LLM Architecture

AI Agents

Structured Cognitive Loop: Merging Symbolic and Neural AI

New research introduces a cognitive architecture that bridges symbolic control and neural reasoning in LLM agents, offering a structured framework for more reliable and interpretable AI systems with explicit planning and execution phases.

LLM Architecture

Uncertainty Architecture for Robust LLM Applications

A technical framework for designing LLM applications that explicitly handle uncertainty, covering architectural patterns, confidence scoring, and system design principles for building more reliable AI systems.

Agentic AI

Small Language Models Dominate Agentic AI Systems

Small language models are outperforming larger counterparts in agentic AI workflows due to speed, cost efficiency, and specialized task performance. Technical analysis reveals why compact models excel at autonomous decision-making.

LLM Architecture

RAG vs Fine-Tuning: The LLM Architecture Decision

Comprehensive technical analysis of retrieval-augmented generation and fine-tuning strategies for LLMs, exploring when to use each approach, their technical trade-offs, and emerging hybrid architectures that combine both methodologies.

LLM Architecture

LLM Architecture Evolution: Transformers to MoR Explained

Deep dive into the technical progression of large language model architectures, from the foundational Transformer through Mixture of Experts to cutting-edge Mixture of Routers, examining how each innovation addresses scaling and efficiency challenges.