Microsoft Invests in OpenAI to Pursue Challenging AI Goal

With Sam Altman as chief executive, OpenAI, the nonprofit artificial intelligence lab he founded with Elon Musk, has become a for-profit company pursuing investments. In fact, Altman, who stepped down as head of Y Combinator, just inked an impressive $1 billion contract with Microsoft. With Microsoft as a marquee investor, OpenAI will now pursue its lofty goal of creating artificial general intelligence (AGI), a system that can mimic the human brain. Alphabet’s DeepMind lab is also pursuing the creation of AGI. Continue reading Microsoft Invests in OpenAI to Pursue Challenging AI Goal

Google Debuts Deep Planning Network Agent with DeepMind

Google unveiled the Deep Planning Network (PlaNet) agent, created in collaboration with DeepMind, to provide reinforcement learning via images. Reinforcement learning uses rewards to improve AI agents’ decision-making. Whereas model-free techniques work by getting agents to predict actions from observations, agents created with model-based reinforcement learning come up with a general model of the environment leveraged for decision-making. In unfamiliar surroundings, however, agents must create rules from experience. Continue reading Google Debuts Deep Planning Network Agent with DeepMind

DeepMind’s Learning Algorithm Could Prove a Game-Changer

DeepMind recently released the full evaluation of AlphaZero, a single system capable of playing “Go,” chess, and shogi (Japanese chess). This new project builds on AlphaGo, a program that beat one of the best players in the world at the board game “Go” in 2016, and AlphaGo Zero, software capable of mastering the game from first principles. AlphaZero represents a dramatic step forward in AI research as it is one of the first intelligent systems capable of generalizing solutions to new problems with little to no human input. Continue reading DeepMind’s Learning Algorithm Could Prove a Game-Changer

OpenAI Beats Human-Player Team at Complex Video Game

OpenAI, an artificial intelligence research group backed by Elon Musk, stated that its software can beat “teams of five skilled human players” in Valve’s video game “Dota 2.” If verified, the achievement would be a milestone in computer science and a leap beyond other AI researchers working on mastering complex games. IBM’s software mastered chess in the late 1990s, and Alphabet’s DeepMind created software that dominated “Go” in 2016. “Dota 2” is a multiplayer sci-fi fantasy game where teams advance through exploration. Continue reading OpenAI Beats Human-Player Team at Complex Video Game

Intel AI Lab Reveals Plans to Open-Source More NLP Libraries

The Intel AI Lab, which open-sourced a library for natural language processing, plans to open-source more such libraries, to help developers and researchers speed up the process of giving virtual assistants and chatbots functions such as name entity recognition, intent extraction and semantic parsing. With new libraries, these developers can also publish research, train and deploy artificial intelligence and reproduce the latest innovations in the AI community. Intel’s first conference for AI developers was held May 23-24 in San Francisco. Continue reading Intel AI Lab Reveals Plans to Open-Source More NLP Libraries

Google Brain Leverages AI to Generate Wikipedia-Like Articles

The latest project out of Google Brain, the company’s machine learning research lab, has been using AI software to write Wikipedia-style articles by summarizing information on the Internet. But it’s not easy to condense social media, blogs, articles, memes and other digital information into salient articles, and the project’s results have been mixed. The team, in a paper just accepted at the International Conference on Learning Representations (ICLR), describes how difficult it has been. Continue reading Google Brain Leverages AI to Generate Wikipedia-Like Articles

Google Intends to Advance Machine Learning With its AutoML

In May, research project Google Brain debuted its AutoML artificial intelligence system that can generate its own AIs. Now, Google has unveiled an AutoML project to automate the design of machine learning models using so-called reinforcement learning. In this system, AutoML is a controller neural network that develops a “child” AI network for a specific task. The near-term goal is that AutoML would be able to create a child that outperforms human versions. Down the line, AutoML could improve vision for autonomous vehicles and AI robots. Continue reading Google Intends to Advance Machine Learning With its AutoML