The expedition has only just begun and already it is producing some stunning footage of the denizens of Earth's deepest abyss. NOAA's Okeanos research ship will spend the next two months cruising the seas above the Mariana trench, using sonar systems and a remotely operated vehicle (ROV) to explore the little known parts of the trench and its surroundings. Footage from the daily dives is being live-streamed, with highlights posted on the expedition site. On 24 April the ROV captured this footage of a beautiful jellyfish (see video above), belonging to the Crossota genus, at a depth of nearly 4 kilometres. On 25 April it filmed a striking, violet sea cucumber swimming above the sea floor (see video below).

A recent article titled "Why is AI Female?" made the connection that gendered labor, in service professions in particular, is fueling our expectations for gendered AI assistants and service robots. Furthermore, the author argues, this "feminizing -- and sexualizing -- of machines" signals a future with a disproportionate use of feminized VR and robots for a male-dominated sex industry. "Sex with robots is a big leap from asking Siri to set an alarm, but the fact that we've largely equated artificial intelligence with female personalities is worth examining. There are, after all, few sexualized male robots or avatars." Herbert Televox and Mr. Telelux, the early 20th century robots made by Westinghouse, were both male.

A recent article titled "Why is AI Female?" made the connection that gendered labor, in service professions in particular, is fueling our expectations for gendered AI assistants and service robots. Furthermore, the author argues, this "feminizing -- and sexualizing -- of machines" signals a future with a disproportionate use of feminized VR and robots for a male-dominated sex industry. "Sex with robots is a big leap from asking Siri to set an alarm, but the fact that we've largely equated artificial intelligence with female personalities is worth examining. There are, after all, few sexualized male robots or avatars." Herbert Televox and Mr. Telelux, the early 20th century robots made by Westinghouse, were both male.

While many tech firms are working to develop drones to carry goods, one firm believes a giant ball may be more suitable. FreeMotionHandling is a sphere-shaped autonomous vehicle filled with helium that can suck up objects using a'tongue'. The firm says it can pick ups and drop off items up to 400g. While many tech firms work to develop clunky drones to carry goods, one has designed a sphere-shaped autonomous vehicle filled with helium that sucks up objects. It uses an adaptive drive system to thrust itself in directions of rotation and craters for'dynamic flying behavior in all spatial direction. To get from one place to another, FreeMotionHandling uses and indoor tracking system of 10 infrared cameras.

Efficient use of multiple batteries is a practical problem with wide and growing application. The problem can be cast as a planning problem under uncertainty. We describe the approach we have adopted to modelling and solving this problem, seen as a Markov Decision Problem, building effective policies for battery switching in the face of stochastic load profiles. Our solution exploits and adapts several existing techniques: planning for deterministic mixed discrete-continuous problems and Monte Carlo sampling for policy learning. The paper describes the development of planning techniques to allow solution of the non-linear continuous dynamic models capturing the battery behaviours. This approach depends on carefully handled discretisation of the temporal dimension. The construction of policies is performed using a classification approach and this idea offers opportunities for wider exploitation in other problems. The approach and its generality are described in the paper. Application of the approach leads to construction of policies that, in simulation, significantly outperform those that are currently in use and the best published solutions to the battery management problem. We achieve solutions that achieve more than 99% efficiency in simulation compared with the theoretical limit and do so with far fewer battery switches than existing policies. Behaviour of physical batteries does not exactly match the simulated models for many reasons, so to confirm that our theoretical results can lead to real measured improvements in performance we also conduct and report experiments using a physical test system. These results demonstrate that we can obtain 5%-15% improvement in lifetimes in the case of a two battery system.

This article describes an exemplary robot exercise which was conducted in a class for mechatronics students. The goal of this exercise was to engage students in scientific thinking and reasoning, activities which do not always play an important role in their curriculum. The robotic platform presented here is simple in its construction and is customizable to the needs of the teacher. Therefore, it can be used for exercises in many different fields of science, not necessarily related to robotics. Here we present a situation where the robot is used like an alien creature from which we want to understand its behavior, resembling an ethological research activity. This robot exercise is suited for a wide range of courses, from general introduction to science, to hardware oriented lectures.

There is a huge and growing number of systems that depend on batteries for power supply, ranging from small mobile devices to large high-powered systems such as electrical substations. In most of these systems, there are significant user-benefits or engineering reasons to base the supply on multiple batteries, with load being switched between batteries by a control system. The key to efficient use of multiple batteries lies in the design of effective policies for the management of the switching of load between them. This paper describes work in which we show that automated planning can produce much more effective policies than other approaches to multiple battery load management in the literature.

Efficient use of multiple batteries is a practical problem with wide and growing application. The problem can be cast as a planning problem. We describe the approach we have adopted to modelling and solving this problem, seen as a Markov Decision Problem, building effective policies for battery switching in the face of stochastic load profiles. Our solution exploits and adapts several existing techniques from the planning literature and leads to the construction of policies that significantly outperform those that are currently in use and the best published solutions to the battery management problem. We achieve solutions that achieve more than 99\% efficiency compared with the theoretical limit and do so with far fewer battery switches than existing policies. We describe the approach in detail and provide empirical evaluation demonstrating its effectiveness.

An effective to develop an abstract UI model which solution to this problem must have three encompasses the essence of those systems.

General Electric's Research and Elscint (Hackensack, NJ), a manufacturer Johnson Controls (Milwaukee, WI) Development Center (Schenectady, of medical imaging systems, has has begun deployment of a knowledge-based NY) has developed an expert system begun offering its customers a service engineering application which is being used to increase the option based on expert systems. The to increase the productivity of the speed of design of new jet engines, MasterMind system delivers troubleshooting engineering design function. The system, called Engineous, on laptop or desktop computers. The General (Menlo Park, CA), is conveyor for further processing. It problems and recommends solutions objects have become rotated.