Hierarchical Neural story generation had the most realistic paragraphs of any text generation paper I came across last summer when I was doing research on this topic. I also find it fun that they used a subreddit as their training set (writingprompts). The architecture is a mixture of self attention layers and convolutional layers. Generate a prompt and then generate a full story. I tried to extend their work to prompt, outline, story but the results were meh (they were similar quality to not bothering with the outline step).

Deep learning is a buzzword that has been hyped by the business and technical press for years, often with relatively meager results that failed to live up to expectations. But over the past 18 months, according to a new report from Tractica, the true power of deep learning has been realized, thanks to advances in hardware and algorithms that use pattern recognition applied in a continuous learning loop, enabling them to train themselves to perform tasks without requiring explicit programming code. The sheer power of deep learning, however, is likely to lead to the development of more powerful and disruptive applications of tomorrow, such as driverless cars, personalized education, and preventative healthcare. Tractica forecasts that, with this expanding set of applications, the worldwide deep learning software market will grow from $3 billion in 2017 to $67.2 billion by 2025. "Deep learning has been a key point of focus for many companies, given its potential to transform entire industries," says principal analyst Keith Kirkpatrick.

Today, many companies use AI and location technology to drive more accurate predictions and strengthen decision-making. Hear Joseph Sirosh, Corporate Vice President of the Cloud AI Platform at Microsoft, talk about how AI combined with location intelligence magnifies understanding and improves business. To learn more about the power of location technology for better insights and better decisions, download our free e-books Making Sense of Digital Transformation and Making the Most of the Internet of Things. We talk to business and technology leaders who share analysis, insights, and stories on data science, the Internet of Things, Smart Communities and other forces driving digital transformation and leveraging the power of location intelligence.

Until last year, Brandon Tory, a senior software Artificial Intelligence engineer at Google and rapper, led a secret double life. Raised in Brockton, Massachusetts, a neighborhood known for crime and drugs, he lived with his family in a shelter as a teenager. Tory knew he wanted to be some kind of scientist, but also had a passion for music. He wanted to have a huge impact in both creativity and science. At University of Massachusetts Amherst he studied computer engineering and then worked as a senior Apple engineer in Cupertino.

I'm super happy to introduce my side project called: deepy. Here is the code: https://github.com/kaszperro/deepy The purpose was to learn how neural networks, autograd and other mechanisms work. Also I think, that those who want to know how mainstream libraries work, it's good starting point, because the code is very small and simple. It's still in early stage though, but so far I've programmed: It uses numpy for computations.

As recently as five years ago, the advent of Netflix, Hulu, Amazon Prime Video and YouTube Premium sounded the death knell for multi-billion dollar businesses, altered the living-room habits of millions of people, and changed studio production structures permanently. Companies that adapted survived, and the viewing audience received a handful of clear benefits in return -- most notably the ability to watch high-quality shows and movies on demand and, most recently, an explosion of award-winning, culturally transformative entertainment options. The idea of a "Netflix for games" service has been floating around since long before video-streaming became a thing, but it hasn't found a solid foothold quite yet. Streaming games is a more complicated process than streaming video, since it adds user input to the mix. While being piped into a player's home or phone from a server that could be hundreds of miles away, the game has to respond, without lag, to every button press a player makes.

Gradient-based optimization of absolute errors is tricky, since the gradient is "never" zero. In theory, adaptive methods should be able to damp oscillations so that it converges to the minimum. However, I found none of the'standard' methods were able to do this "out of the box". Learning rate decay could alleviate the problem, but needs manual tuning which I would rather avoid. Does anyone know of a method that can do this?

When watching a film, you may be the sort of person who immerses themselves in the story and special effects with a view to a couple of hours of escapism. Or, perhaps like me, you are the type who wants to work out what is real and what is computer generated imagery (CGI) and how realistic it really is. Either way, filmmakers continue to push the boundaries to improve the quality and variety of the special effects they deliver with the purpose of enhancing the audience experience and keep us coming back to the box-office. Films are now leaving the studio and the location shoot and moving in a steady stream towards the data center. The latest wave of technology seeing adoption includes areas such as Machine Learning and Deep Learning, which are all subcategories of artificial intelligence (AI).

Amazon Alexa has been programmed to read the news headlines in the style of a newsreader. The popular voice assistant will now emphasise words, and mimic the intonation and pace of a TV anchor to present the news in a more natural way. Newsreader Alexa has been trained to read the daily bulletins when the user says'Alexa, what's the latest?' Amazon Alexa has been programmed to read the news headlines in the style of a newsreader. The virtual assistant already was able to read out the headlines but using the traditional robotic voice. Amazon conducted tests and found that people preferred hearing the news in this more realistic and listener friendly manner, compared to the robotic tone.

In high school, Mackenzie Leake shot a movie about being afraid to get her driver's license. "A very millennial subject," she jokes. It gave her a punishing lesson in editing video: Leake spent countless hours, over the course of weeks, "scrubbing" through her footage to find the best shots, then painstakingly assembling them. "It's a ton of grunt work," she notes. Now, seven years later, she's trying to accelerate the process.