Building Simulations with a Single Prompt on GPT-5
Unlock game and simulation development with GPT-5. A single prompt can create complex, interactive applications,
ADaSci Expert
Aniruddha Shrikhande
Aniruddha Shrikhande is an AI enthusiast and technical writer with a strong focus on Large Language Models (LLMs) and generative AI. Committed to demystifying complex AI concepts, he specializes in creating clear, accessible content that bridges the gap between technical innovation and practical application. Aniruddha's work explores cutting-edge AI solutions across various industries. Through his writing, Aniruddha aims to inspire and educate, contributing to the dynamic and rapidly expanding field of artificial intelligence.
100% Accuracy of AI Agents Is Unrealistic — Here Are the Reasons
Expecting 100% accurate responses from AI agents is unrealistic due to language ambiguity, data gaps,
Hands-On RAG with AWS Bedrock and S3 Vector Store
Turn HR documents into a smart chatbot using Amazon S3 Vectors and Bedrock. Upload to
Chartered Data Scientist (CDS™)
The highest distinction in the data science profession. Not just earn a charter, but use it as a designation.
A Hands-On Guide to Building Multi-Agent Systems Using n8n
n8n is an open-source, low-code workflow automation platform that enables seamless integrations between applications using
Deep Dive into Open Source RL for Large Scale LLMs DAPO
DAPO is an open-source RL framework that enhances LLM reasoning efficiency, achieving top-tier AIME
A Hands on Guide to Compact Vision Language Models using SmolDocling
SmolDocling, a 256M VLM, enables efficient document conversion using DocTags to preserve structure while reducing
A Deep Dive into Chain of Draft Prompting
Chain of Draft (CoD) optimizes LLM efficiency by reducing verbosity while maintaining accuracy. It cuts
Mastering Multi-Head Latent Attention
DeepSeek’s MLA reduces KV cache memory via low-rank compression and decoupled positional encoding, enabling efficient
The DRAMA Framework Explained – From Large LLMs to Efficient Small Dense Retrievers
DRAMA enhances dense retrieval by leveraging LLM-based data augmentation and pruning to create efficient, high-performance
AI Co-Scientist Systems – A Multi Agent System for Research
AI co-scientists powered by Gemini 2.0 accelerate scientific discovery by generating and ranking hypotheses using
Benchmarking AI on Software Tasks with OpenAI SWE-Lancer
SWE-Lancer benchmarks AI models on 1,400+ real freelance software engineering tasks worth $1M, evaluating their
Step-Video-T2V for Text to Video Generation
Step-Video-T2V, a cutting-edge text-to-video model with 30B parameters, enhances video quality using Video-VAE, Video-DPO, and
Advancing Multilingual Text Embeddings through Nomic Embed Text V2
Nomic Embed Text V2 revolutionizes text embeddings with Mixture-of-Experts (MoE), enhancing efficiency, multilingual support, and
