Latest from Google AI – Alpa: Automated Model-Parallel Deep Learning

Posted by Zhuohan Li, Student Researcher, Google Research, and Yu Emma Wang, Senior Software Engineer, Google Core Over the last several years, the rapidly growing size of deep learning models has quickly exceeded the memory capacity of single accelerators. Earlier models like BERT (with a parameter size of < 1GB) can efficiently scale across accelerators…

Latest from MIT Tech Review – Meta has built a massive new language AI—and it’s giving it away for free

Meta’s AI lab has created a massive new language model that shares both the remarkable abilities and the harmful flaws of OpenAI’s pioneering neural network GPT-3. And in an unprecedented move for Big Tech, it is giving it away to researchers—together with details about how it was built and trained. “We strongly believe that the…

UC Berkeley – Designing Societally Beneficial Reinforcement Learning Systems

Deep reinforcement learning (DRL) is transitioning from a research field focused on game playing to a technology with real-world applications. Notable examples include DeepMind’s work on controlling a nuclear reactor or on improving Youtube video compression, or Tesla attempting to use a method inspired by MuZero for autonomous vehicle behavior planning. But the exciting potential…

Latest from MIT : A one-up on motion capture

From “Star Wars” to “Happy Feet,” many beloved films contain scenes that were made possible by motion capture technology, which records movement of objects or people through video. Further, applications for this tracking, which involve complicated interactions between physics, geometry, and perception, extend beyond Hollywood to the military, sports training, medical fields, and computer vision…

Latest from Google AI – Extracting Skill-Centric State Abstractions from Value Functions

Posted by Dhruv Shah, Intern, and Brian Ichter, Research Scientist, Robotics at Google Advances in reinforcement learning (RL) for robotics have enabled robotic agents to perform increasingly complex tasks in challenging environments. Recent results show that robots can learn to fold clothes, dexterously manipulate a rubik’s cube, sort objects by color, navigate complex environments and…

Latest from MIT : Engineers use artificial intelligence to capture the complexity of breaking waves

Waves break once they swell to a critical height, before cresting and crashing into a spray of droplets and bubbles. These waves can be as large as a surfer’s point break and as small as a gentle ripple rolling to shore. For decades, the dynamics of how and when a wave breaks have been too…

Latest from MIT Tech Review – Modern data management, the hidden brain of AI

Artificial intelligence (AI) is the darling of businesses and governments because it not only promises to add tens of trillions to the gross domestic product (GDP), but it comes with all the excitement of action-packed movies or dopamine-drenched gaming. We are mesmerized by computer vision, natural language processing, and the uncanny predictions of recommendation engines….

Latest from MIT : How can we reduce the carbon footprint of global computing?

The voracious appetite for energy from the world’s computers and communications technology presents a clear threat for the globe’s warming climate. That was the blunt assessment from presenters in the intensive two-day Climate Implications of Computing and Communications workshop held on March 3 and 4, hosted by MIT’s Climate and Sustainability Consortium (MCSC), MIT-IBM Watson…

Latest from MIT : Aging Brain Initiative awards fund five new ideas to study, fight neurodegeneration

Neurodegenerative diseases are defined by an increasingly widespread and debilitating death of nervous system cells, but they also share other grim characteristics: Their cause is rarely discernible and they have all eluded cures. To spur fresh, promising approaches and to encourage new experts and expertise to join the field, MIT’s Aging Brain Initiative (ABI) this…

Latest from MIT : Machine learning, harnessed to extreme computing, aids fusion energy development

MIT research scientists Pablo Rodriguez-Fernandez and Nathan Howard have just completed one of the most demanding calculations in fusion science — predicting the temperature and density profiles of a magnetically confined plasma via first-principles simulation of plasma turbulence. Solving this problem by brute force is beyond the capabilities of even the most advanced supercomputers. Instead,…