Unsupervised Reinforcement Learning (RL), where RL agents pre-train with self-supervised rewards, is an emerging paradigm for developing RL agents that are capable of generalization. Recently, we released the Unsupervised RL Benchmark (URLB) which we covered in a previous post. URLB benchmarked many unsupervised RL algorithms across three categories — competence-based, knowledge-based, and data-based algorithms. A…
By the end of 2020, DeepMind, the UK-based artificial-intelligence lab, had already produced many impressive achievements in AI. Still, when the group’s program for predicting protein folding was released in November of that year, biologists were shocked by how well it worked. Nearly everything your body does, it does with proteins. Understanding what individual proteins do…
Last year, researchers at Data Science Nigeria noted that engineers looking to train computer-vision algorithms could choose from a wealth of data sets featuring Western clothing, but there were none for African clothing. The team addressed the imbalance by using AI to generate artificial images of African fashion—a whole new data set from scratch. Such…
In March 2016 Demis Hassabis, CEO and cofounder of DeepMind, was in Seoul, South Korea, watching his company’s AI make history. AlphaGo, a computer program trained to master the ancient board game Go, played a five-game match against Lee Sedol, a top Korean pro with the second-highest number of international championship wins to his name…
Artificial intelligence systems may be able to complete tasks quickly, but that doesn’t mean they always do so fairly. If the datasets used to train machine-learning models contain biased data, it is likely the system could exhibit that same bias when it makes decisions in practice. For instance, if a dataset contains mostly images of…
A heart attack patient, recently discharged from the hospital, is using a smartwatch to help monitor his electrocardiogram signals. The smartwatch may seem secure, but the neural network processing that health information is using private data that could still be stolen by a malicious agent through a side-channel attack. A side-channel attack seeks to gather…
Posted by Ali Kemal Sinop and Kostas Kollias, Research Scientists, Google Research In the world of networks, there are models that can explain observations across a diverse collection of applications. These include simple tasks such as computing the shortest path, which has obvious applications to routing networks but also applies in biology, e.g., where the…
Building driverless cars is a slow and expensive business. After years of effort and billions of dollars of investment, the technology is still stuck in the pilot phase. Raquel Urtasun thinks she can do better. Last year, frustrated by the pace of the industry, Urtasun left Uber, where she led the ride-hailing firm’s self-driving research…
Posted by Daniel Suo, Software Engineer and Elad Hazan, Research Scientist, Google Research, on behalf of the Google AI Princeton Team Mechanical ventilators provide critical support for patients who have difficulty breathing or are unable to breathe on their own. They see frequent use in scenarios ranging from routine anesthesia, to neonatal intensive care and…
Posted by Joshua Greaves, Software Engineer and Pablo Samuel Castro, Staff Software Engineer, Google Research, Brain Team Benchmark challenges have been a driving force in the advancement of machine learning (ML). In particular, difficult benchmark environments for reinforcement learning (RL) have been crucial for the rapid progress of the field by challenging researchers to overcome…