Google AI and UC Berkeley Introduce PAIRED: A Novel Multi-Agent Approach for Adversarial Environment...

The success of any machine learning technique is hugely dependent on its training data. In the case of reinforcement learning (RL), we...

Google and Facebook Introduce ‘LazyTensor’ That Enables Expressive Domain-Specific Compilers

Researchers at Facebook and Google introduce a new technique called ‘LazyTensor’ that combines eager execution and domain-specific compilers (DSCs) to employ both...

Google AI Introduces Lyra: A Novel Low-Bitrate Speech Codec For Speech Compression

Researchers at Google AI recently introduced Lyra, a high-quality, very low-bitrate speech codec that makes voice communication available even on the slowest...

Google AI Introduces ‘Model Search’: An Open Source Platform For Finding Optimal Machine learning...

Google AI has announced the release of Model Search, a platform that will help researchers develop machine learning (ML) models automatically and efficiently....

University of Wisconsin-Madison, UC Berkeley, and Google Brain Introduce Nystromformer: A Nystrom-based Algorithm for...

Early days of research in Natural language processing established long-term dependencies. It also brought the vanishing gradient problem in front of us...
Behaviors learned by DreamerV2 for some of the 55 Atari games. These videos show images from the environment. Video predictions are shown below in the blog post.

Google AI, DeepMind And The University of Toronto Introduce DreamerV2, The First Reinforcement Learning...

Google AI, in collaboration with DeepMind and the University of Toronto, has recently introduced DreamerV2. It is the first Reinforcement Learning (RL)...

Google AI Researchers Introduce Tracln- An Easy Approach To Estimate Training Data Influence

In a paper published at NeurIPS 2020, Google AI researchers have proposed a simple, scalable approach to estimate training data influence- TracIn. The quality of a Machine...

Google AI launches Crowdsourcing Adverse Test Sets for Machine Learning (CATS4ML) Data Challenge

Researchers at Google AI have recently launched Crowdsourcing Adverse Test Sets for Machine Learning (CATS4ML) Data Challenge. This challenge focuses on improving...

Taking Accessibility of Mobile Apps to the Next Level with IconNet, A Vision-Based Object...

Researchers at Google AI recently developed a technology called IconNet that enables Android users to have hands-free control over their mobile devices...

Researchers From Google Brain Introduces Symbolic Programming And A Python Library Called PyGlove For...

A team of researchers from Google Brain introduces a new way of programming automated machine learning (AutoML) based on symbolic programming. The...
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