In another addition to the ever-expanding list of things robots can do better than humans, artificial intelligence has beaten one of NASA's world-class pilots in a drone race. Researchers at NASA's jet propulsion lab in Pasadena, California, revealed Tuesday the results of two years spent developing algorithms for autonomous drones using technology also used for spacecraft navigation, funded by Google. The space agency put its AI to the test on October 12, finding that their robot was nimbler and did not get tired like a human pilot. Related: A robot mocked Elon Musk and his grim AI predictions. The race, held on October 12, pitted NASA drone pilot Ken Loo against custom-built drones named after comic book characters Batman, Joker and Nightwing, capable of reaching speeds of up to 80 miles per hour.

This paper proposes the continuous semantic topic embedding model (CSTEM) which finds latent topic variables in documents using continuous semantic distance function between the topics and the words by means of the vari-ational autoencoder(V AE). The semantic distance could be represented by any symmetric bell-shaped geometric distance function on the Euclidean space, for which the Mahalanobis distance is used in this paper. In order for the semantic distance to perform more properly, we newly introduce an additional model parameter for each word to take out the global factor from this distance indicating how likely it occurs regardless of its topic. It certainly improves the problem that the Gaussian distribution which is used in previous topic model with continuous word embedding could not explain the semantic relation correctly and helps to obtain the higher topic coherence. Through the experiments with the dataset of 20 Newsgroup, NIPS papers and CNN/Dailymail corpus, the performance of the recent state-of-the-art models is accomplished by our model as well as generating topic embedding vectors which makes possible to observe where the topic vectors are embedded with the word vectors in the real Euclidean space and how the topics are related each other semantically.

We investigate the low-dimensional structure of deterministic transformations between random variables, i.e., transport maps between probability measures. In the context of statistics and machine learning, these transformations can be used to couple a tractable "reference" measure (e.g., a standard Gaussian) with a target measure of interest. Direct simulation from the desired measure can then be achieved by pushing forward reference samples through the map. Yet characterizing such a map---e.g., representing and evaluating it---grows challenging in high dimensions. The central contribution of this paper is to establish a link between the Markov properties of the target measure and the existence of low-dimensional couplings, induced by transport maps that are sparse and/or decomposable. Our analysis not only facilitates the construction of transformations in high-dimensional settings, but also suggests new inference methodologies for continuous non-Gaussian graphical models. For instance, in the context of nonlinear state-space models, we describe new variational algorithms for filtering, smoothing, and sequential parameter inference. These algorithms can be understood as the natural generalization---to the non-Gaussian case---of the square-root Rauch-Tung-Striebel Gaussian smoother.

The deluge of satellite imagery leaves U.S. intelligence agencies with the world's biggest case of FOMO--"fear of missing out"--because human analysts can sift through only so many images to spot a new nuclear enrichment facility or missiles being trucked to different locations. That's why U.S. intelligence officials have sponsored an artificial-intelligence challenge to automatically identify objects of interest in satellite images. Since July, competitors have trained machine-learning algorithms on one of the world's largest publicly available data sets of satellite imagery--containing 1 million labeled objects, such as buildings and facilities. The data is provided by the U.S. Intelligence Advanced Research Projects Activity (IARPA). The 10 finalists will see their AI algorithms scored against a hidden data set of satellite imagery when the challenge closes at the end of December.

NASA has pitted a professional drone racer against its AI. The space agency took on pilot Ken Loo on a specially designed course using three purpose built drones named Batman, Joker and Nightwing. While the human prevailed, NASA found its craft, which were funded by Google, were far more consistent - and didn't suffer from tiredness. The space agency took on pilot Ken Loo on a specially designed course using three purpose built drones named Batman, Joker and Nightwing in a project funded by Google. Loo averaged 11.1 seconds, compared to the drones 13.9 seconds The team built three custom drones (dubbed Batman, Joker and Nightwing) and developed the complex algorithms the drones needed to fly at high speeds while avoiding obstacles.

Here are the stories you shouldn't miss today: What are you doing today, other than turning up the air conditioning if you live in Southern California? Spending it with family and friends? Watching TV? (Check out these tips.) Wondering how you are going to cook that turkey? Feeling remorse about the bird that gave its life? However you spend the day, columnist Bill Plaschke wants you to remember the Thanksgiving spirit.

Elon Musk has been very vocal about his concerns over artificial intelligence, and now the Tesla and SpaceX CEO has quantified his worries. In a recent talk, Musk claimed that efforts to make AI safe only have'a five to 10 per cent chance of success.' The warning comes shortly after Musk claimed that regulation of artificial intelligence was drastically needed because it's a'fundamental risk to the existence of human civilisation.' Elon Musk has been very vocal about his concerns over artificial intelligence, and now the Tesla and SpaceX CEO has quantified his worries. In a recent talk, Musk claimed that efforts to make AI safe only have'a five to 10 per cent chance of success' Elon Musk's latest company Neuralink is working to link the human brain with a machine interface by creating micron-sized devices.

From the Russian President Putin to the Facebook CEO Mark Zuckerberg, everybody is talking about artificial intelligence. Yes, AI is promising a gamut of benefits to forward-thinking businesses. This has been grabbing the attention of everyone who is in the business world. If I tell the definition of artificial intelligence in a single line, "AI is a method of building human intelligence in machines". So machines can think like human, work like human (faster than human), without requiring human intervention.

During yesterday's Autumn statement, Chancellor Philip Hammond outlined positive measures to push the adoption of autonomous and electric cars, develop new 5G networks, treble the number of computer science teachers and further research into AI and robotics. But tucked away in the 88-page document were small changes that show the UK government plans to get a lot tougher on technology companies that aren't willing to give back as much as they should. The most important notice came during Hammond's budget speech. As he pledged £400 million for a UK-wide EV charging network and a £100 million subsidy for electric car buyers, the finance minister also outlined steps to claw back money from tech giants like Google, Amazon and Apple, which use legal loopholes to avoid paying tax in the UK. "Multinational digital businesses pay billions of pounds in royalties to jurisdictions where they are not taxed – and some of these royalties relate to UK sales," said Hammond in his speech.

Prince Harry and a robot have been announced as two guest editors on Radio 4's Today Programme. Their fellow editors will be Baroness Trumpington, Tamara Rojo and Ben Okri. This is the 14th year control has been handed over to public figures between Christmas and New Year. Kensington Palace said Prince Harry would use the opportunity to "shine a spotlight on issues that are close to his heart". The palace added: "He is working closely with Today's team to produce segments on a range of topics, including youth violence, conservation and mental health."