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Building Long-Term Memory in AI Agents

Building Long-Term Memory in AI Agents

Building Long-Term Memory in AI Agents

Nagesh Singh Chauhan

5 days ago12 min read

Quantization in LLM

Quantization in LLM

Quantization in Large Language Models(LLMs)

Nagesh Singh Chauhan

Jan 99 min read

Small Language Models(SLMs)

Small Language Models(SLMs)

Small Language Models(SLMs) in Modern AI Engineering

Nagesh Singh Chauhan

Jan 714 min read

ReAct Agents

ReAct Agents

ReAct Agents Explained: A Step-by-Step Implementation Using LangGraph

Nagesh Singh Chauhan

Jan 411 min read

mHC: Manifold-Constrained Hyper-Connections

mHC: Manifold-Constrained Hyper-Connections

mHC: Manifold-Constrained Hyper-Connections by DeepSeek

Nagesh Singh Chauhan

Jan 36 min read

LLMs in Self-Driving Cars

LLMs in Self-Driving Cars

LLMs in Self-Driving Cars: Teaching Machines to Understand the Road Like Humans

Nagesh Singh Chauhan

Jan 110 min read

GraphRAG

GraphRAG

GraphRAG Explained: Boosting RAG Performance with Knowledge Graphs

Nagesh Singh Chauhan

Dec 30, 202510 min read

AI Guardrails

AI Guardrails

AI Guardrails: Making Autonomous Agents Safe for the Enterprise

Nagesh Singh Chauhan

Dec 29, 202510 min read

Top 23 types of RAG Architectures

Top 23 types of RAG Architectures

Top 23 types of RAG Architectures

Nagesh Singh Chauhan

Dec 28, 202531 min read

Context Engineering

Context Engineering

Context Engineering: From Better Prompts to Better Thinking

Nagesh Singh Chauhan

Dec 25, 202515 min read

LLM-as-a-Judge

LLM-as-a-Judge

LLM-as-a-Judge: Rethinking How We Evaluate AI Systems

Nagesh Singh Chauhan

Dec 25, 202514 min read

The future of AI is not defined by larger models, but by better context and orchestration.

The future of AI is not defined by larger models, but by better context and orchestration.

Model Context Protocol (MCP): Engineering Context for LLMs

Nagesh Singh Chauhan

Dec 22, 202511 min read

Dragon Hatchling (BDH) is a new large language model architecture that treats computation as a network of locally interacting “neuron particles” connected by adaptive synapses, rather than as layers of dense matrices.

Dragon Hatchling (BDH) is a new large language model architecture that treats computation as a network of locally interacting “neuron particles” connected by adaptive synapses, rather than as layers of dense matrices.

The Dragon Hatchling (BDH): Bridging Transformers and Brain-Like Reasoning

Nagesh Singh Chauhan

Dec 21, 202510 min read

Introduction to Reinforcement Learning

Introduction to Reinforcement Learning

Introduction to Reinforcement Learning

Nagesh Singh Chauhan

Dec 13, 202513 min read

Understanding Game Theory and Its Impact on Decision Making

Understanding Game Theory and Its Impact on Decision Making

Understanding Game Theory and Its Impact on Decision Making

Nagesh Singh Chauhan

Dec 10, 202519 min read

Breaking the Rules: Jailbreaking in Large Language Models

Breaking the Rules: Jailbreaking in Large Language Models

Breaking the Rules: Jailbreaking in Large Language Models

Nagesh Singh Chauhan

Dec 31, 202410 min read

Byte Latent Transformer: Engineering the Next Generation of AI

Byte Latent Transformer: Engineering the Next Generation of AI

Byte Latent Transformer: Engineering the Next Generation of AI

Nagesh Singh Chauhan

Dec 21, 20247 min read

Fluid Intelligence: Understanding Liquid Neural Networks

Fluid Intelligence: Understanding Liquid Neural Networks

Fluid Intelligence: Understanding Liquid Neural Networks

Nagesh Singh Chauhan

Dec 20, 20244 min read

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CONTACT

nageshchauhanc4@gmail.com

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