This paper presents a multi-agent AI architecture that achieves 92.1% reliability by organizing specialized AI agents into teams with opposing roles and hierarchical oversight, similar to corporate organizational …
GEPA introduces a novel prompt optimization approach that uses natural language reflection and Pareto-based evolutionary search to optimize compound AI systems, achieving superior performance compared to reinforcement …
A randomized controlled study examining how AI assistance affects skill formation in software development, finding that while AI can improve productivity, it significantly impairs conceptual understanding, code reading, …
Research reveals that while 92% of companies plan to increase AI investments, only 1% have reached AI maturity. The biggest barrier isn’t employee readiness—who are already using AI extensively—but leadership …
This paper introduces Agentic Variation Operators (AVO), which replace traditional evolutionary search operators with autonomous AI agents that can iteratively optimize code through self-directed exploration, achieving …
JPMorgan Chase implemented an AI platform called COiN (Contract Intelligence) using NLP and machine learning to automate legal document analysis, saving over 360,000 hours annually and reducing compliance errors by 80%. …
Comprehensive research by the UK Department for Science, Innovation & Technology reveals that only 16% of UK businesses currently use AI, with natural language processing being the most common application. The study …
Anthropic shares the engineering challenges and lessons learned from building Claude’s Research feature, a multi-agent system that uses multiple AI agents working in parallel to explore complex topics more …
This research proposes using distributed systems theory as a principled framework for designing and evaluating LLM teams, demonstrating that coordination challenges like consistency conflicts, communication overhead, and …
A comprehensive guide to using Gemini 2.5 Flash Image (Nano Banana) for generating consistent imagery from archive photos, demonstrating how to build a prompt-based pipeline that preserves character features across …
DRAGON-AI is a novel method that employs Large Language Models and Retrieval Augmented Generation to automatically generate ontology components including relationships, definitions, and logical axioms. The system …
This comprehensive review examines the bidirectional relationship between AI techniques and ontologies, exploring how machine learning contributes to automated ontology construction while ontologies enhance AI system …
A comprehensive exploration of how private data can be extracted from AI systems through various attack vectors including fine-tuned models, RAG systems, and vector embeddings. Demonstrates practical attacks against LLMs …
