The invasive mosquitofish (Gambusia holbrooki) chews off the tails of freshwater fishes and tadpoles, leaving the native animals to perish while dining on other fishes’ and amphibians’ eggs. Researchers engineered a robot to scare mosquitofish away, revealing how fear alters…
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