The article analyzes McKinsey’s latest research on why organizational restructuring alone fails to sustain productivity gains and outlines a four‑step framework—diagnosing workflow bottlenecks, removing redundancies, synchronizing information, and leveraging AI—to streamline processes, break departmental silos, and unlock lasting value.
The 2025 report catalogs startups funded by major international insurers, grouping them into AI, fintech, data security, sustainability, medical tech and other categories, and provides each company's core technology, market focus and recent financing details.
Discover how AI, especially large language models, transforms traditional web scraping by introducing semantic understanding, dynamic adaptability, and automated extraction, with in‑depth reviews of emerging tools like Crawl4AI and Browser‑use, practical code examples, best‑practice guidelines, and deployment tips for modern data collection.
This article explores how the LAS team's AI‑driven data lake solution, built on Daft for lake computing and Lance for lake storage, tackles the emerging challenges of multimodal data handling, offering faster I/O, heterogeneous CPU‑GPU scheduling, and seamless integration for AI workloads.
This article compiles a comprehensive list of high‑quality, publicly available datasets across domains such as general platforms, education, finance, health, text, and vision, providing URLs, key features, and practical usage tips to help researchers and practitioners quickly find the right data for their AI and data‑science projects.
The author evaluates the free open‑source AiPy tool through three real‑world cases—U.S. GDP trend analysis, Cambricon stock assessment, and short‑video production—showing its local, code‑free workflow for data processing, report generation, and multimedia creation while noting minor visual glitches and their fixes.
This article examines how AI large‑model training demands massive GPU clusters and low‑latency, high‑throughput networks, compares Clos/Fat‑Tree, Spine‑Leaf, Dragonfly, Group‑wise Dragonfly+ and Torus topologies, and discusses design choices for scaling to hundreds of thousands of GPUs while noting related data‑center resources.
Jeff Huber, founder of Chroma, argues that traditional RAG is obsolete, introduces context engineering as the new paradigm, and shares five practical retrieval strategies, a complete pipeline, and insights on handling context rot, memory, and generative benchmarking to build production‑grade AI applications.
This guide demonstrates using the Tongyi Lingma AI agent to automatically design an SQLite database schema, generate SQL, insert sample data, and conduct data analysis with visual charts, covering all required installations, configurations, prompts, and code snippets.
In this talk, Alibaba Cloud CIO Jiang Linquan shares how his team systematically tackled organizational, technical, and operational challenges to deploy large‑language‑model applications across dozens of enterprise scenarios, presenting real‑world case studies, a RIDE methodology, and practical metrics for success.
The article highlights a new 2024‑2025 Chinese AI large‑model market research report, noting a 2024 market size of approximately 294.16 billion CNY and a projected exceedance of 700 billion CNY by 2026, while also revealing high user engagement rates, with over half using models multiple times weekly.
This weekly tech roundup highlights Meituan’s dynamic container performance breakthrough, Huawei’s Mate X5 foldable adaptation, ByteDance’s Rspack 1.5 features, AI‑driven automation advances, MQTT and Crush terminal tools, Alibaba Cloud’s AI platform milestones, and practical guides for performance optimization and Chrome extension development.
This guide walks you through a Bash script that automatically checks for Ollama, installs it if missing, lets you choose a DeepSeek‑r1 model size, starts the Ollama service, and runs the selected model locally, complete with usage examples and a token‑cost note.
This article delves into the implementation details and optimization strategies of Retrieval‑Augmented Generation (RAG), covering document chunking, index enhancement, embedding, hybrid search, and re‑ranking, and provides practical code examples to help developers move from quick deployment to deep performance tuning.
This article explains how embedding technology converts unstructured data into vector representations, powers precise retrieval in Retrieval‑Augmented Generation (RAG), outlines the evolution of embedding models, discusses current challenges such as long‑text handling and domain adaptation, and highlights emerging solutions.
A Stanford Digital Economy Lab analysis of millions of workers shows that AI exposure is sharply reducing employment rates for 22‑25‑year‑old software developers and customer‑service reps, while older workers and low‑AI‑exposure jobs continue to grow, highlighting a split between automation‑driven and augmentation‑driven AI impacts.
This article examines why context management is critical for LLM agents, compares the strategies of OpenManus, Manus, Claude Code, and Gemini-cli, and extracts practical lessons on token limits, compression techniques, and engineering trade‑offs for building efficient, cost‑effective AI systems.
