AI Agents
Survey: AI Agent Architectures, Applications & Evaluation
New survey paper comprehensively examines AI agent system architectures, their applications across domains, and frameworks for evaluating autonomous AI behavior and capabilities.
LLM Architecture
AI Agents
Inside AI Coding Agents: Architecture, Tools, and Agentic Loops
A technical deep dive into how AI coding agents work, from tool-calling mechanisms and agentic loops to planning systems and memory architectures that enable autonomous code generation.
LLM Architecture
KV Caching Explained: The LLM Optimization Behind Real-Time AI
Key-Value caching dramatically accelerates LLM inference by storing computed attention states. Understanding this technique is essential for building efficient AI video and synthetic media applications.
AI Agents
Kaggle's AI Agent Program: Key Learnings on Production Systems
Kaggle's intensive AI agent program reveals practical insights on building production-ready systems, covering orchestration patterns, tool integration, and deployment strategies for real-world applications.
AI Agents
AI Agents Waste 80% of Compute on Inter-Agent Communication
New research reveals multi-agent AI systems spend up to 80% of computational resources on coordination overhead rather than productive work, highlighting critical efficiency challenges in agentic architectures.
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.