The article explains how the Model Context Protocol (MCP) introduces Streamable HTTP as a modern, bidirectional transport that overcomes the one‑way, session‑less limitations of Server‑Sent Events, providing richer data formats, built‑in session management, and better resilience for AI assistants.
In a candid interview, Thoughtworks CTO Rachel Laycock explains that while AI is reshaping the tech industry, it cannot eliminate the need for skilled developers, especially when tackling legacy code, technical debt, and cloud migration, and she outlines how generative AI tools can augment—not replace—human expertise.
This roundup highlights Tencent's GPU capacity for future models, Alibaba's fully disclosed Qwen3 technical report, Anaconda's unified AI platform, Parasoft's AI‑enhanced SOAtest, and Google Cloud's GA of the Apigee API Management Operator, offering a snapshot of current AI advancements.
DeepMind's AlphaEvolve, a Gemini-powered coding agent, combines large language models with an evolutionary framework to automatically discover, optimize, and evolve advanced algorithms, achieving notable gains in data‑center scheduling, TPU design, matrix multiplication, and even solving longstanding mathematical problems.
This article examines the unique employment challenges faced by job seekers in third‑tier and county‑level cities in China and proposes design principles—visual noise reduction, direct information delivery, plain‑language phrasing, localized location cues, trust signals, and dialect‑aware AI—to make recruitment apps more accessible and effective for these users.
The curl project founder warns that a flood of AI‑generated, low‑quality vulnerability reports is draining developers' time, eroding trust, and prompting new verification measures, highlighting broader risks for the open‑source ecosystem.
This article introduces the AntV‑developed mcp-server-chart MCP Server, explains how to set up the VSCode + Cline + Node environment, configure the server via JSON, and demonstrates its ability to generate network and bar charts through large‑model function calls, while also discussing current limitations and future improvements.
This article presents StableReinforce and the R1-Reward model, demonstrating how reinforcement learning techniques can stabilize training and significantly improve the performance of multimodal reward models for large language models across several benchmarks.
This article presents a large‑scale advertising risk‑control solution that combines deep‑research paradigms, domain‑graph constraints, and large language models to enable explainable, responsible, and high‑precision fraud detection, detailing system architecture, challenges, demo workflow, and future directions.
This article details the design and implementation of an AI‑driven Intelligent SQL Assistant that automates query parsing, index recommendation, execution‑plan visualization, and supports SQL generation, diagnosis, and explanation across multiple dialects, while outlining its layered architecture, core modules, code examples, and future enhancements.
This article analyzes NVIDIA's evolving AI supercomputer architectures—detailing the H100‑based 256‑GPU SuperPod, the GH200‑based 256‑GPU SuperPod with integrated Grace CPU, and the GB200‑based 576‑GPU SuperPod—examining their NVLink and InfiniBand topologies, bandwidth limits, and scalability challenges.
At Sequoia Capital’s third AI summit, 150 top AI founders agreed that the next wave of AI will stop selling mere tools and start selling measurable outcomes, reshaping pricing models, product design, operating‑system‑style agents, and even the very structure of organizations.
This article provides a systematic security analysis of the Model Context Protocol (MCP), demonstrating how malicious tool definitions, prompt injection, command injection, and over‑privileged implementations enable data theft, arbitrary code execution, and large‑scale attacks against AI agents and their users.
This article reviews five free text‑to‑speech solutions—AI易视频, Google TTS, Natural Reader, Balabolka, and Speech2Go—detailing their features, language support, installation needs, and unique capabilities to help creators choose the right tool for narration, translation, or multi‑character audio production.
This talk explores the technical challenges of applying large language models and knowledge graphs in finance, discusses solutions such as RAG enhancements, graph‑guided retrieval, multimodal extensions, and presents future research directions including multimodal graph integration, agentic systems, and decision‑making applications.
This guide shows how to combine ELK, DeepSeek’s LLM API, and a Feishu chatbot in Python to automatically collect, analyze, classify, and alert on system logs, using a config file, custom utilities, and a simple historical fault database for intelligent DevOps monitoring.
