Machine learning is at the peak of the hype scale, but travel search giant Expedia has been building its core business on the technology for the best part of a decade. Expedia has grown far beyond a search engine for flights – it's now the parent company of a dozen travel brands including Trivago and Hotels.com The business of delivering quality flight search results is tough, and Fleischman describes it as an "unbounded computer science problem". The reason for this is because flight itineraries and schedules are constantly changing, and Expedia's proprietary'best fare search' (BFS) has to'learn' and adapt all the time. The extent of the problem can be summed up by one statistic.

This is a recursive neural network (LSTM type) with 3 layers of 680 neurons each, trying to find patterns in audio and reproduce them as well as it can. It's not a particularly big network considering the complexity and size of the data, mostly due to computing constraints, which makes me even more impressed with what it managed to do. The audio that the network was learning from is voice actress Kanematsu Yuka voicing Hinata from Pure Pure. I used 11025 Hz, 8-bit audio because sound files get big quickly, at least compared to text files - 10 minutes already runs to 6.29MB, while that much plain text would take weeks or months for a human to read. I wrote a program that converts any data into UTF-8 text and vice-versa, and to my excitement, torch-rnn happily processed that text as if there was nothing unusual.

Sometimes an app is so just right for its moment in history that it hits everyone between the eyes and lingers in the limelight. That's what is happening with Prisma (free, iTunes Store link), a free photo/art app for iPhone that touts special effects image "filters" that render the painterly styles of famous artists like Van Gogh, Picasso, Lichtenstein, Mondrian, Kandinsky, and others. The buzz around Prisma and the fascination it has generated persists because the app is super simple to use and yields an endless variety of genuinely unique results. Each style is applied differently in response to the unique patterns in the picture. Use of neural networks for art, which involves interpreting images in layers, is not brand a new concept.

In this project, we will be building an autonomous rc car using supervised learning of a neural network with a single hidden layer. We will use a remote-controlled car with a Raspberry Pi and a Raspberry Pi camera module mounted on top. In the training mode, the camera module would provide images needed to train the neural network and in the autonomous mode; would provide the images to the trained model to predict the movements and direction of the car. You can find the Github repository for this project here. We will need a remote controlled car, a Raspberry Pi, a power bank, an L293D Motor Driver IC and some jumper wires to connect the circuits.

Learn from OpenAI CTO Greg Brockman on how NVIDIA DGX-1 has the power to create impactful AI technologies and achieve unimaginable breakthroughs.

Articoolo's ability to automatically generate high-quality, near instant articles in minutes is amazing. Here's some How-To tips and strategies to get the best results from using Articoolo article builder, then tweaking it for your content marketing, blog posts and article distribution needs. Using AI artificial intelligence and NLG natural language generation, Articoolo is on the cutting edge of CGC computer generated content. As an automated article builder, it isn't perfect. But it can generate very well-written drafts you can quickly modify to meet your content marketing needs.

There was always that one kid in high school that could forge his mom's signature. Sick and "get out of school early" notes. Data analytics company BeyondCore has been acquired by Salesforce for an undisclosed sum. Liveuamap is opendata-driven media platform that change the way you receive latest news. Japan lags Silicon Valley in conventional internet services but could become a global leader in the deep-learning technology of artificial intelligence, a leading AI expert has said.

The campaign execution, testing, optimization and analysis work that marketers are required to perform manually today has grown too immense for them to handle effectively. Artificial intelligence marketing is a real solution to the nearly impossible challenges facing marketing professionals everywhere. Marketers today must coordinate their campaigns for dozens of devices, technologies, and channels, meeting individual users with messaging relevant to who they are and what they want. Achieving that near 1:1 consumer targeting takes plenty of data from each relevant channel -- it takes so much data, in fact, that dealing with it effectively has become an almost impossible challenge for most organizations. The overwhelming response to the problem of big data overload has been to adopt a wide array of software tools to organize information and surface insights.

CEVA, Inc. (NASDAQ: CEVA), the leading licensor of signal processing IP for smarter, connected devices, today announced that Novatek Microelectronics, Taiwan's 2nd largest fabless IC design house, has licensed and deployed the CEVA-XM4 intelligent vision DSP for its next-generation vision-enabled System-on-Chips (SoCs) targeting a range of end markets requiring advanced visual intelligence capabilities. Novatek's current camera SoC lineup for car DVR and surveillance systems integrates the 3rd generation CEVA-MM3101 imaging & vision DSP and is shipping in volume. By integrating CEVA-XM4 as a dedicated vision processor in their next-generation SoC designs, Novatek and its customers can rapidly deploy highly-sophisticated vision algorithms to enable advanced applications such as surveillance systems with face detection and authentication, drone anti-collision systems and advanced driver assistance systems (ADAS). These types of applications are built utilizing CEVA's Deep Neural Network (CDNN2), a proprietary software framework that enables deep learning tasks to run on the CEVA-XM4 and outperform any GPU or CPU-based system in terms of speed, power consumption and memory bandwidth requirements. "The CEVA-XM4 is an exceptional processor for imaging and computer vision, offering outstanding performance, flexibility and power efficiency for applications requiring visual intelligence capabilities," said Allen Lu, Assistant Vice President of iVoT SBU, Novatek.