Elon Musk has built cars and rockets. OpenAI -- the artificial intelligence research nonprofit co-chaired by Tesla Motors CEO Musk and Y Combinator President Sam Altman -- wants to build a robot for your home.

Elon Musk has built cars and rockets. OpenAI - the artificial-intelligence research nonprofit cochaired by Tesla Motors CEO Musk and Y Combinator President Sam Altman - wants to build a robot for your home. Building a robot, OpenAI's leadership explains in a blog entry on Monday, is a good way to test and refine a machine's ability to learn how to perform common tasks. By "build," the company means taking a current off-the-shelf robot and customizing it to do housework. "More generally, robotics is a good test bed for many challenges in AI," reads the blog entry.

Hi everyone, I was inspired by OpenAI's "Requests for Research" project list that was released a few days ago. In particular, I'm trying to tackle Project #2 on their list, Im2Latex. Unfortunately I'm a newbie when it comes to Machine Learning, and I've only completed one online book so far. I'm asking for some tutorials or online resources that could help me learn about some of the following: sequence to sequence models, attention, and in-depth OCR among other things. If you know of any such tutorials please post them here to help steer me in the right direction.

Deep generative models parameterized by neural networks have recently achieved state-of-the-art performance in unsupervised and semi-supervised learning. We extend deep generative models with auxiliary variables which improves the variational approximation. The auxiliary variables leave the generative model unchanged but make the variational distribution more expressive. Inspired by the structure of the auxiliary variable we also propose a model with two stochastic layers and skip connections. Our findings suggest that more expressive and properly specified deep generative models converge faster with better results. We show state-of-the-art performance within semi-supervised learning on MNIST, SVHN and NORB datasets.

Android N notifications are getting a new look to help provide a better user experience. They now have a fresh look, improved for custom views, and expanded functionality in the forms of Direct Reply. The default look and feel of notifications has changed, and now the fields around the notifications have been collapsed into a new header row with the app's icon and name anchoring the notification, according to Android developer advocate Ian Lake on the Android Developers Blog. This makes the title, text and large icon have a lot of space, and now the notifications are slightly larger and easier to read. Notification actions have also received a redesign and are now in a visually separate bar below the notification, according to the blog.

Elon Musk is getting involved in AI, too, by supporting OpenAI, a non-profit research company focused on advancing digital intelligence for the common good. "Elon Musk has launched the OpenAI project with a star-studded list of backers – Palantir CEO Peter Thiel, LinkedIn founder Reid Hoffman and Y Combinator president Sam Altman," says an impressed Jones. OpenAI is headed up by machine learning expert Ilya Sutskever, ex-Google Brain Team member, and has just opened the OpenAI Gym in beta to help developers working with'reinforced learning', a type of machine learning that's central to AI. Essentially, it's about getting software to alter its behaviour in a dynamic environment in order to get a reward (you can't give Siri a biscuit every time she'found this on the web'). The arrival of AI means a changing of the guard in the tech industry, with disruption, innovation – and the complete domination of the cloud. Expertise, not investment, will become king.

Today, Google's newest machine learning project released its first piece of generated art, a 90-second piano melody created through a trained neural network, provided with just four notes up front. The drums and orchestration weren't generated by the algorithm, but added for emphasis after the fact. It's the first tangible product of Google's Magenta program, which is designed to put Google's machine learning systems to work creating art and music systems. The program was first announced at Moogfest last week. Along with the melody, Google published a new blog post delving into Magenta's goals, offering the most detail yet on Google's artistic ambitions.

My favorite post in a while, look forward to seeing more. I actually have a question for you (or anyone else who reads this) I have some experience with Box2D and other stuff OpenAI/Gym uses and I'd love to create some games/sims that people could train there AI's for, is there a good guide line I could use when making these?

You've probably heard about OpenAI -- a new nonprofit to focus on artificial intelligence research that is good for humanity. So here we have a case of knowledgeable people recognizing a threat and deciding that the way forward is to create a nonprofit organization. This moment has some historical precedent. In 1955, Albert Einstein, Bertrand Russell and several other scientists got together and issued a manifesto about the dangers of nuclear technologies. It would launch decades of Pugwash conferences and the anti-nuclear movement. The founders of OpenAI also issued a manifesto.

Gym-TORCS is the reinforcement learning (RL) environment in TORCS domain with OpenAI-gym-like interface. TORCS is the open-rource realistic car racing simulator recently used as RL benchmark task in several AI studies. Gym-TORCS is the python wrapper of TORCS for RL experiment with the simple interface (similar, but not fully) compatible with OpenAI-gym environments. The current implementaion is for only the single-track race in practie mode. If you want to use multiple tracks or other racing mode (quick race etc.), you may need to modify the environment, "autostart.sh" or the race configuration file using GUI of TORCS.