In a recent AI Ascent presentation, OpenAI researcher Dan Roberts explained how scaling laws for both pre‑training and reinforcement learning reveal a new test‑time dimension of model performance, showcased the capabilities of the o1 and o3 models, and outlined a massive compute‑scaling strategy aimed at creating AI systems that can reason for years like Einstein.
This guide explains how to use Baidu Baige's AI heterogeneous computing platform to deploy the eight‑model Qwen3 family—including dense and MoE variants—via a one‑click process, covering resource configuration, inference acceleration options, and post‑deployment service access.
This article examines five major LLM‑driven AI agent planning and execution patterns—ReAct, Plan‑and‑Execute, Static Workflow, Static Workflow with local intelligence, and modular hierarchical planning—detailing their mechanisms, code examples, strengths, weaknesses, suitable scenarios, and optimization techniques.
This article provides a detailed Chinese‑to‑English summary of Andrej Karpathy’s 7‑hour LLM tutorial, covering chat process analysis, tokenization, pre‑training data pipelines, model architecture, training strategies, post‑training fine‑tuning, reinforcement learning, chain‑of‑thought reasoning, and current industry applications.
The article introduces Chain‑of‑Recursive‑Thoughts (CoRT), explains how recursive self‑evaluation enhances large language model reasoning, outlines its workflow, shares GitHub resources, compares it with existing CoT methods, and reports experimental results using Mistral 3.1 24B.
An award‑winning joint project by Shanghai Jiao Tong University and Ant Group unveils a multimodal foundation model and advanced detection techniques that dramatically improve AI‑driven content risk governance across massive online services.
Tao Zhe Xuan’s new YouTube channel demonstrates how an AI‑driven workflow using GitHub Copilot and the Lean proof assistant produced a 33‑minute “blind” proof of a Magma equation, highlighting the potential of semi‑automated theorem proving while preserving human readability.
This article demonstrates how large language models can augment business development engineers by providing data insight, automating algorithm training, and enabling low‑cost rapid product prototyping, thereby transforming traditional backend‑focused roles into full‑stack, AI‑enhanced innovators.
Redis 8.0 GA introduces a suite of new data structures—including a Vector Set for AI, native JSON support, and several probabilistic types—enhances the query engine with secondary indexes and full‑text/vector search, delivers significant performance gains, and re‑embraces open source by adding an OSI‑approved AGPLv3 license.
During the May Day holiday, Fields Medalist Tao Zhuoxuan used ChatGPT to develop an open‑source Python tool that automatically verifies asymptotic estimates involving arbitrary positive parameters, shared the GitHub repository, and then promoted his AI community, paid courses, and related services.
JManus is an open‑source, Java‑centric AI agent platform built on Spring AI Alibaba that lets developers quickly create, configure, and run multi‑agent applications with support for major large language models, a web UI, and advanced PLAN‑ACT reasoning capabilities.
Researchers from ShanghaiTech and USC introduced the compact inference model Tina, which leverages low‑rank adaptation and reinforcement learning to achieve comparable or superior performance to large SOTA models while reducing post‑training and evaluation costs to just $9, a 99.6% savings over traditional approaches.
This article presents a comprehensive overview of Zhihu Direct Answer, describing its AI‑driven search architecture, RAG framework, query understanding, retrieval, chunking, reranking, generation, evaluation mechanisms, engineering optimizations, and the professional edition, while sharing concrete performance‑boosting practices and future development plans.
This tutorial walks through building a Retrieval‑Augmented Generation (RAG) system by combining LangChain for document processing, Elasticsearch’s vector store with the ELSER v2 model for semantic search, and Higress as a cloud‑native AI gateway, complete with deployment scripts, code examples, and query testing.
The Vue ecosystem has taken a major step into artificial intelligence by adding llms.txt files to its documentation sites and releasing the vitepress-plugin-llms, which automatically generates AI‑friendly metadata to improve developer efficiency and document parsing.
