AI
Google's Agent2Agent and Anthropic's Model Context Protocol (MCP) - A Comparative Analysis
The AI apps work non deterministically based on their artificial intelligence. To ensure decision making is robust and reliable in this procedure, systems like Agent2Agent and MCP come into the picture. These let AI “teams” collaborate like skilled professionals.
Self-Host Llama 3 70B on Your Own GPU Cluster: A Step-by-Step Guide
Hosting Llama 3 70B on your own GPU cluster isn’t just about bragging rights—it’s about unlocking the freedom to tweak, experiment, and own your AI setup. But let’s be real: This isn’t for the faint of heart. You’ll need grit, patience, and a willingness to troubleshoot like a pro.
How to Deploy Large Language Models (LLMs) - A Step-by-Step Guide
Imagine a world where machines don’t just follow commands but converse, create, and problem-solve alongside humans. This isn’t science fiction—it’s the reality shaped by Large Language Models (LLMs), the crown jewels of modern artificial intelligence
FlashMLA: Revolutionizing Efficient Decoding in Large Language Models through Multi-Latent Attention and Hopper GPU Optimization
In this study, we'll do a comprehensive exploration of FlashMLA’s architecture, technical innovations, and real-world impact, with detailed explanations of foundational concepts like the KV cache and hardware constraints.
GRPO Group Relative Policy Optimization Tutorial
Group Relative Policy Optimization (GRPO) is a reinforcement learning (RL) algorithm designed to optimize large language models (LLMs) for reasoning tasks. Introduced in the DeepSeekMath and DeepSeek-R1 papers, GRPO eliminates the need for a value function model, reducing memory overhead by 40-60% compared to Proximal Policy Optimization (PPO).
DeepScaleR-1.5B isnt just good for its size – it’s rewriting the rules
DeepscaleR, an open-source model demonstrates how reinforcement learning (RL) can unlock exceptional performance in small models through innovative scaling strategies. Let’s dive into the key insights from their groundbreaking research.
Comparative Analysis of AI Agent Frameworks with DSPy: LangGraph, AutoGen and CrewAI
This article compares DSPy with these frameworks across cost, learning curve, code quality, design patterns, tool coverage, and enterprise scalability, incorporating insights from industry benchmarks and developer feedback .
8 Techniques to Optimize Inference for Large Language Models: A Comprehensive Research Review
Deploying Large Language Models (LLMs) like GPT-4, Llama 3, or Mixtral for real-world applications demands careful optimization to balance performance, cost, and scalability. This article delves into advanced techniques for accelerating LLM inference, providing technical insights, empirical results, and practical recommendations.