Mastering Data Compression with LLMs via LMCompress
LMCompress uses large language models to achieve state of the art, lossless compression across text,
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.
Mastering Scientific and Algorithmic Discovery with AlphaEvolve
AlphaEvolve by DeepMind evolves and optimizes code using LLMs and evolutionary algorithms, enabling breakthroughs in
A Deep Dive into J1’s Innovative Reinforcement Learning
J1 by Meta AI is a reasoning-focused LLM judge trained with synthetic data and verifiable
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