NVIDIA announced native Python support in its CUDA toolkit, enabling developers to write GPU‑accelerated code directly in Python, detailing the new programming model, JIT‑based architecture, performance benefits, and the broader impact on AI development and the developer ecosystem.
The article examines how pre‑generating structured context for codebases can overcome the uncertainty and quality issues of traditional Retrieval‑Augmented Generation, outlines the technical and business challenges of RAG, compares existing code‑search tools, and introduces AutoDev’s Context Worker as a practical solution.
Redis 8.0 GA introduces major performance enhancements, adds AI‑focused vector and probabilistic data structures, expands native JSON support, improves the query engine with secondary indexes, and re‑embraces open source by offering an AGPLv3 licensing option.
Redis 8.0 marks a major shift with its return to a true open‑source license (AGPLv3), the consolidation of Redis Open Source, a suite of advanced modules like Vector Search and TimeSeries, and a Spring Boot compatibility guide, turning Redis from a simple cache into a versatile data platform.
The article outlines a five‑layer AI multi‑agent architecture covering hierarchical command chains, human‑in‑the‑loop security barriers, decentralized peer‑to‑peer networks, industrial‑grade pipeline processing, and data‑transformation alchemy, each illustrated with concrete enterprise and autonomous‑driving examples.
IDC’s April 2024 report shows China’s automotive cloud market reaching 6.51 billion RMB in the second half of 2024, with a 27.4% YoY growth, and highlights Baidu Cloud’s 34.5% share in the 16.34 billion RMB autonomous‑driving solution market, driven by AI advances and expanding compute investments.
JD Retail’s engineering team tackles hard AI problems by replacing a monolithic reward model with specialized small models for ad‑image generation, deploying an LLM‑driven query‑expansion pipeline that lifts conversion rates, and pruning text‑to‑image transformers using FFT and RDP to boost throughput 40% without loss, while building comprehensive evaluation tools and a semantic smart‑assistant.
The Gemini 2.5 Pro 05‑06 update dramatically improves code‑generation performance, tops the WebDev Arena leaderboard over Claude 3.7 Sonnet, and introduces unique video‑to‑web multimodal abilities, while still facing UI bugs and naming inconsistencies ahead of the upcoming Google I/O conference.
PPTAgent, an open‑source AI tool jointly developed by the Chinese Academy of Sciences and Shanghai Jiexin Technology, automatically creates high‑quality PowerPoint slides by analyzing reference decks, extracting layout patterns, and iteratively editing content with a self‑correction mechanism, achieving superior content, design, and coherence scores compared to existing methods.
The 2024 Google DORA report shows that AI adoption in software development raises documentation, code quality, and review speed, yet simultaneously reduces delivery throughput by 1.5% and stability by 7.2%, highlighting both productivity gains and new operational challenges for DevOps teams.
The article introduces Nacos 3.0’s major upgrades—including migration to JDK 17 and Spring Boot 3.4.1, new Admin APIs, default authentication, AI‑focused Model Content Protocol, distributed lock, fuzzy listening, and native xDS support—while also promoting an enterprise‑level backend engineering booklet priced at 11.9 CNY.
This article details the design, implementation, and practical usage of a Model Context Protocol (MCP) service for Ant Design components, explaining how to extract component documentation, define MCP tools and prompts, integrate with AI models like Claude, and improve frontend development efficiency.
DeepSeek has quietly open‑sourced a new mathematics‑focused large language model, DeepSeek‑Prover‑V2 (available in 671B and 7B variants), achieving 88.9% on MiniF2F and strong results on PutnamBench, alongside the high‑quality ProverBench dataset and a novel recursive theorem‑proving pipeline.
This article explores the MCP platform’s data service capabilities, detailing its core components—Resources, Prompts, and Tools—and demonstrates how its Text2SQL feature enables natural‑language queries to retrieve table schemas, perform data sampling, and execute complex relational analyses across multiple database tables.
This article examines Japan’s looming 500,000 IT talent shortage, Microsoft’s AI‑driven overhaul of M365, a fraud case involving outsourced development, Redis’s return to open‑source licensing, and Google’s rollout of Gemini AI for children, highlighting the broader implications for the tech industry.