This article provides a comprehensive interview‑style analysis of Server‑Sent Events (SSE), covering its definition, 20‑year history, core features, data format, Java Spring Boot implementation, client‑side EventSource usage, detailed comparison with WebSocket and other polling techniques, and a decision guide for choosing the right real‑time communication protocol in modern AI‑driven applications.
California’s July unemployment surged to 5.5%, while blue‑collar jobs rebound, AI displaces junior roles, remote outsourcing drives senior‑developer demand, and sector‑specific hiring trends reveal a complex shift that could redefine the state’s labor landscape for years to come.
A collaborative study by Universiti Putra Malaysia and UNSW Sydney presents an AI-driven framework that combines an enhanced YOLOv11 model with a random‑forest regressor to automatically classify ceramic artifacts and predict their auction prices, demonstrating significant performance gains over traditional methods.
Feat is a high‑performance Java web service framework that offers a SpringBoot‑like development experience while delivering faster startup, lower memory usage, higher request throughput, and built‑in AI‑native and cloud‑native capabilities, making it a compelling alternative for modern backend development.
This Alibaba Cloud report examines how large AI models are moving beyond simple Q&A and office assistance to power complex financial tasks such as investment research, credit approval, and risk management, delivering cost savings, efficiency gains, better risk control, and enhanced user experiences for banks.
Meeseeks, a new benchmark released by Meituan’s M17 team, systematically evaluates large language models’ instruction‑following ability with a three‑tier framework, multi‑round self‑correction, and extensive real‑world data, revealing performance gaps among models such as OpenAI o‑series, Claude, DeepSeek and Qwen2.5.
JoyAgent‑JDGenie is an open‑source, end‑to‑end multi‑agent framework that lets users generate reports, PPTs, and data analyses directly from queries, supports easy integration of custom tools, and achieves a 75.15% accuracy on the GAIA benchmark, surpassing major competitors.
At DTCC2025 in Beijing, industry leaders showcased AI-driven innovations, vector database advances, RAG techniques, and distributed database performance breakthroughs, illustrating how databases are evolving from passive data stores into intelligent, autonomous systems that boost efficiency, scalability, and business value across sectors.
This article explains how the unique data‑driven, knowledge‑intensive, and complex nature of the financial industry makes large language models especially valuable, outlines the limitations of generic models, and shows how domain‑specific, cost‑effective models can deliver superior performance for finance.
This guide walks through installing Tongyi Lingma, generating a Qwen3‑based conversational and poetry‑creation agent with Chainlit, integrating Alipay MCP for payment requests, troubleshooting common issues, and providing useful resource links for a complete AI‑agent development workflow.
The article explains the rapid evolution of the AI application ecosystem, outlines the challenges of end‑to‑end observability for large‑language‑model services, and details how the open‑source LoongSuite suite—through non‑intrusive instrumentation for Python and Go agents and tight integration with the Dify platform—provides comprehensive, cloud‑native monitoring, tracing, and metric collection across the entire AI stack.
This article details the two‑month end‑to‑end development of Alipay's AI Travel Assistant, describing the product concept, technical background, adoption of the xUI interaction framework, gRPC streaming, Kotlin Multiplatform integration, migration challenges, performance metrics, and future roadmap.
This article details JD Retail's AI‑driven virtual try‑on system, covering business challenges, technical hurdles, core algorithmic innovations, practical results from a major fashion brand, and future directions for personalized, automated, and predictive AI try‑on in e‑commerce.
This article details how JD.com’s AI‑driven virtual fitting solution, integrated with an A/B testing platform, transformed fashion e‑commerce by generating realistic model images and videos, cutting production costs to zero, accelerating design cycles, and increasing conversion rates by over 80% during major sales events.
Elon Musk is intensifying his battle in the AI arena by suing Apple and OpenAI for alleged antitrust practices, launching a new venture called “Macrohard” to challenge Microsoft, and seeking alliances with Meta, all driven by his vision to reshape AI development and curb monopolistic control.
The article explains China’s newly released “AI+” policy, outlines its three-stage timeline through 2027, 2030 and 2035, compares it with the earlier “Internet+” initiative, and discusses how AI will reshape industries, daily life, jobs and opportunities for individuals.
