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.

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

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

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

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

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...

Meta Reality Labs Research Introduces Sonata: Advancing Self-Supervised Representation Learning for 3D Point Clouds

3D self-supervised learning (SSL) has faced persistent challenges in developing semantically meaningful point representations suitable for diverse applications with minimal supervision. Despite substantial progress...

This AI Paper Introduces the Kolmogorov-Test: A Compression-as-Intelligence Benchmark for Evaluating Code-Generating Language Models

Compression is a cornerstone of computational intelligence, deeply rooted in the theory of Kolmogorov complexity, which defines the minimal program needed to reproduce a...

Beginner’s Guide to Deploying a Machine Learning API with FastAPI

In this guide, you will learn how to deploy a machine learning model as an API using FastAPI. We will create an API that...

This AI Paper Introduces PLAN-AND-ACT: A Modular Framework for Long-Horizon Planning in Web-Based Language Agents

Large language models are powering a new wave of digital agents to handle sophisticated web-based tasks. These agents are expected to interpret user instructions,...

This AI Paper Introduces GRPO-based Open-RS: A Low-Cost Reinforcement Learning Framework to Enhance Reasoning in Small Language Models

One particular focus on large language models has been improving their logical thinking and problem-solving skills. Reinforcement learning (RL) is increasingly used in this...

Qwen Releases the Qwen2.5-VL-32B-Instruct: A 32B Parameter VLM that Surpasses Qwen2.5-VL-72B and Other Models like GPT-4o Mini

​In the evolving field of artificial intelligence, vision-language models (VLMs) have become essential tools, enabling machines to interpret and generate insights from both visual...

This AI Paper from NVIDIA Introduces Cosmos-Reason1: A Multimodal Model for Physical Common Sense and Embodied Reasoning

Artificial intelligence systems designed for physical settings require more than just perceptual abilities—they must also reason about objects, actions, and consequences in dynamic, real-world...

This AI Paper from UC Berkeley Introduces TULIP: A Unified Contrastive Learning Model for High-Fidelity Vision and Language Understanding

Recent advancements in artificial intelligence have significantly improved how machines learn to associate visual content with language. Contrastive learning models have been pivotal in...