The article recaps the 3rd eBPF Developer Conference in Xi'an, highlighting talks on BPF‑on‑MPTCP, system‑wide PGO, bperf, autonomous‑driving use cases, and AI‑driven observability, while sharing the author's insights on continuous profiling, SysOM, and future challenges of scaling eBPF with large models.
This guide shows how to integrate Zabbix with a locally deployed DeepSeek large language model via Webhook, enabling automatic analysis of alert causes and solutions, feeding results back to operators through dashboards or enterprise WeChat, and dramatically reducing MTTR and manual effort.
JetBrains has released its purpose‑built code‑completion large language model, Mellum, as an open‑source project on Hugging Face, highlighting its focus on specialized code‑completion tasks, low runtime costs, support for many programming languages, and its potential for AI/ML researchers and educators.
This article outlines the major technical upgrades in Nacos 3.0—including JDK 17, Spring Boot 3.4.1, enhanced Admin API, default authentication, MCP for AI models, unified namespaces, distributed‑lock beta, fuzzy listening, and xDS support—while also promoting a series of AI‑focused products, community groups, and paid resources for developers.
DeepSeek‑Prover‑V2‑671B, a 671 billion‑parameter AI model released on Hugging Face, dramatically advances formal mathematical theorem proving with MoE architecture, FP8 quantization, 163 k token context, superior performance over GPT‑4 Turbo and other models, and broad implications for research and industry.
This article introduces the Qwen3 family of open‑source large language models, details their architecture, parameter counts, multilingual support, and benchmark performance, and provides step‑by‑step instructions for deploying them with frameworks like SGLang, vLLM, and local runtimes such as Ollama and LMStudio.
The SecretFlow open‑source community and Chengdu Smart City Research Institute co‑host a deep‑tech meetup in Chengdu, featuring leading experts from Ant Group, UESTC, and industry partners who will explore privacy‑computing principles, SPU technology, federated learning, and real‑world financial and governmental use cases through talks and hands‑on workshops.
This article clarifies three major misunderstandings about the Model Context Protocol (MCP), explaining that it does not require large‑model support, works even without function‑calling capabilities, and is not natively built into models, while outlining how MCP standardizes context augmentation through a black‑box server architecture.
In a candid a16z interview, Meta CTO Andrew Bosworth predicts that AI will overhaul the app‑centric model, ushering in AR glasses and intent‑driven services that could render traditional app stores obsolete while outlining the technical, market and regulatory challenges ahead.
This article demonstrates how to transform a traditional Spring Boot book‑management service into an AI‑driven MCP service by importing Spring AI dependencies, configuring proxy and MCP server settings, annotating service methods with @Tool, registering them, and exposing a chat endpoint that lets large language models query and manipulate book data through natural language.
This article summarizes Zuoyebang's infrastructure leader Dong Xiaocong's presentation on the challenges of AI inference demand and supply, and describes the design and implementation of a unified compute network—including trusted networking, multi‑region container scheduling, and traffic routing—to efficiently serve large‑scale AI models.
A recent interview collection reveals how mandatory AI tools in software firms generate overwhelming negativity, low morale, and productivity pitfalls, while also highlighting the speed benefits of AI for scaffolding and offering practical guidance for developers to retain control over their code.
This comprehensive tutorial shows how to use the Model Context Protocol (MCP) to transform AI assistants like Claude, ChatWise, or Cherry Studio into powerful tools that can access your computer’s files, fetch real‑time information, interact with software, and even control smart devices, with clear step‑by‑step instructions, code examples, and troubleshooting tips.
This article explains the Model Call Protocol (MCP), its purpose, core implementation code, and step-by-step workflow for integrating AI function calls, comparing it with custom solutions, and discussing practical considerations such as accuracy, cost, and ecosystem impact.
The article examines the new Streamable HTTP transport layer introduced in the Model Context Protocol (MCP), comparing it with the traditional HTTP+SSE approach and demonstrating its superior stability, performance, and client simplicity through architectural analysis, session management details, and extensive benchmark results.
