AI Architecture
UCSD and Together AI introduce Parcae, a stable looped transformer architecture that achieves the quality of models twice its size, potentially reshaping how efficient AI systems are built and deployed.
LLM Systems
A new research paper proposes decision-centric design for LLM systems, shifting focus from model accuracy to downstream decision quality — with implications for how AI pipelines are architected.
Multi-Agent AI
New research shows LLM agents that self-organize without predefined roles or hierarchies consistently outperform carefully designed multi-agent structures across collaborative tasks.
LLM Agents
ArXiv paper examines how design decisions in agentic LLM search systems impact both accuracy and computational costs, providing quantitative framework for budget-constrained deployments.
RAG
Most RAG failures aren't LLM issues—they're chunking failures. Learn why text segmentation strategies determine retrieval quality and how to fix common mistakes.
multimodal AI
From diffusion models to vision-language transformers, understanding the seven architectural approaches behind modern AI image generation and cross-modal synthesis.
Agentic AI
As AI agents gain autonomy to execute code and access external systems, security becomes critical. These five architectural patterns help protect agentic AI from prompt injection, privilege escalation, and data leakage.
AI Agents
New research introduces SkillNet, a framework for creating, evaluating, and connecting modular AI skills that can be composed into complex agent capabilities.
LLM Agents
Researchers introduce AriadneMem, a hierarchical memory system enabling LLM agents to maintain coherent context across extended interactions through structured episodic, semantic, and procedural memory layers.
AI research
New research introduces learned policies for context window management in AI agents, enabling more efficient handling of long-running tasks that exceed memory limits.
LLM Agents
Understanding how control flow architectures determine LLM agent behavior is crucial for building reliable AI systems. This technical deep dive explores the patterns that shape autonomous AI agents.
Vision Transformers
From ViT to Swin Transformer, these four architectures revolutionized how AI processes visual information—and they're the backbone of today's deepfake generators and detectors alike.