Author: Madhur Garg

Madhur Garg
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Madhur Garg is a consulting intern at MarktechPost. He is currently pursuing his B.Tech in Civil and Environmental Engineering from the Indian Institute of Technology (IIT), Patna. He shares a strong passion for Machine Learning and enjoys exploring the latest advancements in technologies and their practical applications. With a keen interest in artificial intelligence and its diverse applications, Madhur is determined to contribute to the field of Data Science and leverage its potential impact in various industries.

Meet VTC (Virtual Token Counter): The First Fair Scheduler for Large Language Model LLMs Serving

The pursuit of fairness in Large Language Models (LLMs) is the primary concern addressed in recent research that recognizes the distinctive qualities associated with...

This Paper Explores How Deep Learning Enhances Osteoporosis Screening with Routine CT Scans

The prevalence of osteoporosis, a condition that weakens bones due to decreased bone mass, is a significant concern due to the increasing global population....

Can a Single Model Revolutionize Music Understanding and Generation? This Paper Introduces the Groundbreaking MU-LLaMA and M2UGen Models

The necessity for large-scale music datasets with natural language captions is a difficulty for text-to-music production, which this research addresses. Although closed-source captioned datasets...

Can Large Language Models Handle Longer Contexts Without Additional Training? This AI Paper Proposes SelfExtend to Stimulate LLMs’ Long Context Handling Potential

Within large language models (LLMs), one of the main challenges researchers face is the necessity of expanding the context window to achieve maximum performance...

Salesforce Research Proposes MoonShot: A New Video Generation AI Model that Conditions Simultaneously on Multimodal Inputs of Image and Text

Artificial intelligence has always faced the issue of producing high-quality videos that smoothly integrate multimodal inputs like text and graphics. Text-to-video generation techniques now...

Meet CLOVA: A Closed-Loop AI Framework for Enhanced Learning and Adaptation in Diverse Environments

The challenge of creating adaptable and versatile visual assistants has become increasingly evident in the rapidly evolving Artificial Intelligence. Traditional models often grapple with...

This AI Paper Introduces DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-based 3D Vision

Neural View Synthesis (NVS) poses a complex challenge in generating realistic 3D scenes from multi-view videos, especially in diverse real-world scenarios. The limitations of...

This AI Paper from CMU Unveils New Approach to Tackling Noise in Federated Hyperparameter Tuning

In the ever-expanding Federated Learning (FL), a critical challenge surfaces—optimizing hyperparameters essential for refining machine learning models. The intricate interplay of data heterogeneity, system...

Meta Introduces HawkEye: Revolutionizing Machine Learning ML Debugging with Streamlined Workflows

In machine learning (ML) research at Meta, the challenges of debugging at scale have led to the development of HawkEye, a powerful toolkit addressing...

This AI Research from China Proposes YAYI2-30B: A Multilingual Open-Source Large Language Model with 30 Billion Parameters

Researchers have identified a critical need for models tailored specifically for Chinese applications in large language models. The YAYI2-30B model addresses this imperative by...

Meet ML-SEISMIC: A Physics-Informed Deep Learning Approach for Mapping Australian Tectonic Stresses with Satellite Data

Understanding the current stress state of the Earth's crust is imperative for various geological applications, ranging from carbon storage to fault reactivation studies. However,...

Cohere AI Researchers Investigate Overcoming Quantization Cliffs in Large-Scale Machine Learning Models Through Optimization Techniques

Artificial intelligence's ascent of large language models (LLMs) has redefined natural language processing. However, deploying these colossal models poses a challenge, with post-training quantization...

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