Lucd, an Enterprise AI platform and solution services company, today announced it has partnered with AI Satellitez, whose mission is to provide artificial intelligence and machine learning models to businesses to optimize their operations. Lucd's Enterprise Artificial Intelligence platform provides digital transformation through the responsible use of data. Utilizing intellectual property combined with leading technologies and tools to form a complete open platform, Lucd enables all businesses to take advantage of the fast-moving AI market to gain a competitive advantage. "At Lucd, we are excited about our partnership with AI Satellitez as they provide best in class model creation capabilities that enhance the customer experience, driving business transformation with unique use cases for our customers," said John Leschorn, COO and Co-Founder at Lucd. "AI Satellitez is excited to partner with Lucd as they offer the best in class platform to run custom Machine Learning and Data Analytics models that we build for our clients. Their unique offer of a secure and compliant platform for our customers to store data and run models is a competitive advantage for us all," said Sam Reagin, VP of Sales for AI Satellitez.

If there's anything that machine learning has taught us, it's that artificial intelligence can't write for shit--just look at this very horny, but very bad A.I. …

Over the past few years, the term "deep learning" has firmly worked its way into business language when the conversation is about Artificial Intelligence (AI), Big Data and analytics. And with good reason – it is an approach to AI which is showing great promise when it comes to developing the autonomous, self-teaching systems which are revolutionizing many industries. Deep Learning is used by Google in its voice and image recognition algorithms, by Netflix and Amazon to decide what you want to watch or buy next, and by researchers at MIT to predict the future. The ever-growing industry which has established itself to sell these tools is always keen to talk about how revolutionary this all is. But what exactly is it?

It takes years of work to become a cinematographer. Researchers at Carnegie Mellon University are developing a system for aerial cinematography that learns from human visual preferences in order to enable drones to make artsy filmmaking choices while autonomously filming scenes. The system does not require GPS tags to localize targets or prior maps of an environment. Drones have been a boon to filmmakers, significantly lowering costs for aerial shots, which previously required chartering manned helicopters or airplanes. But the ease of access also comes with a downside.

Musician Halldór Eldjárn has been drawing a lot of attention recently for his AI-approach to composing, as well as his homemade percussion-playing robots. Here's what has made him the artist he is today. The concept of generating music has always fascinated me. My uncle, Kjartan Ólafsson, has worked in this field for decades, creating an AI-driven music composition software called Calmus. He definitely made me realise it was possible to make a computer write music.

Just tried TPU pytorch for a classification problem, my impressions so far are quite positive. Working with TPU looks very similar to working with a multi-GPU with distributed data parallel - it needs about the same amount of modifications, maybe even smaller, at least when all ops are supported and shapes are static, like it is for a simple classifications task. It also needs an efficient data pipeline and a powerful machine to feed all 8 TPU core, similar to what you'd need for an 8-GPU machine. So far I didn't see any strange hangs or stability issues.

Called LOGAN, the deep neural network, i.e., a machine of sorts, can learn to transform the shapes of two different objects, for example, a chair and a …