Author: Tanushree Shenwai

Tanushree Shenwai
480 POSTS0 COMMENTS
https://www.marktechpost.com
Tanushree Shenwai is a consulting intern at MarktechPost. She is currently pursuing her B.Tech from the Indian Institute of Technology(IIT), Bhubaneswar. She is a Data Science enthusiast and has a keen interest in the scope of application of artificial intelligence in various fields. She is passionate about exploring the new advancements in technologies and their real-life application.

DeepMind Researchers Introduce Manipulation-Independent Representations (MIR) For Successful Cross Embodiment Visual Imitation

Recently, researchers at DeepMind have proposed manipulation-independent representations (MIR) to support successful imitation of behaviors demonstrated by previously unseen manipulator morphologies using only visual...

Google AI Introduces LEAF: A Learnable Frontend for Audio Classification

Recently, researchers at Google introduced a neural network called LEarnable Audio Frontend (LEAF) that can be initialized to approximate mel filterbanks. It is an...

Facebook AI Presents Contrastive Semi-Supervised Learning (CSL): An AI Approach For Automatic Speech Recognition (ASR) Models

Researchers from Facebook have recently introduced a Contrastive Semi-supervised Learning (CSL) approach that synthesizes pseudo-labeling and contrastive losses to improve learned speech representations’ stability. In...

Researchers from Google Research and UC Berkeley Introduce BoTNet: A Simple Backbone Architecture that Implements Self-Attention Computer Vision Tasks

Researchers at UC Berkeley and Google Research have proposed a conceptually simple yet powerful backbone architecture that incorporates self-attention for various computer vision tasks,...

Researchers at the University of Michigan and Netease Fuxi AI Lab Introduce ‘MeInGame’: A Deep Learning Technique To Automatically Create a Game Character Face...

A team of researchers from Netease Fuxi AI Lab and the University of Michigan recently created a deep learning technique called 'MeInGame' that can...

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 advantages. The...

A New Study by NVIDIA, University of Toronto, McGill, and Vector Institute Proposes Neural Representation that Enables the Real-Time Rendering of Neural SDFs

Researchers from NVIDIA, the University of Toronto, McGill University, and the Vector Institute led a study that proposed an efficient neural representation that enables...

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 networks. The...

Researchers From UC Berkeley, University of Maryland, and UC Irvine Introduce A new Contextual Calibration Approach That Significantly Improves GPT-3 Accuracy Up to 30%

A team of researchers at UC Berkeley, University of Maryland, and UC Irvine conducted a study to identify that can cause instability in the...

Facebook AI And Sorbonne University Propose A New Benchmark, CTrL, To Evaluate How Efficiently Continual Learning (CL) Models Transfer Knowledge Between Tasks And Scale...

In collaboration with Sorbonne University, Facebook AI introduced a new benchmark for continual learning (CL). This presents excellent means to improve traditional machine learning...

Google AI, DeepMind And The University of Toronto Introduce DreamerV2, The First Reinforcement Learning (RL) Agent That Outperforms Humans on The Atari Benchmark

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

DeepMind Researchers Propose Normalizer-Free ResNets (NFNets) To Achieve Large-Scale Image-Recognition Without Batch Normalization

A team of researchers at DeepMind introduces Normalizer-Free ResNets (NFNets) and demonstrates that the image recognition model can be trained without batch normalization layers....