DeepMind researchers introduce a framework that aims to solve the problem by enabling simple RL agent implementations to be run at different scales of execution.
The slogan of Arlington, Texas is “American Dream City,” and as residents start their commute this morning some may wonder if they are in fact dreaming. A fleet of futuristic autonomous vehicles today began chauffeuring Arlingtonites along city streets in self-driving startup Drive.ai’s latest public road testing project.
The DeepMimic paper’s first author, Berkeley PhD student Xue Bin Peng, has now open-sourced the project’s codes, data, and frameworks. Moreover, Peng’s new research demonstrates that DeepMimic’s simulated characters can also learn to perform highly dynamic movements by using regular video clips of human examples as input data.
Xilinx believes one solution is its recently-released, cutting-edge 7nm programmable chip Versal. The chip is based on Xilinx Adaptive Compute Acceleration Platform (ACAP) technology and built with 7nm FinFET manufacturing process technology, integrating the Arm Cortex-A72 and Cortex-R5, an AI engine and DSP engine.
The Massachusetts Institute of Technology (MIT) today announced they will invest US$1 billion into a new college for artificial intelligence. The MIT Stephen A. Schwarzman College of Computing will “constitute both a global center for computing research and education, and an intellectual foundry for powerful new AI tools.”
Founded in 1999, Tokyo-based DeNA has developed popular platforms and services for gaming, E-commerce, automotive, healthcare and entertainment content distribution. As AI continues transforming all things digital, DeNA is expanding its deep learning tech capabilities to support R&D on new techniques.
Virtual personal assistants have become an integral part of our everyday lives. So much so that some people want to take the relationship with their digital friend to the next level. A new Business Insider article reveals that over one million people asked Amazon’s Alexa to marry them in 2017.
Last month’s ReWork Deep Learning Summit in London provided a peek at current recent research progress and future trends in artificial intelligence technologies. The two-day event featured top scientists and engineers from Facebook, MIT Media lab, DeepMind and other leading institutes.
A Shanghai Jiao Tong University research team has announced the world’s first software for photonic analog quantum computing and simulation. “Feynman Photonic Analog Quantum Simulation” (FeynmanPAQS) is named after renown quantum physicist Richard P. Feynman.
The company made a series of AI-related announcements today at the Huawei Connect 2018 Conference in Shanghai, introducing two AI chips and a machine learning framework. Huawei’s AI push is expected to intensify its battle with domestic rivals Alibaba, Tencent and Baidu in the AI market.
The computational power of smartphones and tablets has skyrocketed to the point where they approach the level of desktop computers on the market not long ago. Although it’s easy for mobile devices to run all the standard smartphone apps, today’s artificial intelligence algorithms can be too compute-heavy for even high-end devices to handle.
UC Berkeley researchers have published a paper demonstrating how Deep Reinforcement Learning can be used to control dexterous robot hands for complicated tasks. Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations proposes a low-cost and high-efficiency control method that uses demonstration and simulation techniques to accelerate the learning process.
A typical JD motorcycle deliveryman in Shanghai delivers 100 packages per day, racing along the city’s waterfront, navigating tiny alleyways and darting between the city’s skyscrapers. That may seem impressive but JD is still striving to improve motorcycle delivery efficiency with new tech — much of it AI-powered.
This August, thousands of Chinese middle school students participated in a two-day “AI teacher vs. Human teacher” competition. Students were separated into two groups: one received math tutoring from experienced teachers, the other from an intelligent learning system.
“Best GAN samples ever yet? Very impressive ICLR submission! BigGAN improves Inception Scores by >100.” The above Tweet is from renowned Google DeepMind research scientist Oriol Vinyals. It was retweeted last week by Google Brain researcher and “Father of Generative Adversarial Networks” Ian Goodfellow, and picked up momentum and praise from AI researchers on social media.
Visual search is an important new business tool that is changing the way people interact with E-commerce and social media platforms. Instead of entering a text query, visual search engines enable users to identify and locate items via photos snapped with their smartphone cameras.
Skip is an experimental research language project that Facebook developed over the last three years: “Skip tracks side effects to provide caching with reactive invalidation, ergonomic and safe parallelism, and efficient garbage collection. Skip is statically typed and ahead-of-time compiled using LLVM to produce highly optimized executables.”
Nadja Rhodes is enamoured with artificial intelligence. A Seattle-based Microsoft software developer unpracticed in AI techniques such as deep learning, Rhodes had applied to a number of tech company sponsored AI residency initiatives, but to no avail. And so she was thrilled to be accepted by OpenAI Scholars.
Georgia Tech and Google Brain researchers have introduced the new interactive tool GAN Lab, which visually presents the training process of complex machine learning model Generative Adversarial Networks (GANs). Even machine learning newbs can now experiment with GAN models using only a common web browser.
Sneakerheads of the world love online reseller GOAT. Sellers submit formatted photos of their sneakers and the company finds a buyer. The GOAT website has some 400,000 listings. Rare models like Air Yeezy Blink, Air Jordan 3 Retro Solefly and Pharrell x Chanel x NMD Human Race Trail can fetch tens of thousands of dollars.
Chip giant Nvidia today announced the opening of its new AI research centre in Toronto.
Nvidia Director of AI Sanja Fidler will lead the AI Research Lab. The University of Toronto Assistant Professor previously worked at the Toyota Technological Institute in Chicago as a research assistant professor.
In a new paper Durham University researchers introduce a anomaly detection model, GANomaly, comprising a conditional generative adversarial network that “jointly learns the generation of high-dimensional image space and the inference of latent space.” The process enables the model to perform anomaly detection tasks even in sample-poor environments.
Chinese Internet mogul Jack Ma has a flair for naming new businesses: Alibaba originates from a character made famous in the One Thousand and One Nights collection of Arabian folk tales; while the company’s R&D arm Damo Academy derives from the name of a Chinese Buddhist monk instrumental in the creation of Shaolin Kung Fu.
Grammarly announces a new tool that provides better grammar checking services for users. The tool is based on Grammarly’s AI system, which uses machine learning and natural language processing techniques. The service will be available on Chrome as an extension, and is expected to launch on Google Docs later this year.
The World Artificial Intelligence Conference 2018 kicked off yesterday in Shanghai, drawing top-tier AI scientists and entrepreneurs from China’s tech giants for discussions on AI’s latest technological frontiers and industrial applications. Synced is live at the West Bund Artistic Center in Shanghai to bring you highlights from selected Day 1 Keynotes.