Suddenly, everybody is talking about machine learning, AI bots and deep learning. It's showing up in new products to look at "call home data," in cloud-hosted optimization services and even built into new storage arrays! Is this something brand new or just the maturation of ideas spawned out of decades-old artificial intelligence research? Does deep learning require conversion to some mystical new church to understand it, or do our computers suddenly get way smarter overnight? Should we sleep with a finger on the power off button?

The diagram is actually a computer program, so once the user designs the workflow, they can simply click a button to conduct the analysis. WAIVS includes not just discrete tonal analysis but other image-analysis algorithms, including the latest computer vision and artistic style algorithms. Recent work by Leon Gatys and others at the University of Tübingen, Germany, has demonstrated the use of deep learning techniques and technology to create images in the style of the great masters like Van Gogh and Picasso. The specific deep learning approach, called convolutional neural networks, learns to separate the content of a painting from its style. The content of a painting consists of objects, shapes and their arrangements but usually does not depend upon the use of colors, textures and other aspects of artistic style.

Facebook has not been shy about its artificial intelligence (AI) intentions, having long announced the introduction of AI and machine learning into its core social media platform. Now it has unveiled its next step in that direction: DeepText. DeepText, Facebook's newest artificial intelligence system, is a deep learning-based, text-understanding engine that is expected to understand the textual content of several thousand posts per second, spanning more than 20 languages. DeepText's goal is not only to recognize the topics that are being discussed, but to draw in Facebook services that relate to these topics. For instance, someone typing the sentence "I need a ride" in the Messenger app will be sent a prompt for using the in-app Uber or Lyft options.

Google earlier this month released to the public the first piece of original music created by Magenta, a project that utilizes the artificial intelligence engine TensorFlow to determine if an AI system can create compelling pieces of art and music. It's only fitting, then, that the composition be followed by a short film. Sunspring, starring Silicon Valley's Thomas Middleditch and directed by Oscar Sharp, was written by an LSTM (Long Short Term Memory) recurrent neural network. As Gizmodo recounts, Sharp and technologist Ross Goodwin fed the neural network a smattering of sci-fi scripts and a series of prompts for which to base its film on. Found is a TechSpot feature where we share clever, funny or otherwise interesting stuff from around the web.

Their lines are all grammatically correct but occasionally nonsensical, with Ker saying he has to "go to the skull" and Middleditch proclaiming that he's "not a bright light." The script was created by uploading hundreds of sci-fi screenplays into an LSTM recurrent neural network, as you do, and seeing what it returned -- including the surprisingly emotional monologue from Gray that ends the short. A wealth of information on "Sunspring" in general and "Benjamin" (as the A.I. itself is named) in particular is available on Ars. Oscar Sharp directed the film for the Sci-Fi London film festival and does an admirable job of making stage directions like "He is standing in the stars and sitting on the floor" seem reasonable in the final product.

For a while now, Google's company DeepMind has been working on an artificial intelligence (AI) which plays Atari games better than you remember your older brother playing them in the 1980s. The AI is not only extremely proficient at playing these cult classics but has also learned to play 49 of them completely on its own. Despite this impressive feat, the DeepMind's creation isn't perfect and some games have simply proved to be too complicated for it to learn them on its own, Montezuma's Revenge being one of them. However, the Google-owned company has recently been hard at work correcting the flaws in its AI which has finally mastered the unforgiving 1984 platformer developed by the now-defunct Utopia Software. As its developers explain it, they had to make the AI "curious enough" for it to want to actually win the game.

Cognitive Artificial Intelligence (AI) is any computer program that can think, learn, and generally mimic human cognition. Cognitive computing is the process of understanding and building cognitive computer systems, including AI. Cognitive computing uses machine learning (algorithms that allow machines to learn from past experience by detecting patterns), rather than explicitly programmed algorithms (algorithms with a pre-defined and pre-programed sets of rules). The ultimate goal of cognitive computing is to build fully cognitive Artificial Intelligence. The concept of "smart machines" goes back to early science fiction, Alan Turing's theoretical machines and work on early AI, and the emergence of the term cognitive computing in the 50's. Despite the rich history, current cognitive AI is best understood by simply look at recent projects like Google's DeepMind and IBM's Watson two, similar but different, ways modern tech is going about creating machines that can think like humans.

NVIDIA has been a pioneer in accelerating deep learning and has been developing deep learning software, libraries and tools for a number of years. Today's deep learning solutions rely almost exclusively on NVIDIA GPU-accelerated computing to train and speed up challenging applications such as image, handwriting, and voice identification. NVIDIA GPUs excel at parallel workloads and speed up networks by 10-75x compared to CPUs, reducing each of the many data training iterations from weeks to just days. In fact, in the last year, GPUs have sped up training deep neural networks (DNNs) by as much as 12x. AI innovation is happening at breakneck pace.

Deep learning is the fastest-growing field in artificial intelligence, helping computers make sense of infinite amounts of data in the form of images, sound, and text. Using multiple levels of neural networks, computers now have the capacity to see, learn, and react to complex situations as well or better than humans. Every industry will be impacted by deep learning, and many businesses are already delivering new products and services based on this new way of thinking about data and technology.

We're getting A.I. to do all sorts of weird and wonderful things these days, whether its on the small-scale of text prediction or captioning photos, to driving cars for us and beating people at board games. But what if we turned a neural network into a science fiction writer? The answer is that you'd get a complete mess in return. That is the premise behind Sunspring, a film starring Silicon Valley's Thomas Middleditch and directed by Oscar Sharp and written by... well, an LSTM recurrent neural network. Sharp and technologist Ross Goodwin fed the network a bevy of sci-fi scripts, from Ghostbusters 2 to Star Wars, and then gave it a selection of prompts to include in the screenplay it churned out.