Facing a multi‑year, multi‑billion‑dollar core banking migration, the quality‑assurance team compressed a 3‑month testing window to two weeks by deploying risk‑driven test prioritisation, contract‑based end‑to‑end testing, layered automation, AI‑powered defect diagnosis and production‑traffic replay, delivering a dramatic efficiency leap while maintaining zero‑tolerance data accuracy.
This resource presents a curated collection of cutting‑edge case studies and technical insights on financial large‑model data governance, proactive metadata‑based intelligent governance, data cleaning and compliance, AI‑powered operations, BI+AI innovations, and generative data analysis across leading industry players.
This article details the end‑to‑end development of Alipay’s AI Travel Assistant, covering product conception, the migration to a unified xUI 1.0 framework, the adoption of KMP for cross‑platform UI, the shift from RPC + SYNC to gRPC streaming, and the challenges of card‑ecosystem migration, all achieved within a two‑month sprint by a four‑person client team.
This resource guide presents a curated list of cutting‑edge topics—including multimodal GraphRAG, knowledge‑graph‑driven large‑model applications in finance, traditional Chinese medicine, automotive manufacturing, and knowledge‑management trends—offering insights into AI‑powered knowledge services, and invites readers to scan the QR code to download the full e‑book.
Amid the digital transformation wave, automation has evolved from simple scripted tasks to AI-powered intelligent systems, offering adaptive decision-making, dynamic workflow generation, and robust handling of UI changes, with tools like Playwright and MidScene.js enabling both web and mobile automation through advanced AI integration.
This article explains how recommendation systems work, distinguishes online services from offline computation, outlines a typical recommendation flow, and presents a three‑stage evolution (1.0, 2.0, 3.0) with design principles for stability, observability, and efficiency, culminating in a DAG‑based orchestration and traceable execution.
This article details the rapid two‑month development of Alipay’s AI Travel Assistant, covering product goals, challenges of fragmented travel services, the adoption of the xUI framework, gRPC streaming, KMP cross‑platform code, and the resulting performance and engineering benefits.
The 2025 McKinsey Quarterly special issue analyzes how leaders must expand from traditional hard skills to six core traits across character, craft, and structure, adapt to AI‑driven industry shifts, and embed a "leadership factory" to sustain resilient growth in a rapidly changing business landscape.
This article introduces the Context-as-Memory approach, which treats previously generated video frames as memory to achieve scene‑consistent interactive long video generation, and details a camera‑trajectory‑based memory retrieval mechanism that dramatically improves efficiency and performance over existing state‑of‑the‑art methods.
This article explores how programming paradigms have shifted from traditional languages to AI‑driven development, detailing AI Agent concepts, workflow versus agentic modes, single versus multi‑agent strategies, prompt versus context engineering, the reference architecture with Spring AI Alibaba, Nacos, Higress and RocketMQ, and the observability solutions built on OpenTelemetry and LoongSuite.
This article presents a curated collection of cutting‑edge case studies and research on AI‑driven data governance, large‑model data cleaning, intelligent operations, and innovative analytics from industry leaders such as JD, Alibaba Cloud, Ping An, Didi, and Kuaishou.
This guide introduces the open‑source OxyGent multi‑agent framework, walks through a quick 20‑line installation, demonstrates environment configuration, tool integration, visualization, and advanced features such as RAG, Reflexion, and distributed deployment for AI applications.
This article presents a curated list of advanced topics covering AI-driven data governance, large‑model applications, intelligent operations, and BI+AI practices from industry leaders such as JD, Alibaba Cloud, Ping An, Didi, and Kuaishou, along with a QR code to download the full e‑book.
This article analyzes how modern AI coding assistants like Gemini‑CLI and Claude Code can overcome the maintenance costs of traditional modeling, making RUP, the 4+1 view and UML viable again as powerful tools for high‑quality, AI‑augmented software development.
This article presents a curated list of cutting‑edge resources covering AI‑powered data governance, large‑model driven data cleaning, intelligent operations, and generative analytics techniques from industry leaders such as JD.com, Alibaba Cloud, Ping An Life, Didi, and Kuaishou.
This digest covers Oracle’s denial that “JavaScript” is a generic term, recent TC39 proposals, Vercel’s native support for Hono, a Vue‑React hybrid called Veact, V8’s JSON.stringify speed boost, CSS scroll‑spy tricks, masonry layout techniques, and an AI‑generated Space Invaders game.
