Ilya Sutskever, director of OpenAI, an independent research group, will describe what might be the next big breakthrough in artificial intelligence today at EmTech Digital, a conference organized by MIT Technology Review in San Francisco. Sutskever will describe research showing an approach in machine learning that can perform even better than methods that have produced huge breakthroughs recently. His technique may also prove far more scalable. In a blog post describing the work, Sutskever and colleagues describe using "evolutionary strategies" to have machines figure out for themselves how to solve a complex task. The researchers say the approach is distantly related to a decades-old approach that involves optimizing algorithms using a process of simulated evolution.

Ilya Sutskever, director of OpenAI, an independent research group, will describe what might be the next big breakthrough in artificial intelligence today at EmTech Digital, a conference organized by MIT Technology Review in San Francisco. Sutskever will describe research showing an approach in machine learning that can perform even better than methods that have produced huge breakthroughs recently. His technique may also prove far more scalable. In a blog post describing the work, Sutskever and colleagues describe using "evolutionary strategies" to have machines figure out for themselves how to solve a complex task. The researchers say the approach is distantly related to a decades-old approach that involves optimizing algorithms using a process of simulated evolution.

Our finding continues the modern trend of achieving strong results with decades-old ideas. For example, in 2012, the "AlexNet" paper showed how to design, scale and train convolutional neural networks (CNNs) to achieve extremely strong results on image recognition tasks, at a time when most researchers thought that CNNs were not a promising approach to computer vision. Similarly, in 2013, the Deep Q-Learning paper showed how to combine Q-Learning with CNNs to successfully solve Atari games, reinvigorating RL as a research field with exciting experimental (rather than theoretical) results. Likewise, our work demonstrates that ES achieves strong performance on RL benchmarks, dispelling the common belief that ES methods are impossible to apply to high dimensional problems. ES is easy to implement and scale.

OpenAI is a non-profit AI research company, discovering and enacting the path to safe artificial general intelligence.

It is now table stakes for artificial intelligence algorithms to "learn" about the world around them. The next level: For AI bots to learn how to talk to each other -- and develop their own shared language. New research released last week by OpenAI, the artificial intelligence nonprofit lab founded by Elon Musk and Y Combinator president Sam Altman, details how they're training AI bots to create their own language, based on trial and error, as the bots move around a set environment. This is different from how artificial intelligence algorithms typically learn -- using large sets of data, like to recognize a dog by taking in thousands of pictures of dogs. The world the researchers created for the AI bots to learn in is a computer simulation of a simple, two-dimensional white square.

I know OpenAI will be releasing their official version sometime soon, but for those of you who want to try out using ES right away I made my own implementation. Let me know if you have any comments on it!

Have you ever experienced the dread of overhearing two people, speaking a language you don't understand, begin laughing wildly? You just have to wonder what it is they're talking about, and if it's a joke at your expense. Heck, maybe you even check your teeth to make sure you aren't walking around with half of your lunchtime ham sandwich stuck to your gums. As Wired reports, researchers at OpenAI have made some huge strides in getting bots to communicate with each other, and without actually telling them how to do so. The group published a research paper earlier this week explaining exactly how they were able to accomplish the complex task, and it's all based on reinforcement learning.

OpenAI research has a short introduction on their newest research "Learning to Communicate". There are many trends that I watch for in the field of Deep Learning. Two trends that are related and I believe going to be very promising areas are language learning and multi-agent communication. If you have not been watching, this week has had a tremendous release of papers involving the former and culminating with OpenAI's post, stitching it all together! Let me explain though what transpired in this amazing week.

Robots have learned how to communicate with each other by creating their own language, a new report explains. Experts at artificial intelligence research group OpenAI conducted an experiment that challenged software bots to complete a series of tasks, such as moving to a specific location, in a simple, two-dimensional virtual world. The team used a technique called reinforcement learning, presenting the challenges as cooperative rather than competitive, and rewarding the robots for completing them. "We've just released initial results in which we teach AI agents to create language by dropping them into a set of simple worlds, giving them the ability to communicate, and then giving them goals that can be best achieved by communicating with other agents," wrote the OpenAI team in a blog post. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

Igor Mordatch is working to build machines that can carry on a conversation. That's something so many people are working on. In Silicon Valley, chatbot is now a bona fide buzzword. He doesn't deal in the AI techniques that typically reach for language. He's a roboticist who began his career as an animator. He spent time at Pixar and worked on Toy Story 3, in between stints as an academic at places like Stanford and the University of Washington, where he taught robots to move like humans.