More than 60 years after it was blown up by two atomic blasts then later sunk off the cost of California, the wreckage of the historic USS Independence has been seen for the first time. After being found in April this year, the Ocean Exploration Trust (OET) has now explored the wreck with robotic submarines, and released the first close-up images of how the ship looks now. This exploration is revealing the ship holds war secrets, including a fighter plane within the sunken aircraft carrier. After being found in April this year, a team of divers from the National Oceanic and Atmospheric Administration ( NOAA) has now explored the wreck with robotic submarines, and released the first close-up images of how the ship looks now. Walkway leading to personnel hatch near'gun tub' hanging over walkway on starboard side of ship is pictured USS Independence (CVL 22) operated in the central and western Pacific from November 1943 until August 1945.

The first female pilot to fly solo from Britain to Australia has been'brought back to life' with ground-breaking 3D technology. Amy Johnson completed the journey from London to Darwin in 1930 - one of many record-breaking flights during her career. To mark 75 years since her death, experts have created a fully interactive digital 3D version of Ms Johnson, which can even walk and talk about her achievements. The first female pilot to fly solo from Britain to Australia has been'brought back to life' with ground-breaking 3D technology. 'Virtual Amy' will go display in the children's library within Hull Central Library as part of the Amy Johnson Festival.

PARIS – Scientists Wednesday announced the discovery of an Earth-sized planet orbiting the star nearest our Sun, opening up the glittering prospect of a habitable world that may one day be explored by robots. Named Proxima b, the planet is in a "temperate" zone compatible with the presence of liquid water -- a key ingredient for life. The findings, based on data collected over 16 years, were reported in the peer-reviewed journal Nature. "We have finally succeeded in showing that a small-mass planet, most likely rocky, is orbiting the star closest to our solar system," said co-author Julien Morin, an astrophysicist at the University of Montpellier in southern France. "Proxima b would probably be the first exoplanet visited by a probe made by humans," he told AFP.

A sampling-based optimization method for quadratic functions is proposed. Our method approximately solves the following $n$-dimensional quadratic minimization problem in constant time, which is independent of $n$: $z^*=\min_{\mathbf{v} \in \mathbb{R}^n}\langle\mathbf{v}, A \mathbf{v}\rangle + n\langle\mathbf{v}, \mathrm{diag}(\mathbf{d})\mathbf{v}\rangle + n\langle\mathbf{b}, \mathbf{v}\rangle$, where $A \in \mathbb{R}^{n \times n}$ is a matrix and $\mathbf{d},\mathbf{b} \in \mathbb{R}^n$ are vectors. Our theoretical analysis specifies the number of samples $k(\delta, \epsilon)$ such that the approximated solution $z$ satisfies $|z - z^*| = O(\epsilon n^2)$ with probability $1-\delta$. The empirical performance (accuracy and runtime) is positively confirmed by numerical experiments.

We derive fundamental sample complexity bounds for recovering sparse and structured signals for linear and nonlinear observation models including sparse regression, group testing, multivariate regression and problems with missing features. In general, sparse signal processing problems can be characterized in terms of the following Markovian property. We are given a set of $N$ variables $X_1,X_2,\ldots,X_N$, and there is an unknown subset of variables $S \subset \{1,\ldots,N\}$ that are relevant for predicting outcomes $Y$. More specifically, when $Y$ is conditioned on $\{X_n\}_{n\in S}$ it is conditionally independent of the other variables, $\{X_n\}_{n \not \in S}$. Our goal is to identify the set $S$ from samples of the variables $X$ and the associated outcomes $Y$. We characterize this problem as a version of the noisy channel coding problem. Using asymptotic information theoretic analyses, we establish mutual information formulas that provide sufficient and necessary conditions on the number of samples required to successfully recover the salient variables. These mutual information expressions unify conditions for both linear and nonlinear observations. We then compute sample complexity bounds for the aforementioned models, based on the mutual information expressions in order to demonstrate the applicability and flexibility of our results in general sparse signal processing models.

New bots are constantly being launched and we have covered a fair few, from this chatbot chef which plans meals for users via emoji, to a messenger bot that helps out in emergency situations. New innovation, Wonder, is designed to help users store and recall the information they need from their gym locker password, their insurance provider, right through to the type of ink cartridges their printer uses. Customers first enter their phone number on Wonder's website. They then text Wonder the information they want to remember at a later date. The app stores that information, and when the customer is trying to recall the details, they can ask Wonder directly via text message: "When's the next company meeting?"

In addition, IRIS-NoiseSweeper software has also been ported to the Tensilica Vision DSP to provide premium video quality and cleaner still-images. The software is targeted at image noise reduction for high-resolution still images. The technology features an automated noise profile estimation that reduces calibration needs and shortens development time. It operates in a single frame and eliminates any motion-blurring phenomena associated with multi-frame techniques. The Tensilica family of imaging/vision DSPs was designed for the complex algorithms in imaging, video and computer vision applications including innovative multi-frame image capture, video pre- and post-processing, object and face recognition, low-light enhancement and many other complex tasks.

When it comes to artificial intelligence (AI), UK senior business decision-makers overwhelmingly agree that can help improve customer experiences by providing new data. Nearly 50% also pointed to AI allowing for automation of tasks, freeing humans to focus on more valuable work. About one in four of those surveyed in July 2016 by Morar Consulting for digital agency Squiz say that AI will reduce human error, and some think AI will help them deliver services better. But there are plenty of AI concerns as well. Over one-third of those surveyed said their primary concern is with the very concept of AI itself: 36% said they took issue with the lack of human control or oversight in AI. For another 30%, the primary cause for concern was the expense of AI, and one in four cited errors made by the AI as their leading concern.

Summary: Sensors that know how you feel? Sensors that want to change the way you feel? When did that happen and better yet how? We're getting used to sensors finding out what we're doing. Apparently they are now sufficiently sophisticated that they can even tell if I'm sitting up straight (yes Mom – BTW using a camera is almost cheating, you should be able to do this with just an accelerometer and a gyro).

It might be a term you've heard being passed around the internet recently, but in the simplest form… A chatbot is a computer program that mimics conversation with the user using artificial intelligence. As well as conventional chat, messenger platforms have tightened up their user experience for chatbot communication. This is achieved by using a series of multiple-choice questions in the format of a pseudo-conversation. This is similar to gaming (e.g. Fallout and Final Fantasy), when gamers are asked to make choices via a multiple selection screen that influence the game's story.