Neptune Lines PCTCs feature METIS Ship Connect – the automated data acquisition solution whose accuracy is approved by Lloyds Register. The METIS platform uses a network of Wireless Intelligent Collectors to harvest machinery, navigation and operational data regardless of equipment supplier. Its ship performance analysis also integrates AIS data, data fetched from vessels' daily / arrival / departure regular reporting and weather forecasts to provide services such as automated noon reporting, analysis of technical and operational domains and weather-related reporting. Outputs include live dashboards showing the condition of main engines, diesel generators, ballast water treatment systems and other machinery as well as power and fuel consumption. However, the METIS platform also allows Neptune Lines management to visualize KPIs such as power vs speed under the full ship speed range and in all weathers using machine learning models and run'what if' routing scenarios to weigh up consequences for fuel and arrival times.

The parameters for a Markov Decision Process (MDP) often cannot be specified exactly. Uncertain MDPs (UMDPs) capture this model ambiguity by defining sets which the parameters belong to. Minimax regret has been proposed as an objective for planning in UMDPs to find robust policies which are not overly conservative. In this work, we focus on planning for Stochastic Shortest Path (SSP) UMDPs with uncertain cost and transition functions. We introduce a Bellman equation to compute the regret for a policy. We propose a dynamic programming algorithm that utilises the regret Bellman equation, and show that it optimises minimax regret exactly for UMDPs with independent uncertainties. For coupled uncertainties, we extend our approach to use options to enable a trade off between computation and solution quality. We evaluate our approach on both synthetic and real-world domains, showing that it significantly outperforms existing baselines.

Divers recovered the device at the bottom of Gelting Bay, on Germany's northern coast, while working to remove abandoned fishing nets that threaten marine life. Designed shortly after WWI by the engineer Arthur Scherbius for commercial usage, the cipher engine was adopted by many national governments and militaries. The portable device is best-known for its use by the Axis powers to encode military commands, for safe transmission by radio, as part of their rapid'blitzkrieg' strategy. Enigma featured a number of wheels, which together formed an electric circuit that repeatedly scrambled an entered character -- and reconfigured after each letter. German military models -- made more complex through the addition of a plugboard, for added scrambling -- and their codebooks were highly sought by the allies.

Ocado's warehouse in Erith, 15 miles east of London on the Thames estuary, is staffed by 1,050 "personal shoppers". Outnumbering them are 1,800 robots the size of small washing machines. You see them by climbing to the top level of the vast warehouse – at 564,000 sq ft, it is more than three times the size of St Peter's in Rome – where a sign tells you that photography is strictly prohibited. The online supermarket is paranoid that rivals will glimpse the technology it believes to be revolutionary. From the viewing platform you can watch these metal cubes endlessly whiz around, moving thousands of plastic crates as if they were playing an enormous game of chess. You occasionally sight bottles of bleach or rosé, packets of noodles and dog biscuits, before they are sent down to a lower level. "I find it quite mesmerising, like robotic ballet," says Mel Smith, CEO of Ocado Retail, the UK arm of the business. "The day I decided I wanted this job was when I went to [the warehouse] and thought, this is absolutely the future."

SpaceX has reused a Falcon 9 rocket for a record breaking seventh time during its most recent mission to put another 60 Starlink satellites into orbit. It comes as the Elon Musk-owned space launch firm is preparing for the first high altitude test flight of its mammoth Starship prototype spaceship - dubbed SN8. Launched from Cape Canaveral in Florida at 02:13 GMT this morning, the Falcon 9 flight was the seventh time that particular first stage booster had been used. This beat the previous record for a booster of six trips and helps Musk in his mission to bring down the cost of launching payloads from the Earth by reusing equipment. SpaceX was able to recover the booster from the Atlantic Ocean using a drone flight - which means it may be able to fly for an eighth time in the future.

Nick Harris, CEO and co-founder of US photonics computing specialist Lightmatter explains how advances in photonic computing technology could give Moore's Law a shot in the arm. Recent advancements in machine learning, computer vision, natural language processing, deep learning and more are already impacting life and humanity in ways seen and often unseen. This is especially true as it relates to artificial intelligence (AI). The demands of AI are growing at a blistering rate. Training AI models today requires ultra-high performance computer chips, leading to what one might refer to as a'space race' among top technology companies to build, acquire, or get exclusive access to the highest-performance chips as soon as they come to market.

As icons and rituals adapt to newer technologies, the rise of robotics and AI can change the way we practice and experience spirituality. Some 100,000 years ago, fifteen people, eight of them children, were buried on the flank of Mount Precipice, just outside the southern edge of Nazareth in today's Israel. One of the boys still held the antlers of a large red deer clasped to his chest, while a teenager lay next to a necklace of seashells painted with ochre and brought from the Mediterranean Sea shore 35 km away. The bodies of Qafzeh are some of the earliest evidence we have of grave offerings, possibly associated with religious practice. Although some type of belief has likely accompanied us from the beginning, it's not until 50,000–13,000 BCE that we see clear religious ideas take shape in paintings, offerings, and objects. This is a period filled with Venus figurines, statuettes made of stone, bone, ivory and clay, portraying women with small heads, wide hips, and exaggerated breasts.

At the outset of World War II, you'd have a better chance of finding a needle in a haystack with a camel stuck in its eye than you did shooting down an enemy aircraft in your first dozen or so shots. This is because anti-aircraft shells at the time used manual fuses that had to be dialed in for specific lengths of time to delay their explosion. The idea was that you'd estimate where the targeted plane would be in, say five seconds, based on its currently flight path, then time the shell for that length, fire the shell at the plane and hope that the timing and location were close enough that shrapnel from the exploding shell hits the plane. If your calculations were off by even a hair, the shell would miss by thousands of feet. And if shooting down piloted aircraft was this hard, intercepting Germany's terrifyingly fast V1 and V2 rockets required far more luck than skill. But that's exactly what the team at Section T set out to do.

Sometime next April, a 50-foot-long autonomous ship will shake loose the digital bonds of its human controllers, scan the horizon with radar, and set a course westward across the Atlantic. The Mayflower Autonomous Ship won't be taking commands from a human captain like the first Mayflower did during its crossing back in 1620. Instead it will get orders from an "AI captain" built by programmers at IBM. The Mayflower's computing system processes data from 30 onboard sensors and six cameras to help the ship sail across the ocean, obey shipping rules (like how to pass other ships at sea), and control electrical and mechanical systems like the engine and rudder. There won't be anyone on board if something goes wrong, although it does have to send a daily report to a human operator back in the UK.

A key problem in computational sustainability is to understand the distribution of species across landscapes over time. This question gives rise to challenging large-scale prediction problems since (i) hundreds of species have to be simultaneously modeled and (ii) the survey data are usually inflated with zeros due to the absence of species for a large number of sites. The problem of tackling both issues simultaneously, which we refer to as the zero-inflated multi-target regression problem, has not been addressed by previous methods in statistics and machine learning. In this paper, we propose a novel deep model for the zero-inflated multi-target regression problem. To this end, we first model the joint distribution of multiple response variables as a multivariate probit model and then couple the positive outcomes with a multivariate log-normal distribution. By penalizing the difference between the two distributions' covariance matrices, a link between both distributions is established. The whole model is cast as an end-to-end learning framework and we provide an efficient learning algorithm for our model that can be fully implemented on GPUs. We show that our model outperforms the existing state-of-the-art baselines on two challenging real-world species distribution datasets concerning bird and fish populations.