MCP & A2A FAIL - not for the reasons you think #ai

How is new knowledge integrated in your neural network interconnect of your transformer architecture? Strange phenomenons happen. We explore all of them. Data efficient learning for AI. All rights authors: How new data permeates LLM knowledge and how to dilute it Chen Sun1, Renat Aksitov1, Andrey Zhmoginov1, Nolan Andrew Miller1, Max Vladymyrov1, Ulrich Rueckert1, Been Kim1 and Mark Sandler1 1 Google DeepMind Identifying and Mitigating the Influence of the Prior Distribution in Large Language Models Liyi Zhang Department of Computer Science Princeton University Princeton, NJ 08540, USA [email protected] Veniamin Veselovsky Department of Computer Science Princeton University Princeton, NJ 08540, USA [email protected] R. Thomas McCoy Department of Linguistics Yale University New Haven, CT 06511, USA [email protected] Thomas L. Griffiths Department of Psychology and Computer Science Princeton University Princeton, NJ 08540, USA [email protected] Memorization vs. Reasoning: Updating LLMs with New Knowledge Aochong Oliver Li Computer Science, Cornell University [email protected] Tanya Goyal Computer Science, Cornell University [email protected] Recommended: ------------------------- SYNTHETIC CONTINUED PRETRAINING Zitong Yang∗ Department of Statistics Stanford University Neil Band∗ Department of Computer Science Stanford University Shuangping Li Department of Statistics Stanford University Emmanuel Cand`es Department of Statistics Stanford University Tatsunori Hashimoto Department of Computer Science Stanford University Multi‑Agent Reinforcement Learning MCP - Model Context Protocol A2A Agent 2 Agent Latency Drift MARL Tutorial RL Failure Modes AI Research Distributed Systems Agent Coordination AI data pipeline