19 results for "system architecture"
ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems
Despite a century of empirical memory research, existing AI agent memory systems rely on system-engineering metaphors (virtual-memory paging, flat LLM storage, Zettelkasten notes), none integrating pr…
Claude Leak Confirms It: LLM Systems Are Architecture, Not Prompts (Orca)
Agents should execute whenever possible — runtime for composable AI agent skills - gfernandf/agent-skills…
Day 21: Affiliate Marketing System - AI System Design in Seconds
Affiliate Marketing System Architecture Building a scalable affiliate marketing...…
Behind the Scenes of a Self-Evolving AI: The Architecture of Tian AI
Deep dive into Tian AI's architecture — three-layer thinking engine, 34GB SQLite knowledge base, self-modification system, and evolution engine.…
A Decoupled Human-in-the-Loop System for Controlled Autonomy in Agentic Workflows
AI agents are increasingly deployed to execute tasks and make decisions within agentic workflows, introducing new requirements for safe and controlled autonomy. Prior work has established the importan…
SoccerRef-Agents: Multi-Agent System for Automated Soccer Refereeing
Refereeing is vital in sports, where fair, accurate, and explainable decisions are fundamental. While intelligent assistant technologies are being widely adopted in soccer refereeing, current AI-assis…
Structural Enforcement of Goal Integrity in AI Agents via Separation-of-Powers Architecture
Recent evidence suggests that frontier AI systems can exhibit agentic misalignment, generating and executing harmful actions derived from internally constructed goals, even without explicit user reque…
Right-to-Act: A Pre-Execution Non-Compensatory Decision Protocol for AI Systems
Current AI systems increasingly operate in contexts where their outputs directly trigger real-world actions. Most existing approaches to AI safety, risk management, and governance focus on post-hoc va…
Interoceptive machine framework: Toward interoception-inspired regulatory architectures in artificial intelligence
This review proposes an integrative framework grounded on interoception and embodied AI-termed the interoceptive machine framework-that translates biologically inspired principles of internal-state re…
FastOMOP: A Foundational Architecture for Reliable Agentic Real-World Evidence Generation on OMOP CDM data
The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM), maintained by the Observational Health Data Sciences and Informatics (OHDSI) collaboration, enabled the harmonisation of el…
Multi-Agent AI Systems Are Eating Single Agents
Single-agent architectures hit a wall the moment your task needs planning, research, and execution in parallel. Multi-agent systems solve this — but most tutorials skip the hard parts. This guide does…
Comparison of upcoming x86 unified memory systems
AMD Gorgon halo summer this year. 15% faster memory clock speeds / bandwidth, than strix halo . Intel nova lake ax expected early next year. 2027 summer: AMD Medusa Halo , 50% performance improvement …
The Controllability Trap: A Governance Framework for Military AI Agents
Agentic AI systems - capable of goal interpretation, world modeling, planning, tool use, long-horizon operation, and autonomous coordination - introduce distinct control failures not addressed by exis…
HeLa-Mem: Hebbian Learning and Associative Memory for LLM Agents
Long-term memory is a critical challenge for Large Language Model agents, as fixed context windows cannot preserve coherence across extended interactions. Existing memory systems represent conversatio…
Analytica: Soft Propositional Reasoning for Robust and Scalable LLM-Driven Analysis
Large language model (LLM) agents are increasingly tasked with complex real-world analysis (e.g., in financial forecasting, scientific discovery), yet their reasoning suffers from stochastic instabili…
LEGO: An LLM Skill-Based Front-End Design Generation Platform
Existing LLM-based EDA agents are often isolated task-specific systems. This leads to repeated engineering effort and limited reuse of successful design and debugging strategies. We present LEGO, a un…
MetaGAI: A Large-Scale and High-Quality Benchmark for Generative AI Model and Data Card Generation
The rapid proliferation of Generative AI necessitates rigorous documentation standards for transparency and governance. However, manual creation of Model and Data Cards is not scalable, while automate…
An Analysis of the Coordination Gap between Joint and Modular Learning for Job Shop Scheduling with Transportation Resources
Efficient job-shop scheduling with transportation resources is critical for high-performance manufacturing. With the rise of "decentralized factories", multi-agent reinforcement learning has emerged a…
Adaptive ToR: Complexity-Aware Tree-Based Retrieval for Pareto-Optimal Multi-Intent NLU
Multi-intent natural language understanding requires retrieval systems that simultaneously achieve high accuracy and computational efficiency, yet existing approaches apply either uniform single-step …