Official account of the DataFun community, dedicated to sharing big data and AI industry summit news and speaker talks, with regular downloadable resource packs.
The article outlines DataWorks' evolution from a decade‑long big‑data governance platform to an AI‑driven Copilot and autonomous Agent system, detailing its technical foundations, tool‑adaptation layer, context engineering, security safeguards, and future vision of a professional, open, and intelligent big‑data development ecosystem.
This article explores the challenges and state of long‑term memory for AI agents, reviews mainstream industry solutions such as RAG, HRM, Titans and Engram, and proposes a four‑layer memory architecture with data acquisition, organization, utilization, and feedback loops to enable agents that remember and forget like humans.
The article analyzes costly data‑platform failures in large enterprises, contrasts traditional data middle‑platforms with Palantir’s ontology‑based approach, and explains a three‑layer architecture that turns raw data into automated business decisions, illustrated with real‑world case outcomes.
This article introduces OxyGent, an open‑source Python framework released in July 2025 that provides atomic orchestration, infinite extensibility, and multi‑modal tool integration for building high‑performance, enterprise‑grade multi‑agent systems, covering its architecture, quick‑start workflow, prompt management, memory bank, and future roadmap.
The article examines the memory and latency challenges of 1750‑billion‑parameter LLM inference, introduces the xLLM framework’s Slidebatching and PD‑separation scheduling strategies, and details how these techniques achieve up to 35% system‑throughput gains and 52% SLO compliance improvements in real‑world multi‑priority workloads.
The OpenClaw v2026.3.7 release introduces webhook compatibility fixes, typing‑feedback UI, prompt‑caching that cuts token usage by 33%, smarter model routing, native support for domestic LLMs, and persistent binding storage for container deployments, making the platform far more reliable and cost‑effective for enterprise automation.
OpenClaw v2026.3.7 brings webhook compatibility fixes, private‑message typing feedback, a 33% token‑saving prompt‑cache, smarter model routing, seamless integration of domestic LLMs such as DeepSeek, Doubao and Qwen, and persistent bindings for Docker deployments, dramatically improving stability, cost efficiency and scalability for enterprise AI agents.
The article examines why costly traditional data middle platforms often become data swamps, contrasts them with Palantir's ontology‑based approach that acts like a navigation system, and outlines a three‑layer architecture that turns data into automated business actions, delivering multi‑hundred‑percent ROI.
This article outlines MaxCompute's 15‑year transformation from a traditional structured‑compute engine to an AI‑native data warehouse, detailing its data, heterogeneous compute, and model capabilities, showcasing three core ability pillars, real‑world case studies, and future development directions.
OpenClaw v2026.3.7 introduces Feishu webhook compatibility fixes, prompt‑cache cost reductions, smarter model routing, domestic model connectors, and persistent binding for container deployments, turning the tool from a geek toy into a reliable enterprise‑grade AI‑agent platform.
