AI research
Neural Paging: AI Learns to Manage Its Own Memory Limits
New research introduces learned policies for context window management in AI agents, enabling more efficient handling of long-running tasks that exceed memory limits.
AI Architecture
LLM Agents
Agent Control Patterns: How Control Flow Shapes LLM Behavior
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
Vision Transformers Explained: 4 Architectures Powering AI Video
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.
AI Architecture
Memory Injections: The Next Evolution Beyond RAG for AI
RAG has limitations. Memory injection techniques offer AI assistants persistent, contextual memory that transforms how they understand and respond to users over time.
Multi-Agent Systems
Supervisor Agents: Orchestrating Multi-Agent AI Systems
Learn how supervisor agents coordinate specialized AI workers in multi-agent systems. This guide covers architectural patterns, LangGraph implementation, and practical orchestration strategies.
Multimodal AI
5 Multimodal AI Architectures Powering Video and Image AI
From early fusion to cross-modal attention, understanding the five core architectures behind AI systems that can see, read, and understand simultaneously—the foundation of modern synthetic media.
Transformers
Positional Encoding Methods: Why Token Order Matters in AI
Transformers process tokens in parallel, losing sequence information. Four positional encoding methods—sinusoidal, learned, RoPE, and ALiBi—solve this fundamental challenge differently.
Agentic AI
Building Production Agentic AI: Memory, Retrieval & Repair
A technical deep-dive into constructing enterprise-ready AI agents with hybrid retrieval systems, provenance tracking for citations, self-repair mechanisms, and persistent episodic memory.
LLM
New Benchmark Framework Evaluates Multi-Agent LLM Systems
Researchers introduce a unified benchmark for evaluating multi-agent LLM frameworks, providing systematic analysis of how autonomous AI agents collaborate on complex tasks.
LLM Agents
Why LLM Reasoning Breaks Down in Long-Horizon Planning Tasks
New research reveals systematic failures in how large language models approach multi-step planning, with implications for AI agents in content generation and autonomous systems.
LLM research
Small-Scale LLMs: Balancing AI Agent Performance with Sustainabil
New research explores how smaller language models can power AI agent systems while dramatically reducing computational costs and environmental impact without sacrificing capability.
LLM research
Soft Recursive Least-Squares: A New Approach to Lifelong LLM Edit
Researchers introduce S-RLS, a novel method for continuous LLM knowledge updates that avoids catastrophic forgetting through soft memory preservation instead of rigid constraints.