Automatic decision-making approaches, such as reinforcement learning (RL), have been applied to (partially) solve the resource allocation problem adaptively in the cloud computing system. However, a complete cloud resource allocation framework exhibits high dimensions in state and action spaces, which prohibit the usefulness of traditional RL techniques. In addition, high power consumption has become one of the critical concerns in design and control of cloud computing systems, which degrades system reliability and increases cooling cost. An effective dynamic power management (DPM) policy should minimize power consumption while maintaining performance degradation within an acceptable level. Thus, a joint virtual machine (VM) resource allocation and power management framework is critical to the overall cloud computing system. Moreover, novel solution framework is necessary to address the even higher dimensions in state and action spaces. In this paper, we propose a novel hierarchical framework for solving the overall resource allocation and power management problem in cloud computing systems. The proposed hierarchical framework comprises a global tier for VM resource allocation to the servers and a local tier for distributed power management of local servers. The emerging deep reinforcement learning (DRL) technique, which can deal with complicated control problems with large state space, is adopted to solve the global tier problem. Furthermore, an autoencoder and a novel weight sharing structure are adopted to handle the high-dimensional state space and accelerate the convergence speed. On the other hand, the local tier of distributed server power managements comprises an LSTM based workload predictor and a model-free RL based power manager, operating in a distributed manner.

Ring's second-generation video doorbell adds a quick release rechargeable battery and boosts video resolution from 720p to 1080p. It remains one of the only video doorbells that can provide its own power instead of relying on your home's existing wiring. Like the previous version we tested, we set up the Ring Video Doorbell 2 in its wireless configuration, mounting the unit in the same, somewhat awkward, location outside our front door. While much of the setup process remains the same, one key difference is the addition of a removable lithium ion battery. This means you can physically install the doorbell while waiting for the battery to charge.

South Korean tech powerhouse LG Electronics Inc. said Sunday it has set up two research centers to develop technologies related to artificial intelligence, Yonhap News Agency reported. One center will focus on developing AI and the other robotics, it said. The AI center will focus on developing technologies applicable to LG Electronics' home appliance lineup, smartphones and automobile parts, while the robotics center will focus on developing "core technologies of smart robotics," Yonhap reported. A division within the AI center "will be devoted to R&D for deep learning, a new area of AI research where a computer emulates the way the human brain creates patterns from data and processes them," the report said.

Logitech has announced a pair of new computer mice with the MX Master 2S and the MX Anywhere 2S. Both are updated versions of Logitech's previous MX models, and both come with a new "Flow" feature for multiple computer support. Logitech's MS Master and MX Anywhere were both considered to be the company's two best mice, and it just seems appropriate that both have new, upgraded models. Like with its previous iteration, the MX Master 2S's thumb wheel can be customized with additional functions through the Logitech Options software. As for the MX Anywhere 2S, it comes with the same speed adaptive scroll wheel feature.

Accurately predicting the future capacity and remaining useful life of batteries is necessary to ensure reliable system operation and to minimise maintenance costs. The complex nature of battery degradation has meant that mechanistic modelling of capacity fade has thus far remained intractable; however, with the advent of cloud-connected devices, data from cells in various applications is becoming increasingly available, and the feasibility of data-driven methods for battery prognostics is increasing. Here we propose Gaussian process (GP) regression for forecasting battery state of health, and highlight various advantages of GPs over other data-driven and mechanistic approaches. GPs are a type of Bayesian non-parametric method, and hence can model complex systems whilst handling uncertainty in a principled manner. Prior information can be exploited by GPs in a variety of ways: explicit mean functions can be used if the functional form of the underlying degradation model is available, and multiple-output GPs can effectively exploit correlations between data from different cells. We demonstrate the predictive capability of GPs for short-term and long-term (remaining useful life) forecasting on a selection of capacity vs. cycle datasets from lithium-ion cells.

Deep beneath the ocean's surface, scientists exploring the Central Pacific Basin have spotted behaviour that's never been seen before outside of the fossil record. Among the many remarkable creatures observed during the mission, researchers with the NOAA's Okeanos Explorer witnessed the moment a snail appeared to be munching on the feces of a'sea lily.' Experts say this behaviour can be traced back hundreds of millions of years to the Palaeozoic Era. Among the many remarkable creatures observed during the mission, researchers with the NOAA's Okeanos Explorer witnessed the moment a snail appeared to be munching on the feces of a'sea lily' (pictured) The expedition kicked off on April 27, in effort to collect new data on the deep-water areas of the Pacific, beginning near the American Samoa capital Pago Pago, and ending near Honolulu, Hawaii. It comes as part of the three-year Campaign to Address the Pacific monument Science, Technology, and Ocean Needs, which aims to explore Pacific marine monuments sanctuaries, the'last relatively pristine marine ecosystems on the planet.' Over 23 days, researchers conducted remotely operated vehicle (ROV) dives in American Samoa, the high seas, and the Jarvis Island, Kingman Reef, and Palmyra Atoll Units of Pacific Remote Islands Marine National Monument.

A robot overlord adjusts Rob's Open Source Android (ROSAL) at the London Science Museum (AP Photo/Alastair Grant) Searching recently for evidence of artificial intelligence taking over our jobs, lives, and everything else, Tom Davenport came up empty. "Nary a robot overlord to be found," he declared at the 14th MIT Sloan CIO Symposium. A day later, at the 3rd RE•WORK Deep Learning Summit, I found many humans who are successfully lording over robots, telling their artificial intelligence creations how to perform a number of narrow cognitive tasks. Davenport, who has published eighteen books on topics ranging from managing organizational data and processes to leading with AI and analytics, is working on his next one, tentatively titled The Cognitive Company. Throughout his distinguished career in a field littered with "hype cycles," Davenport has opted to respond with healthy skepticism to the typical breathless and enthusiastic pronouncements regarding the latest new new thing.

In the late 1950s, Sandia Laboratory was looking for a way to handle radioactive materials without putting humans in danger. The answer was the Mobot--short for either "remote robot" or "mobile robot"--a remotely operated system designed by Hughes Aircraft Co. in 1959 that offered a unique and effective combination of strength and dexterity. A Sandia press release announcing the robot called it a "Replacement for Man," but in fact the robot had no autonomy; it was teleoperated by a human sitting in front of a massive control console connected to the robot by a 60-meter cable. The Mark I version of the Mobot had a pair of meter-long hydraulically actuated arms capable of lifting up to 68 kilograms (150 pounds), along with adjustable-strength grippers. The entire system was mounted on a forklift.

Claridge, founder of xCraft, is best known for being the first contestant on Shark Tank to receive money from all the Sharks – even Kevin O'Leary! Walking the floor of Xponential 2017, the annual convention of the Association for Unmanned Vehicle Systems Integration (AUVSI), Claridge remarked to me how the drone industry has grown up since his TV appearance. Claridge has gone from pitching cellphone cases that turn into drones (aka phonedrone) to solving mission critical problems. The age of fully autonomous flight is near and the drone industry is finally recovering from the hangover of overhyped Kickstarter videos (see Lily drone's $34 million fraud). During the three days of Xponential 2017, several far-reaching announcements were made between stalwarts of the tech industry and aviation startups.

Like most other smart doorbells, Ring lets you see who's at your door and interact with your guests before letting them in. Unlike its competition, however, Ring doesn't require dedicated electrical wiring; instead, it can work off of rechargeable battery power. Since our test home doesn't have built-in doorbell wiring, we chose the wireless installation option. Unfortunately, despite the freedom it offered, we still didn't have a lot of placement options for the Ring. The former was too thin to serve as an adequate base, while the latter were too short to accommodate the Ring's entire length.