OpenAI has come up with a new robot capable of solving a Rubik's Cube with a single hand. The AI-based company trained neural networks in simulation using reinforcement learning to make this achievement possible. The company has been working on this project since May 2017 and has now achieved its goal marking this as a milestone towards its progress in the field of AI. The time taken by the robotic hand varies depending on how the cube is shuffled but on average, it takes about four minutes to solve the puzzle. However, it is worth noting that this is not the first-ever robot that managed to solve the Rubik's cube.

Medical data analytics startup Healx raised $56M from Atomico and others. Standard Cognition patented an inventory management system. Here's what went down in artificial intelligence this week. Become a CB Insights customer. If you're already a customer, log in here.

Microsoft has invested $1 billion in the Elon Musk-founded artificial intelligence venture that plans to mimic the human brain using computers. OpenAI said the investment would go towards its efforts of building artificial general intelligence (AGI) that can rival and surpass the cognitive capabilities of humans. "The creation of AGI will be the most important technological development in human history, with the potential to shape the trajectory of humanity," said OpenAI CEO Sam Altman. "Our mission is to ensure that AGI technology benefits all of humanity, and we're working with Microsoft to build the supercomputing foundation on which we'll build AGI." The two firms will jointly build AI supercomputing technologies, which OpenAI plans to commercialise through Microsoft and its Azure cloud computing business.

Microsoft has invested $1 billion in the Elon Musk-founded artificial intelligence venture that plans to mimic the human brain using computers. OpenAI said the investment would go towards its efforts of building artificial general intelligence (AGI) that can rival and surpass the cognitive capabilities of humans. "The creation of AGI will be the most important technological development in human history, with the potential to shape the trajectory of humanity," said OpenAI CEO Sam Altman. "Our mission is to ensure that AGI technology benefits all of humanity, and we're working with Microsoft to build the supercomputing foundation on which we'll build AGI." The two firms will jointly build AI supercomputing technologies, which OpenAI plans to commercialise through Microsoft and its Azure cloud computing business.

Yesterday, artificial intelligence(AI) powerhouse OpenAI astonished the world by unveiling a prototype of a robotic arm that could solve a Rubik's cube with one hand. The prototype didn't only represent a milestone for the robotics ecosystem in solving high complexity tasks that actively require sensorial information but it also resulted on a major achievement for the AI community. The reason is that the OpenAI robot was completely trained using simulations based on the reinforcement learning models that the OpenAI Five system used to beat human players in Dota2. The research was discussed in a paper that accompanied the news. The importance of OpenAI's achievement was not about designing a robot that could solve a Rubik's cube.

Meta-Learning describes the abstraction to designing higher level components associated with training Deep Neural Networks. The term "Meta-Learning" is thrown around in Deep Learning literature frequently referencing "AutoML", "Few-Shot Learning", or "Neural Architecture Search" when in reference to the automated design of neural network architectures. Emerging from comically titled papers such as "Learning to learn by gradient descent by gradient descent", the success of OpenAI's rubik's cube robotic hand demonstrates the maturity of the idea. Meta-Learning is the most promising paradigm to advance the state-of-the-art of Deep Learning and Artificial Intelligence. OpenAI set the AI world on fire by demonstrating ground-breaking capabilities of a robotic hand trained with Reinforcement Learning.

This paper by Joseph Suarez, Yilun Du, Phillip Isola, and Igor Mordatch shows their use of a gaming system to suggest and conduct research on how complex life on earth might have started. In this case, the team turned a massively multiplayer online role-playing game (MMORPG) into an artificially intelligent research environment, with all of the right characteristics to encourage this microcosm. Their results show how groups break up in different ways to avoid competition: "population size magnifies and incentivizes the development of skillful behaviors and results in agents that outcompete agents trained in smaller populations," and "the policies of agents with unshared weights naturally diverge to fill different niches in order to avoid competition."

Artificial intelligence research organization OpenAI has achieved a new milestone in its quest to build general purpose, self-learning robots. The group's robotics division says that Dactyl, its humanoid robotic hand first developed last year, has learned to solve a Rubik's cube one-handed. In a demonstration video showcasing Dactyl's new talent, we can see the robotic hand fumble its way toward a complete cube solve with clumsy yet accurate maneuvers. It takes many minutes, but Dactyl is eventually able to solve the puzzle. It's somewhat unsettling to see in action, if only because the movements look noticeably less fluid than human ones and especially disjointed when compared to the blinding speed and raw dexterity on display when a human speedcuber solves the cube in a matter of seconds.

OpenAI, the research company that conducts artificial intelligence research was able to train a pair of neural networks to solve the Rubik's Cube using a robotic hand. In a blog post announcing the achievement, OpenAI said the neural networks were trained in simulation, relying on the OpenAIFive code paired with Automatic Domain Randomization, which is a new technique the firm developed. "Human hands let us solve a wide variety of tasks. For the past 60 years of robotics, hard tasks which humans accomplish with their fixed pair of hands have required designing a custom robot for each task. As an alternative, people have spent many decades trying to use general-purpose robotic hardware, but with limited success due to their high degrees of freedom.,"