to raise capital and scale their companies. With this in mind, EVC Ventures hosted an Artificial Intelligence Venture Capital Bootcamp along with BW Businessworld and some other investment partners including Sequoia Capital on 24 March, 2018 at EVC Ventures, India. This Bootcamp witnessed participation of leading global investors and industry experts from BCG, BW Businessworld, Sequoia Capital, EVC Ventures, YourNest Venture Capital, Indian Angel Network, Unifyed and many more. The AI Venture Capital Bootcamp received tremendous interest from startups all over the country.