Author: Nikhil

Nikhil
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Nikhil is an intern consultant at Marktechpost. He is pursuing an integrated dual degree in Materials at the Indian Institute of Technology, Kharagpur. Nikhil is an AI/ML enthusiast who is always researching applications in fields like biomaterials and biomedical science. With a strong background in Material Science, he is exploring new advancements and creating opportunities to contribute.

This AI Paper from ByteDance Introduces MegaScale-Infer: A Disaggregated Expert Parallelism System for Efficient and Scalable MoE-Based LLM Serving

AI Infrastructure
Large language models are built on transformer architectures and power applications like chat, code generation, and search, but their growing scale with billions of...

This AI Paper Introduces an LLM+FOON Framework: A Graph-Validated Approach for Robotic Cooking Task Planning from Video Instructions

AI Paper Summary
Robots are increasingly being developed for home environments, specifically to enable them to perform daily activities like cooking. These tasks involve a combination of...

This AI Paper Introduces Inference-Time Scaling Techniques: Microsoft’s Deep Evaluation of Reasoning Models on Complex Tasks

AI Paper Summary
Large language models are often praised for their linguistic fluency, but a growing area of focus is enhancing their reasoning ability—especially in contexts where...

This AI Paper from Anthropic Introduces Attribution Graphs: A New Interpretability Method to Trace Internal Reasoning in Claude 3.5 Haiku

AI Paper Summary
While the outputs of large language models (LLMs) appear coherent and useful, the underlying mechanisms guiding these behaviors remain largely unknown. As these models...

This AI Paper Introduces a Short KL+MSE Fine-Tuning Strategy: A Low-Cost Alternative to End-to-End Sparse Autoencoder Training for Interpretability

AI Paper Summary
Sparse autoencoders are central tools in analyzing how large language models function internally. Translating complex internal states into interpretable components allows researchers to break...

This AI Paper Introduces FASTCURL: A Curriculum Reinforcement Learning Framework with Context Extension for Efficient Training of R1-like Reasoning Models

AI Paper Summary
Large language models have transformed how machines comprehend and generate text, especially in complex problem-solving areas like mathematical reasoning. These systems, known as R1-like...

This AI Paper Unveils a Reverse-Engineered Simulator Model for Modern NVIDIA GPUs: Enhancing Microarchitecture Accuracy and Performance Prediction

AI Infrastructure
GPUs are widely recognized for their efficiency in handling high-performance computing workloads, such as those found in artificial intelligence and scientific simulations. These processors...

The Complete Beginner’s Guide to Terminal/Command Prompt

Basic Tutorials
The terminal (on Mac/Linux) or command prompt (on Windows) is a powerful tool that allows you to interact with your computer using text commands...

How to Use Git and Git Bash Locally: A Comprehensive Guide

Basic Tutorials
Table of contentsIntroductionInstallationWindowsmacOSLinuxVerifying InstallationGit Bash BasicsNavigation CommandsFile OperationsKeyboard ShortcutsGit ConfigurationAdditional ConfigurationsBasic Git WorkflowInitializing a RepositoryChecking StatusStaging FilesCommitting ChangesBranching and MergingWorking with BranchesMerging BranchesHandling Merge...

This AI Paper Introduces Diversified DPO and ORPO: Post-Training Methods to Boost Output Diversity in Creative Writing with LLMs

AI Paper Summary
Creative writing is a domain that thrives on diversity and imagination. Unlike fact-based or task-specific writing, where a single correct output may exist, creative...

A Beginners Guide to Using Visual Studio Code for Python

Basic Tutorials
Visual Studio Code (VSCode) is a powerful, free source-code editor that makes it easy to write and run Python code. This guide will walk...

Empowering Time Series AI: How Salesforce is Leveraging Synthetic Data to Enhance Foundation Models

AI Paper Summary
Time series analysis faces significant hurdles in data availability, quality, and diversity, critical factors in developing effective foundation models. Real-world datasets often fall short...
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