May 10, 2025 Comments0 FacebookTwitterPinterestWhatsApp Education Fine-tuning vs. in-context learning: New research guides better LLM customization for real-world tasks By AI Observer More from this stream A Deep Technical Dive into Next-Generation Interoperability Protocols: Model Context Protocol... AI Observer - 5 hours ago Enterprise AI Without GPU Burn: Salesforce’s xGen-small Optimizes for Context, Cost,... AI Observer - 5 hours ago ByteDance Open-Sources DeerFlow: A Modular Multi-Agent Framework for Deep Research Automation AI Observer - 5 hours ago Microsoft Researchers Introduce ARTIST: A Reinforcement Learning Framework That Equips LLMs... AI Observer - 5 hours ago Recomended A Deep Technical Dive into Next-Generation Interoperability Protocols: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP) As autonomous systems... Enterprise AI Without GPU Burn: Salesforce’s xGen-small Optimizes for Context, Cost, and Privacy Language processing in... ByteDance Open-Sources DeerFlow: A Modular Multi-Agent Framework for Deep Research Automation ByteDance has released... Microsoft Researchers Introduce ARTIST: A Reinforcement Learning Framework That Equips LLMs with Agentic Reasoning and Dynamic Tool Use LLMs have made... ZeroSearch from Alibaba Uses Reinforcement Learning and Simulated Documents to Teach LLMs Retrieval Without Real-Time Search Large language models... Understanding the Dual Nature of OpenAI Why it matters:...