This article details the technical practice and core thinking behind Ant Financial’s front‑end team Multi‑Agent platform “Tiangong Wànxiàng”, covering its evolution from AutoGPT to Manus, the LangGraph foundation, ReAct agents, context engineering, architecture design, and real‑world front‑end code generation capabilities.
This article reviews the AI‑driven Logos strategy for designing proteins that can bind intrinsically disordered protein regions, detailing scaffold generation, pocket specialization, RFdiffusion‑based assembly, threading, experimental validation, and its broader impact on drug discovery for diseases such as cancer and Alzheimer’s.
Data‑Juicer is an open‑source, one‑stop multimodal data processing system that provides fine‑grained operators, scalable pipelines, and ready‑made recipes to deliver high‑quality, diverse, and model‑friendly data for large language model pre‑training, fine‑tuning, and multimodal applications.
At the 2025 China Internet Conference, 360 joined the launch of the Intelligent Agent Innovation Promotion Plan, outlining a five‑level agent framework, showcasing high‑performance L3/L4 agents, and pledging to leverage its AI and security expertise to drive a collaborative intelligent‑agent ecosystem in China.
The Kuaishou AI‑driven Frontend Technology Evolution salon gathered over 300 engineers and 46,000 online viewers to showcase how AI is reshaping large‑scale front‑end development across business, R&D, and infrastructure, with deep dives into AI‑native platforms, AIDevOps, intelligent agents, AI‑powered D2C, and observability.
Claude Code introduces a "Learning Mode" that pauses at key steps, forces programmers to write code themselves, and offers explanatory and learning output styles, aiming to prevent AI‑induced skill atrophy while providing a more educational coding assistant.
This article walks through designing and implementing an AI code review tool using Node.js, GitLab webhooks, and large language models, covering prompt engineering, diff augmentation, token management, response parsing, and automated comment posting to streamline the review process.
The 2025 H1 AI Core Achievements and Trends report reveals how agents are reshaping productivity, models are gaining inference power and becoming smaller, reinforcement learning is overtaking pre‑training, and industry competition is intensifying, with China and the US narrowing their technology gap.
DynamicFace introduces a controllable face‑swapping framework that leverages composable 3D facial priors, dual‑stream identity injection, and a FusionTVO module to achieve superior image and video quality, identity preservation, and temporal consistency, outperforming existing state‑of‑the‑art methods on benchmark datasets.
Omni-Effects introduces a unified framework that combines LoRA‑based expert mixture models and spatially aware prompts to generate multiple, precisely placed visual effects in video, supported by the new Omni‑VFX dataset and evaluation suite, demonstrating superior spatial control and diversity over prior single‑effect methods.
This article explores Tomoro’s Lumos data‑intelligent agent, detailing its multi‑agent architecture, technical design, practical implementations, and performance optimizations that enable seamless, low‑threshold big‑data self‑service analysis powered by AI.
This guide systematically breaks down Anthropic's official prompt‑engineering recommendations—clear instructions, multishot examples, chain‑of‑thought prompting, XML structuring, response pre‑filling, prompt chaining, long‑context handling, extended thinking, and practical code snippets—showing how to unlock Claude's full potential across complex tasks.
This guide outlines a step‑by‑step process to create a natural‑language‑driven AI system that helps high‑school students fill out college application forms, recommends majors using the Tongyi Qianwen model, and stores data in Supabase, covering frontend design with Vue3, backend services with Python, and integration details.
This article introduces the AI‑powered mind‑map‑MCP tool, explains its features, installation via npm or npx, usage through Coze API and Trae configuration, showcases generated mind‑maps, and outlines future enhancements for better NLP understanding and broader integrations.
The article reflects on how prompt engineering is reshaping software development, questioning whether developers will become prompt engineers, emphasizing the continued importance of coding fundamentals, and urging a balanced use of AI to preserve creativity and problem‑solving skills.
This article presents a comprehensive, high‑throughput OCR invoice processing solution that combines distributed system design, Spring Boot asynchronous execution, Tesseract deep optimization, multi‑engine fusion, structured data extraction, performance tuning, Kubernetes deployment, and security compliance.
This article explains what tokens are in large language models, how they are counted and priced, compares tokenization methods across major models, and provides practical guidelines and code examples for optimizing token usage and selecting the appropriate model for different scenarios.
