NEW YORK--You've been able to ask Amazon's Alexa to help you search for movies and TV shows and deliver other Alexa "skills" through your television set. But only if you connected Amazon's Fire TV external streaming media player or Fire TV Stick to the TV. On Tuesday, Amazon begins taking preorders on Element Electronics Ultra HD 4K smart TVs, the first televisions with the Fire TV Edition built in. Amazon had announced way back during the CES industry confab in January that TVs with the company's Fire TV platform would be coming later in the year. With the supplied voice remote control, you can summon Alexa and bark out various commands: to have Alexa change channels, access more than 300,000 TV episodes and movies from Netflix, Amazon Video, HBO NOW, Showtime, Hulu, Sling TV and other content providers. You can also tap into what Amazon says are 15,000 channels, apps and Alexa skills.

The Skip-Thoughts model is a sentence encoder. It learns to encode input sentences into a fixed-dimensional vector representation that is useful for many tasks, for example to detect paraphrases or to classify whether a product review is positive or negative. See the Skip-Thought Vectors paper for details of the model architecture and more example applications. A trained Skip-Thoughts model will encode similar sentences nearby each other in the embedding vector space. The following examples show the nearest neighbor by cosine similarity of some sentences from the movie review dataset.

Netflix could be about to stop working on millions of Android smartphones, thanks to a new update. The streaming company recently started rolling out Version 5 of its app, which is designed to protect Netflix from potential content pirates. However, the update is also likely to unfairly punish plenty more users who have no such intentions. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

HTC has just launched one of the most unusual smartphones we've ever seen. The HTC U11 is the Taiwanese company's answer to the Samsung Galaxy S8, and it's very different to anything that's come before it. It's designed to be squeezed by users, a new type of interaction that HTC rather ambitiously hopes will find a place in history somewhere alongside the likes of the computer mouse and the touchscreen. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

Submissions should generally be about Artificial Intelligence and its applications. If you think your submission could be of interest to the community, feel free to post it. Try to avoid posting submissions that seem like a self-advertisement. Those usually contain clickbaity titles, speculations or overstatements. If you want to advertise on /r/artificial, the best way is by doing an IAMA.

I was playing around with Amazon ML and built a quick hyperparameter optimization example based on Amazon's GitHub example for k-fold cross validation. I'm an engineer at SigOpt so there's a SigOpt example, but I've also included a non-SigOpt hyperparameter optimization pipeline that updates the old Amazon k-fold cross validation example to boto3, runs as a single file, and lets you provide a list of hyperparameters upfront.

AI is one of the buzzwords of the moment in the world of tech, with startups coming at the concept from all angles -- computer vision, machine learning, unstructured data inference and natural language processing being just a handful -- in a wider effort to create more intelligent machines. Now comes a new organization that hopes to find and foster the next wave of AI businesses and products, co-founded by the ex-CEO of Evernote, Phil Libin (pictured above), who has left his role as a managing director at General Catalyst to build it (but he tells me he'll stay on as an advisor). All Turtles, as the new company is called, is not your traditional startup incubator. In an interview with TechCrunch earlier, Libin (whose other co-founders are Jessica Collier (Product Design) and Jon Cifuentes (Research and Operations) described it as "startup studio", more akin to Netflix's push to develop original content than to 500 Startups. It will start out with locations in San Francisco, Tokyo and Paris.

Retrieving a music file from a large database is a non-trivial task. To support this task, many mechanisms have been developed over the years. However, indexing files remains one of the most popular mechanisms. Several algorithms allow feature extraction from audio signals. Usually, these features are used to describe music content. In this paper, we demonstrate that associations between content-based descriptors can be used as well. We have developed a processing chain which uses association rules mining to find significant relations between content-based descriptors of music files. The significant relations are used to index music files. Experiments conducted demonstrates that the proposed approach can yield interesting results especially with classical music.

Asking effective questions is a powerful social skill. In this paper we seek to build computational models that learn to discriminate effective questions from ineffective ones. Armed with such a capability, future advanced systems can evaluate the quality of questions and provide suggestions for effective question wording. We create a large-scale, real-world dataset that contains over 400,000 questions collected from Reddit "Ask Me Anything" threads. Each thread resembles an online press conference where questions compete with each other for attention from the host. This dataset enables the development of a class of computational models for predicting whether a question will be answered. We develop a new convolutional neural network architecture with variable-length context and demonstrate the efficacy of the model by comparing it with state-of-the-art baselines and human judges.

We describe a new method called t-ETE for finding a low-dimensional embedding of a set of objects in Euclidean space. We formulate the embedding problem as a joint ranking problem over a set of triplets, where each triplet captures the relative similarities between three objects in the set. By exploiting recent advances in robust ranking, t-ETE produces high-quality embeddings even in the presence of a significant amount of noise and better preserves local scale than known methods, such as t-STE and t-SNE. In particular, our method produces significantly better results than t-SNE on signature datasets while also being faster to compute.