Author: Pragati Jhunjhunwala

Pragati Jhunjhunwala
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Pragati Jhunjhunwala is a consulting intern at MarktechPost. She is currently pursuing her B.Tech from the Indian Institute of Technology(IIT), Kharagpur. She is a tech enthusiast and has a keen interest in the scope of software and data science applications. She is always reading about the developments in different field of AI and ML.

Researchers at Purdue University Propose GTX: A Transactional Graph Data System for HTAP Workloads

Researchers from Purdue University have introduced GTX to address the challenge of handling large-scale graphs with high throughput read-write transactions while maintaining competitive graph...

PyTorch Researchers Introduce an Optimized Triton FP8 GEMM (General Matrix-Matrix Multiply) Kernel TK-GEMM that Leverages SplitK Parallelization

PyTorch introduced TK-GEMM, an optimized Triton FP8 GEMM kernel, to address the challenge of accelerating FP8 inference for large language models (LLMs) like Llama3...

Google AI Team Introduced TeraHAC Algorithm and Demonstrated Its High Quality and Scalability on Graphs of Up To 8 Trillion Edges

The Graph Mining team within Google Research has introduced TeraHAC to address the challenge of clustering extremely large datasets with hundreds of billions of...

PyTorch Introduces ExecuTorch Alpha: An End-to-End Solution Focused on Deploying Large Language Models and Large Machine Learning ML Models to the Edge

PyTorch recently introduced ExecuTorch alpha to address the challenge of deploying powerful machine learning models, including extensive language models (LLMs), on edge devices that...

DrBenchmark: The First-Ever Publicly Available French Biomedical Large Language Understanding Benchmark

A group of researchers in France introduced Dr.Benchmark to address the need for the evaluation of masked language models in French, particularly in the...

This AI Paper Proposes FLORA: A Novel Machine Learning Approach that Leverages Federated Learning and Parameter-Efficient Adapters to Train Visual-Language Models VLMs

Traditional methods for training vision-language models (VLMs) often require the centralized aggregation of vast datasets, which raises concerns regarding privacy and scalability. Federated learning...

This AI Research from Google Explains How They Trained a DIDACT Machine Learning ML Model to Predict Code Build Fixes

Softwares are developed through a series of iterative steps, including editing, unit testing, fixing build errors, and code reviews until the product is good...

Researchers at MIT Propose ‘MAIA’: An Artificial Intelligence System that Uses Neural Network Models to Automate Neural Model Understanding Tasks

MIT CSAIL researchers introduced MAIA (Multimodal Automated Interpretability Agent) to address the challenge of understanding neural models, especially in computer vision, where interpreting the...

MIT Researchers Use Deep Learning to Get a Better Picture of the Atmospheric Layer Closest to Earth’s Surface: Improving Weather and Drought Prediction

MIT researchers proposed working with deep learning to address the challenges of understanding and accurately modeling the planetary boundary layer (PBL) to improve weather...

Google AI Introduces SOAR: An Algorithmic Improvement to Vector Search that Introduces Effective and Low-Overhead Redundancy to ScaNN

Google AI researchers introduced ScaNN vector search library to address the need of efficient vector similarity search, which is a critical component of many...

Improving Speech Recognition on Augmented Reality Glasses with Hybrid Datasets Using Deep Learning: A Simulation-Based Approach

Google AI researchers showed how a joint model combining sound separation and ASR could benefit from hybrid datasets, including large amounts of simulated audio...

Researchers from KAUST and Sony AI Propose FedP3: A Machine Learning-based Solution Designed to Tackle both Data and Model Heterogeneities while Prioritizing Privacy

Researchers from Sony AI and KAUST have introduced FedP3 to address the challenge of federated learning (FL) in scenarios where devices possess varying capabilities...

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