Google’s Imagen 4 family—Ultra, Standard, and Fast—introduces unprecedented realism, reliable text rendering, multilingual prompts, and higher instruction fidelity, while the article explains each model’s trade‑offs and offers concrete prompt‑engineering techniques to help creators harness this next‑generation AI image generator.
This article demonstrates how AI tools like Coze and Cursor can automate the generation, validation, and execution of test cases, turning tedious manual processes into fast, accurate, and integrated workflows that boost testing efficiency and coverage.
This article explains the logical and physical architecture of AI compute centers, detailing the division into access, security, network, management, out‑of‑band, AI compute cluster, and general compute zones, and describes the four network planes—parameter, sample, business, and management—required for high‑performance AI workloads.
The report analyzes how AI is reshaping every stage of game creation and experience, highlighting developer adoption rates, advances in asset generation, narrative design, testing, commercialization, and the broader market transformation driven by generative AI technologies.
This comprehensive guide outlines a six‑step roadmap—building a solid technical foundation, gaining hands‑on experience, developing leadership and communication skills, acquiring business acumen, establishing a personal brand, and pursuing senior certifications—to help senior engineers accelerate their journey to a Chief Technology Officer role within five years.
This comprehensive guide shows how development teams can adopt the AI coding assistant CodeBuddy to streamline every stage of the software lifecycle—from diagnosing workflows and selecting tools to automating design, coding, testing, deployment, and continuous improvement—delivering measurable productivity gains and higher code quality.
This article systematically examines the root causes of hallucinations in large language models, evaluates their pros and cons, and presents a comprehensive set of optimization techniques—including prompt engineering, RAG, sampling tweaks, supervised fine‑tuning, LoRA, RLHF, chain‑of‑thought reasoning, and agent/workflow designs—to build more reliable and trustworthy AI applications.
The article analyzes the FilterLLM approach, which augments a frozen LLM with billions of learnable user tokens to predict a full‑user interaction probability distribution in a single forward pass, dramatically speeding up cold‑start recommendation while preserving recommendation quality across multiple benchmarks.
This article explores how large language models break the natural‑language‑to‑SQL barrier, outlines the challenges of NLP‑driven data retrieval, compares Text2SQL and Text2DSL approaches, and proposes a unified data service and metric platform to power enterprise‑grade ChatBI solutions.
Zhou Hongyi’s article highlights AI’s pivotal role in the new technological wave, outlines the challenges of large models, introduces a five‑level taxonomy of intelligent agents, showcases 360’s swarm‑based deployments, and stresses the urgent need for security‑focused agents as AI reshapes enterprises.
The 2025 Google Developer Conference highlighted AI breakthroughs like Gemini 2.5 and Gemma, introduced AI-enhanced Flutter, Android, and Cloud tools, and showcased Chinese developers leveraging these technologies to achieve global impact and social good.
This article details how Zhaozhuan transformed its customer‑service robot from relying on external NLP providers to a fully self‑developed AI solution, covering technical choices, model training, RAG integration, deployment strategies, and future directions.
This article explains what an AI agent is, outlines its four core modules—perception, memory, planning, and action—describes the role of large language models, compares software development generations, discusses memory implementations, planning methods like ReAct and Plan‑and‑Solve, and covers evaluation, cost analysis, and differences between agents and workflows.
A recent Nature paper demonstrates how a data‑driven workflow that combines protein‑sequence mining, experimental synthesis, and machine‑learning optimization can automatically design super‑adhesive hydrogels with tunable strength, elasticity and durability for underwater applications.
GitHub’s recent leadership shake‑up, its integration into Microsoft’s new CoreAI group, and the rapid expansion of AI‑driven tools like Copilot signal a fundamental shift from a developer‑centric code‑hosting platform to a central AI development hub, reshaping the future of software creation.
This article walks through extending the K8s Chat command‑line tool by adding an ‘analyze event’ command that gathers warning‑level events and pod logs, stores them in a map, and sends the information to a large‑language model via OpenAI’s API to receive actionable troubleshooting recommendations, while also suggesting further enhancements such as self‑healing and visualization.
The Q2 2025 State of AI report analyzes Chinese AI labs’ rapid progress across language models, open‑source weights, and multimodal generation, showing a shrinking performance gap with US leaders, detailed benchmark scores, ecosystem classifications, and emerging competitive dynamics.
