BERLIN -- A shoebox-sized European space robot turned up a few surprises when it hopped around on an asteroid last week. In newly released images, the surface of the asteroid Ryugu is "even crazier" than expected, said Ralf Jaumann of the German Aerospace Center's (DLR) Institute of Planetary Research, the scientific director of the MASCOT mission. "Everything is covered in rough blocks and strewn with boulders," he added in an image release. With a diameter of about 3,000 feet (900 meters), Ryugu is one of 17,000 known near-Earth asteroids, and it's made up of some of the most primordial material in the solar system. Studying the space rock's properties and composition could help scientists understand the building blocks of planet formation.

Business spending on cognitive systems will jump an estimated 54% in 2018. Companies continue to invest in artificial intelligence (AI). Doing so means they could boost revenues by 38% within five years. This would also raise employment by 10 percent. By 2030, AI could bump up the global GDP by $15.7 trillion, or a 14% increase.

Two Artificial Intelligence-driven Internet paradigms may emerge in the near future. One will be based on logic, smart enterprises and human merit while the other may morph into an Orwellian control tool. Even former Google CEO Eric Schmidt has foreseen a bifurcation of the Internet by 2028 and China's eventual triumph in the AI race by 2030. In the meantime, the US seems more interested in deflecting the smart questions of today than in building the smart factories of tomorrow. Nothing embodies this better than the recent attempt by MIT's Computer Science and Artificial Intelligence Lab (CSAIL) and the Qatar Computing Research Institute (QCRI) to create an AI-based filter to "stamp out fake-news outlets before the stories spread too widely."

CHIBA – Toyota Motor Corp. and messaging app provider Line Corp. said Monday they will offer an artificial intelligence platform featuring voice commands for navigation services in Toyota cars in Japan by next summer. The services will use Line's Clova (Cloud Virtual Assistant) Auto system, a cloud-based AI platform, which can understand voice commands and respond. The system will be connected to Toyota's in-vehicle device, they said. Toyota drivers can use such voice commands as "Tell me how to get to Tokyo Tower," or "Tell me traffic conditions on the Tomei Expressway," the companies said. Through voice commands inside cars, users can also turn off their lights at home, check the weather at their destination, send and receive messages, and make free calls via the Line app.

Certain phrases tend to follow OnePlus around. Chief among them is that it's "the best phone you've never heard of", and it's representative of the rest. Everyone who's used a OnePlus phone loves it, but the trouble is that group is relatively small. Now the company is hoping that it can jump into the mainstream, taking on the more famous Android phones like Samsung's flagships and finally putting those "iPhone killer" headlines to the test. It intends to do so in a variety of different ways. But the latest is a major announcement that it will finally be much easier to buy: it has signed new partnerships with the UK's biggest carriers and shops, so that people will be able to buy it if they're on EE or Vodafone, or pick one up at John Lewis.

One recent Sunday, 7-year-old Yukito Takanashi of Tokyo was dribbling a soccer ball on a makeshift field. At one point, he put on an eye mask, just like blind soccer players. But he took it off after a while, feeling somewhat uncomfortable. The boy, who has experience playing the game with other children who, like himself, have autism, said it was "difficult" to play with his eyes covered. "It's a good chance to learn about the struggles people with disabilities go through that most people fail to notice in their daily lives," Takanashi's father, Ryoichi, 32, said.

Chinese tech giant Tencent has urged European companies to focus on ethical applications of artificial intelligence, leaving higher-risk ventures to the US and China. Speaking at a conference in Helsinki, Finland, David Wallerstein, Tencent's chief exploration officer, said he was encouraging the European Union to "embrace AI and deploy it in the areas that would have a maximum benefit for human life, even if that technology isn't competitive to take on an American or Chinese market". "By the time you get better at AI in Europe, the planet will have 8.5 billion people and most of the additional billion will be in the developing world. Energy is an area where there's a huge opportunity on the planet, and it's a huge opportunity for Europe. "I've heard lots of people saying how do we catch up with China and the US in the next 15 years, but we may not have much of a planet left by then," he said.

The last few years have seen exponential growth in new technologies. It seems that the world is now opening up to new ideas and experiments. Exponential technologies are fantastic and can help humanity in a great deal. According to the report from PwC, Artificial intelligence could contribute to about $15.7 trillion to the world economy in 2030, expanding the global GDP by 14%. Gartner blockchain trend insight report predicted that Blockchain technology could have a share of to $3.1 trillion in the global economy by 2030.

We discuss deep reinforcement learning in an overview style. We draw a big picture, filled with details. We discuss six core elements, six important mechanisms, and twelve applications, focusing on contemporary work, and in historical contexts. We start with background of artificial intelligence, machine learning, deep learning, and reinforcement learning (RL), with resources. Next we discuss RL core elements, including value function, policy, reward, model, exploration vs. exploitation, and representation. Then we discuss important mechanisms for RL, including attention and memory, unsupervised learning, hierarchical RL, multi-agent RL, relational RL, and learning to learn. After that, we discuss RL applications, including games, robotics, natural language processing (NLP), computer vision, finance, business management, healthcare, education, energy, transportation, computer systems, and, science, engineering, and art. Finally we summarize briefly, discuss challenges and opportunities, and close with an epilogue.

Multiple approaches to use deep learning for image restoration have recently been proposed. Training such approaches requires well registered pairs of high and low quality images. While this is easily achievable for many imaging modalities, e.g. fluorescence light microscopy, for others it is not. Cryo-transmission electron microscopy (cryo-TEM) could profoundly benefit from improved denoising methods, unfortunately it is one of the latter. Here we show how recent advances in network training for image restoration tasks, i.e. denoising, can be applied to cryo-TEM data. We describe our proposed method and show how it can be applied to single cryo-TEM projections and whole cryo-tomographic image volumes. Our proposed restoration method dramatically increases contrast in cryo-TEM images, which improves the interpretability of the acquired data. Furthermore we show that automated downstream processing on restored image data, demonstrated on a dense segmentation task, leads to improved results.