Learning a policy using only observational data is challenging because the distribution of states it induces at execution time may differ from the distribution observed during training. We propose to train a policy by unrolling a learned model of the environment dynamics over multiple time steps while explicitly penalizing two costs: the original cost the policy seeks to optimize, and an uncertainty cost which represents its divergence from the states it is trained on. We measure this second cost by using the uncertainty of the dynamics model about its own predictions, using recent ideas from uncertainty estimation for deep networks. We evaluate our approach using a large-scale observational dataset of driving behavior recorded from traffic cameras, and show that we are able to learn effective driving policies from purely observational data, with no environment interaction.

When the Apollo 11 spacecraft was orbiting the Moon prior to the first lunar landing, Nasa officials told the astronauts on board to look out for the'lovely girl with a big rabbit'. They were jokingly referring to a story from Chinese mythology in which the goddess Chang'e escapes Earth to live on the Moon with her pet, Jade Rabbit. This week, almost 50 years on from that'giant leap for mankind', the legend of Chang'e resurfaced -- and this time the joke is on the Americans as China announced it had became the first nation to land a spacecraft on the'dark side of the moon'. The robotic probe was named Chang'e 4, a product of China's £3.9 billion a year space exploration project. This week, almost 50 years on from that'giant leap for mankind', the legend of Chang'e resurfaced -- and this time the joke is on the Americans as China announced it had became the first nation to land a spacecraft on the'dark side of the moon' If ever there was a metaphor for the Communist super-power's obsessive secrecy and soaring global ambition, then this audacious secret mission provides it.

The South China Sea is host to a number of countries vying for control in the area. Attempting to develop new tactics and technologies to swing the balance in its favor, China may have found its key advantage – artificial intelligence (AI). Described as an "enabling" technology, in the same way as the combustion engine or electricity, applications range from deep-sea exploration and international investment, to cybersecurity and combat operations. Chinese scientists are currently developing plans for the first-ever AI-run colony on Earth. Designed for unmanned submarine science and defense operations, the project started at the Chinese Academy of Sciences following a visit from President Xi Jinping in April to the deep-sea research institute in Sanya, Hainan province.

Mia Dand is the CEO of Lighthouse3.com, Mia is an experienced marketing leader who helps F5000 companies innovate at scale with digital and emerging technologies. She has built and led new emerging technology programs for global brands including Google, Symantec, HP, eBay and others. Mia is a strong champion for diversity & inclusion in tech.

Functional data analysis is a statistical framework where data are assumed to follow some functional form. This method of analysis is commonly applied to time series data, where time, measured continuously or in discrete intervals, serves as the location for a function's value. Gaussian processes are a generalization of the multivariate normal distribution to function space and, in this paper, they are used to shed light on coastal rainfall patterns in British Columbia (BC). Specifically, this work addressed the question over how one should carry out an exploratory cluster analysis for the BC, or any similar, coastal rainfall data. An approach is developed for clustering multiple processes observed on a comparable interval, based on how similar their underlying covariance kernel is. This approach provides significant insights into the BC data, and these insights can be described in terms of El Nino and La Nina; however, the result is not simply one cluster representing El Nino years and another for La Nina years. From one perspective, the results show that clustering annual rainfall can potentially be used to identify extreme weather patterns.

Anthony Levandowski, the controversial engineer at the heart of a lawsuit between Uber and Waymo, claims to have built an automated car that drove from San Francisco to New York without any human intervention. The 3,099-mile journey started on 26 October on the Golden Gate Bridge, and finished nearly four days later on the George Washington Bridge in Manhattan. The car, a modified Toyota Prius, used only video cameras, computers and basic digital maps to make the cross-country trip. Levandowski told the Guardian that, although he was sitting in the driver's seat the entire time, he did not touch the steering wheels or pedals, aside from planned stops to rest and refuel. "If there was nobody in the car, it would have worked," he said.

The world's first ever underwater Artificial Intelligence colony will be created on the South China sea bed, Chinese President Xi Jinping claims. The base has been described as a'deep sea Atlantis' and will be used for unmanned submarine science and defence operations. Chinese officials and scientists familiar with the plans say that the deep sea station will analyse samples from the sea bed and send reports to the surface. Xi urged the scientists and engineers to'dare to do something that has never been done before' on a recent visit to the deep sea research institute in Hainan Province. China's unmanned submarine vehicle Qianlong III, pictured, could help to drive a subsea exploration programme and herald the arrival of an AI colony on the South China Sea bed, Chinese scientists and officials say'There is no road in the deep sea, we do not need to chase after other countries, we are the road,' President Xi said.

The dream of having a robot deliver packages to your home is now real, provided you live in the right part of the UK. Starship Technologies has launched a ground-based robot package service (the first in the world, according to the company) in Milton Keynes. You have to tell companies to ship to a Starship facility instead of your usual destination, but after that it's just a matter of using a mobile app to schedule a robotic delivery at a convenient time. You can track the bot in the app if you're anxiously awaiting an order. You won't have to wait long to try this on the other side of the Atlantic.

The evaluation of very large amounts of data is becoming increasingly relevant in ocean research. Diving robots or autonomous underwater vehicles, which carry out measurements independently in the deep sea, can now record large quantities of high-resolution images. To evaluate these images scientifically in a sustainable manner, a number of prerequisites have to be fulfilled in data acquisition, curation and data management. "Over the past three years, we have developed a standardized workflow that makes it possible to scientifically evaluate large amounts of image data systematically and sustainably," explains Dr. Timm Schoening from the "Deep Sea Monitoring" working group headed by Prof. Dr. Jens Greinert at GEOMAR. The background to this was the project JPIOceans "Mining Impact." The ABYSS autonomous underwater vehicle was equipped with a new digital camera system to study the ecosystem around manganese nodules in the Pacific Ocean.