When robots need a brain, their creators turn to Silicon Valley. Most of the AI tech that drives advanced robotics originates in Bay Area labs. At last month’s ReWork Deep Learning for Robotics Summit in San Francisco, researchers from Silicon Valley AI labs and institutes discussed their latest work and how it is being used to teach robots. Synced was onsite to bring you an inside look at their work.
China’s prestigious Tsinghua University is opening a dedicated AI research centre. The Tsinghua University Institute for Artificial Intelligence will be led by Dean Bo Zhang (张钹) of the Chinese Academy of Sciences, and Tsinghua Director of Academic Committee Andrew Chi-Chih Yao (姚期智), a Turing Award Laureate. The announcement was made at today’s Tsinghua-Google AI Symposium in Beijing.
Microsoft is working on a bias-detecting tool which can alert people if an AI algorithm might be treating them unfairly based on their race or gender. As more and more decisions are being made by or based on AI, the detection of unfair biases has become an important public issue.
Embedded AI can transform a tabletop speaker into a personal assistant; give a robot brains and dexterity; and turn a smartphone into a smart camera, music player, or game console. Traditional processors, however, lack the computational power to support many of these intelligent features.
Google has announced the release of MusicVAE, a machine learning model that makes composing musical scores as easy as mixing paint on a palette. A breakthrough from Google Brain’s Magenta Project, MusicVAE generates and morphs melodies to output multi-instrumental passages optimized for expression, realism and smoothness which sound convincingly like human-composed music.
Word2vec is an open source tool developed by a group of Google researchers led by Tomas Mikolov in 2013. It describes several efficient ways to represent words as M-dimensional real vectors, also known as word embedding, which is of great importance in many natural language processing applications