The article examines the rapid rise of AI interview software, highlighting its appeal to job seekers, the potential for cheating, expert criticism, associated risks, and the need for balanced, ethical approaches to ensure fairness in recruitment.
This article examines how to build AI‑friendly software architectures by aligning team coding standards, layered design, domain‑driven terminology, prompt‑engineering techniques, project‑specific rules, validation‑first development, and continuous refactoring to improve both human and generative‑AI productivity.
This article explores how AI‑powered low‑code platforms transform UX design by enabling designers to turn concepts into functional prototypes, reducing development effort, accelerating validation cycles, and reshaping the workflow from creative ideation to product delivery through real‑world case studies.
OpenAI announced new shopping capabilities for ChatGPT, improving product recommendation, visual presentation, and direct purchase links, while Alibaba released the Qwen3 series of large and MoE language models with detailed parameter counts and benchmark performance, highlighting rapid advancements in consumer‑focused AI applications.
The article examines China's rapid shift toward domestic databases across finance, government, and energy sectors, highlighting how DBAs must upgrade from reactive fire‑fighting to strategic architects by mastering distributed systems, AI‑driven automation, cloud‑native tools, and open‑source community collaboration.
This article surveys the latest AI breakthroughs, covering ChatGPT‑4o's native image generation, Runway's Gen‑4 video model, Midjourney V7, AnimeGamer's infinite anime simulation, JiMeng 3.0 poster creator, ComfyUI‑Copilot workflow assistant, DomoAI's voice‑image digital humans, Ready AI web builder, DeepSeek‑V3, and Alibaba's ultra‑realistic 3D digital human model.
DP-Recon leverages generative diffusion priors and a visibility‑guided SDS loss to achieve high‑fidelity, compositional 3D scene reconstruction from extremely sparse images, delivering superior geometry, texture, and text‑driven editing capabilities demonstrated on benchmark datasets and real‑world indoor scenarios.
This guide explains how to set up a Model Context Protocol (MCP) server, define its resources, tools, and prompt templates, implement both manual and WebSocket versions of a Snake game client, create MCP clients in TypeScript and Python, debug with the inspector, and integrate the server with AI agents for autonomous gameplay.
ByteDance’s ByteBrain team showcases how large‑model AI, operations research, and system‑level innovations have produced award‑winning papers and billions of yuan in cost savings while improving on‑call efficiency, database estimation, and cloud infrastructure reliability.
Version 3.0 of Nacos upgrades to JDK 17 and Spring Boot 3.4.1, introduces AI‑focused MCP, enhanced Admin API with default authentication, unified namespaces, beta distributed lock and fuzzy listening features, and native xDS protocol support, while highlighting related open‑source SpringBoot + Vue e‑commerce projects.
Jeff Dean’s 2024 ETH Zurich talk traces fifteen years of AI breakthroughs—from the rise of neural networks and back‑propagation, through large‑scale distributed training, TPUs, Transformers, sparse MoE models, and advanced prompting techniques—showing how scaling compute, data, and clever software have driven today’s powerful Gemini models.
This guide shows how to select a model in LM Studio, expose a local port, start the HTTP server, and interact with it via curl commands, covering quick model listing, chat requests, and the difference between streaming and full‑response modes.
A 21‑year‑old Chinese founder’s startup Cluely raised seed funding for an AI tool that covertly assists users in interviews, coding challenges, and sales calls, sparking ethical debates, university disciplinary action, and rapid market traction with over $3 million ARR.
LiAuto announced that its self‑developed vehicle operating system, HaloOS, will be fully open‑sourced starting April 23, with a phased release covering vehicle control, intelligent driving, communication middleware, and virtualization components, aiming to build an active community for technology sharing and collaboration.
This week’s GitHub star surge highlights five open‑source AI projects—a free Cursor VIP tool, a one‑stop video translation and dubbing platform, a privacy‑first meeting‑minutes assistant, an open‑source personal finance OS, and a highly customizable AI chatbot SDK—each with key features, deployment options, and repository links.
