Author: Tanushree Shenwai

Tanushree Shenwai
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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.

Researchers At Stanford Propose Deep Learning Models For Predicting RNA Degradation Via Dual Crowdsourcing

A quick rollout of mRNA-based vaccinations against severe acute respiratory syndrome coronavirus 2 demonstrates the enormous promise of mRNA-based therapeutics as a modular therapeutic...

Google AI Propose A Novel Generative Modeling Framework Called ‘EHR-Safe’ For Generating Highly Realistic And Privacy-Preserving Synthetic EHR Data

The potential of EHR to improve patient care, integrate performance measurements into clinical practice, and streamline clinical research is enormous. Diseases may be diagnosed...

Amazon Researchers Release CoCoA-MT: A Dataset and Benchmark for Controlling formality in Machine Translation

Neural machine translation (NMT) models have steadily improved over the years, and their quality is now quite close to that of human translators. Commonly,...

Latest AI Research Introduces Contrast-Consistent Search (CCS): A Novel Approach To Detect Knowledge From Model Representations

Language models are extensively used in real-world applications, which brings exciting new opportunities. However, this also increases the stakes of AI research and introduces...

This AI Paper Proposes GhostNetV2 to Enhance Cheap Operation with Long-Range Attention

Deep neural network design is crucial in computer vision for many applications, such as image and object recognition and video analysis. AlexNet, GoogleNet, ResNet,...

A Memristor Crossbar-Based Learning Method For Activity Difference Training of Deep Learning Models

Deep learning is being widely used to solve data-analysis-related problems. These models require intensive training in physical data centers before they can be deployed...

Meta AI Releases Data2vec 2.0:  An Efficient Self-Supervised Learning For Machine Learning Tasks

Self-supervised learning is a form of unsupervised learning in which the supervised learning task is constructed from raw, unlabeled data. Supervised learning is effective...

Amazon Research Introduces MTGenEval: A New Benchmark For Evaluating Gender Bias In Machine Translation

It has been a long-held goal of the field of computer science to develop software capable of translating written text between languages. The last...

Salesforce Presents AI Summarist: A Conversational AI Tool That Helps User Manage Their Information Consumption As Per Their Work Preferences

Slack is an effective productivity tool used by professionals and teams worldwide to stay in touch and update on the latest work-related information in...

RISELab Team At UC Berkeley Open Sources Skypilot: A Novel Framework That Targets Cloud Cost Optimization for Machine Learning and Data Science

The two of the biggest problems for both large and small enterprises are analysis and storage. To begin, the rate at which Big Data...

This Artificial Intelligence (AI) Paper Presents A Study On The Model Update Regression Issue In NLP Structured Prediction Tasks

Model update regression is the term used to describe the decline in performance in some test cases following a model update, even when the...

Latest Machine Learning (ML) Research From CMU Presents Causal Imitation Learning Under Temporally Correlated Noise

A form of social learning, imitation is how new behaviors are picked up. Understanding how to communicate, interact socially, and control one's emotions while...