This article explains how the Model Context Protocol (MCP) solves the AI integration "M×N" problem by providing a universal language for AI applications and tools, outlines its technical principles, showcases practical case studies, and promotes the accompanying book that teaches MCP from theory to implementation.
This guide walks through deploying the open‑source Coze AI Agent platform using Volcengine ECS's one‑click service, customizing large language models, building a DeepResearch workflow, and explains why open‑sourcing the stack accelerates the collaborative future of AI agents.
This article examines how empathetic user research and AI‑driven features transformed a resume‑building tool for older domestic‑service workers, detailing behavior analysis, process simplification, multimodal interaction, and trust‑building AI assistants that dramatically increased completion rates and platform value.
This article explains how massive Transformer‑based large language models compress text data into mathematical representations, why scale, self‑attention, and training paradigms enable emergent general intelligence, and walks through tokenization, embedding, multi‑layer attention, architecture choices, energy costs, and hallucination mitigation.
This article details Bilibili's multi-layer storage architecture and Alluxio‑based cache acceleration for large‑scale AI model training, covering challenges of high‑throughput, low‑latency file access, metadata scalability, fault tolerance, and the engineering solutions that boosted I/O performance up to ten‑fold.
This article explores a hybrid approach that combines traditional static application security testing (SAST) with large language models (LLM) to automatically detect business‑logic vulnerabilities, detailing the methodology, implementation stages, experimental results, and the challenges of integrating AI into code security analysis.
This article introduces four notable open‑source AI projects—Google's Gemini CLI, the voice‑interactive XiaoZhi chatbot, the comprehensive AI Engineering Hub, and the GPT‑Pilot programming companion—detailing their key features, generous free quotas, star counts, supported hardware, and providing direct GitHub repository links for each.
The Q2 2025 State of AI Highlights Report analyzes benchmark data, model performance, and market dynamics, revealing five major industry trends, the rise of AI agents, rapid advances in language, vision, and speech models, and shifting hardware acceleration strategies that shape the future of artificial intelligence.
GitHub CEO Thomas Dohmke warns that developers who do not adopt AI risk becoming obsolete, outlining research on AI adoption stages, new essential skills, shifting education, and a changing job market that still predicts strong growth but with fundamentally different roles.
This week’s tech roundup highlights major AI breakthroughs—including OpenAI’s GPT‑5 launch, the SWE‑Swiss code‑fixing model from Peking University and ByteDance, Pinduoduo’s AI talent hiring surge, the emerging Agentic Web paradigm, Google’s Genie 3 world model, multimodal railway design AI, DJI’s first robot vacuum, AI‑enhanced smart glasses, and a new humanoid robot perception system—all reflecting rapid advances across generative, multimodal, and applied AI.
This newsletter curates five technical articles covering AI‑enhanced frontend productivity, a comparative deep dive into tree shaking across major bundlers, innovative AI code generation for e‑commerce frontends, a rapid AI‑assisted component refactor, and efficiency gains in ad‑monitoring development.
This guide walks developers through Dify's native MCP integration—explaining the protocol, showing step‑by‑step configuration, demonstrating usage in agents and chatflows, and presenting real‑world cases like data analysis and travel planning—to accelerate AI application development.
A senior engineer recounts how AI‑generated Terraform and Kubernetes code exposed a production database, leaked secrets, and created costly outages, then shares concrete mistakes, security‑first templates, validation pipelines, and AI‑pair‑programming practices to keep DevOps work safe and reliable.
The article chronicles half a century of database history, analyzing the rise and collapse of systems like Informix, Sybase, FoxPro, HBase, and dBase, while examining how Oracle, Microsoft, and IBM are adapting to cloud and AI, and forecasting the forces reshaping the future of data storage.
This article examines the varied attitudes toward AI coding assistants, outlines four common CTO response strategies, and provides a practical framework for evaluating costs, security, stability, and technical debt while guiding teams through responsible adoption and cultural impact.
This article explains how the Transformer model replaces sequential RNN processing with parallel self‑attention, detailing its core components, positional encoding, encoder‑decoder workflow, industry impact, and surprising facts such as training speed gains and energy efficiency.
Learn step‑by‑step how to create an AI‑driven zodiac horoscope chatbot on Alibaba Cloud Baileian, configure the Alipay MCP payment service, set up secure KMS credentials, and achieve a complete commercial pay‑to‑use loop from user query to transaction confirmation.
