Alibaba's official tech channel, featuring all of its technology innovations.
This guide walks you through installing the Moltbot AI assistant on Alibaba Cloud's lightweight application server, configuring Baidu's Bailei API key, opening required ports, generating access tokens, and accessing the chat interface, plus a quick overview of the pre‑installed Shadow Cloud Computer image.
This article details the design, challenges, and performance gains of an AI‑driven rental recommendation system that replaces a multi‑agent architecture with a single LLM using dynamic tool‑use, introduces a two‑stage reinforcement‑learning pipeline, and achieves sub‑second latency and higher accuracy for complex rental scenarios.
The article examines common pitfalls of AI programming assistants—premature exits, fragile single‑prompt workflows, costly re‑prompting, and context loss—explains that these stem from unreliable LLM self‑evaluation, and introduces the Ralph Loop (also called Ralph Wiggum Loop) as a robust, stop‑hook‑driven solution that forces continuous iteration until explicit, verifiable completion criteria are met.
This article details the engineering challenges and solutions for deploying a 3.5 billion‑parameter MoE LLM in Taobao's search relevance pipeline, covering large‑batch scheduling, dynamic load balancing, intra‑batch KV‑Cache reuse, and MoE kernel tuning to meet sub‑second latency requirements.
This article explains the common difficulties of writing effective prompts, introduces the open‑source prompt‑optimizer skill that automatically selects and refines professional prompt frameworks, and provides step‑by‑step instructions for preparing materials, packaging the skill for Claude and Chrome, and installing it via GitHub repositories.
This article walks through turning a Meta Ray‑Ban AR headset into an AI‑powered traffic enforcement prototype by combining a lightweight iOS client, Alibaba Cloud Function Compute AgentRun, prompt engineering, and serverless tools to perform OCR, rule checking, and real‑time feedback.
This article explains the history, core concepts, and practical CLI commands of OpenSpec, a spec‑driven development tool that integrates with AI assistants, detailing project initialization, workflow steps, quality control, directory structure, common pitfalls, and comparisons with other specification frameworks to help developers adopt a more efficient, documentation‑first workflow.
Quest redesigns long‑running task execution by combining model capability, context management, dynamic reminders, and a minimal Bash‑centric toolset into a closed‑loop Agent architecture that lets AI generate, verify, and deliver complete software artifacts without constant human intervention.
This article explains what Anthropic Skills are, compares them with MCP, and provides a step‑by‑step, best‑practice workflow—including repository setup, OpenSkills commands, naming conventions, and executable skill patterns—to help developers quickly create robust, efficient Skills for Claude and other AI agents.
This article explains how a hierarchical sparse‑attention framework redesigns KVCache storage across GPU, CPU, and remote memory, eliminates bandwidth and capacity bottlenecks, and enables efficient inference for 128K‑token and larger contexts with dramatically reduced GPU memory usage and higher throughput.
