Posted by Timothy Nguyen1, Research Engineer and Jaehoon Lee, Senior Research Scientist, Google Research For a machine learning (ML) algorithm to be effective, useful features must be extracted from (often) large amounts of training data. However, this process can be…
Using autonomous vehicle guidelines, a team has developed a system to improve interactions between people and robots. The way people interact safely with robots is at the forefront of today’s research related to automation and manufacturing, explains a researcher. She…
Posted by Sercan O. Arik, Research Scientist and Tomas Pfister, Engineering Manager, Google Cloud Multi-horizon forecasting, i.e. predicting variables-of-interest at multiple future time steps, is a crucial challenge in time series machine learning. Most real-world datasets have a time component,…
The human brain works differently than a computer – while the brain works with biological cells and electrical impulses, a computer uses silicon-based transistors. Scientists have equipped a toy robot with a smart and adaptive electrical circuit made of soft…
Posted by Xinying Song, Staff Software Engineer and Denny Zhou, Senior Staff Research Scientist, Google Research Tokenization is a fundamental pre-processing step for most natural language processing (NLP) applications. It involves splitting text into smaller units called tokens (e.g., words…
A maze is a popular device among psychologists to assess the learning capacity of mice or rats. But how about robots? Can they learn to successfully navigate the twists and turns of a labyrinth? Now, researchers have demonstrated they can.…
Computer engineers have developed a new AI method for accurately predicting the power consumption of any type of computer processor more than a trillion times per second while barely using any computational power itself. Dubbed APOLLO, the technique has been…
Posted by Andrew M Dai and Nan Du, Research Scientists, Google Research, Brain Team Large language models (e.g., GPT-3) have many significant capabilities, such as performing few-shot learning across a wide array of tasks, including reading comprehension and question answering…
Using neural networks to model electron interactions in molecules and materials, advancing the state-of-the-art towards the long-standing challenge of the density functional in quantum chemistry Read More
Posted by Yuanzhong Xu and Yanping Huang, Software Engineers; Google Research, Brain Team Scaling neural networks, whether it be the amount of training data used, the model size or the computation being utilized, has been critical for improving model quality…