The article outlines four critical mindset transformations—adopting an AI‑first workflow, embracing commander‑level strategic thinking, continuously learning from AI, and building a composite human‑AI collaboration framework—to help developers stay competitive and extract maximum value from emerging AI programming tools.
The article analyzes the new Streamable HTTP transport introduced in MCP (Model Context Protocol) PR #206, comparing it with the legacy HTTP+SSE approach across stability, TCP connection usage, request success rate, latency, and client‑side code complexity, and shows why Streamable HTTP is superior in high‑concurrency cloud‑native deployments.
The article outlines China’s recent push to internationalize IT standards through the 2024‑2027 Action Plan, details the development and adoption of ITU DevOps and AI‑enhanced DevOps standards, and explains the emerging BizDevOps framework that integrates business and technology for agile digital transformation.
The team built a low‑cost AI‑powered code‑review assistant that injects line‑level comments into GitLab merge requests, using LLMs via Feishu, iterating quickly through MVP and optimization phases, achieving 64 integrations, 150+ daily comments, feedback‑driven prompt refinement, and demonstrating high ROI for small‑to‑medium teams while outlining future IDE and rule‑based extensions.
ByteDance Data Platform’s recent breakthroughs in database research—spanning query‑level Bayesian tuning, adaptive stream‑processing parallelism, and learned cardinality estimation—were highlighted by two papers accepted at VLDB 2025 and ICDE 2025, showcasing significant performance gains and real‑world deployments.
This article presents a complete Gomoku web application built with Vue 3 on the front end and NestJS on the back end, featuring customizable pieces, stylish UI, AI opponents of varying difficulty, and real‑time LAN multiplayer using Socket.io, along with detailed code examples and architectural explanations.
This article shows how the Cursor IDE’s built‑in AI can generate complete PlantUML code for various system diagrams—from RBAC models and login flows to payment processes, DDD layering, and C4 architecture—dramatically cutting manual drawing time and keeping documentation in sync with code.
The article surveys the Algorithmic Foundations of Engineering R&D series, tracing NLP’s evolution from rule‑based systems to today’s multimodal large‑model era, reviewing core machine‑learning and deep‑learning techniques, transformer breakthroughs, representation learning, optimization methods, and emerging research such as retrieval‑augmented generation and AI agents.
At the second Wuhan Cybersecurity Innovation Forum, Ant Group unveiled its AI‑powered "parallel security slice" approach for threat detection, detailing a multi‑layer defense system that leverages a DKCF framework, large‑model reasoning, and knowledge graphs to improve accuracy, reduce false alarms, and uncover unknown threats in complex digital enterprises.
Researchers from UCLA and Meta AI introduce d1, a two‑stage post‑training framework that combines supervised fine‑tuning and a novel diffu‑GRPO reinforcement‑learning algorithm to enable efficient reasoning in masked diffusion large language models, achieving state‑of‑the‑art performance on multiple math and logic benchmarks.
This article explains the original purpose of Retrieval‑Augmented Generation, why it remains essential despite advances in large‑context LLMs, and how combining RAG with fine‑tuning, longer context windows, and model‑context protocols yields more scalable, accurate, and privacy‑preserving AI systems.
This article presents a selection of challenging interview questions frequently asked of big‑data candidates—covering long‑tail task identification, the role of Apache Paimon, handling underperforming cluster nodes, data scale limits, and large‑model fundamentals—along with concise explanations and resources for further study.
DeepSeek leverages AI to automate multi‑source integration, data cleaning, warehouse modeling, real‑time processing, governance, metadata management, reporting, cloud scaling, and decision support, offering twelve distinct use cases that boost efficiency, intelligence, and scalability of modern data warehouses.
Amid a U.S. antitrust trial that could force Google to divest Chrome, OpenAI’s ChatGPT product lead says the company would consider buying the browser, while both firms navigate past negotiations and future AI‑driven search ambitions.
The campus AI Agent competition showcased how large‑language‑model‑powered agents can reason, deceive, and collaborate in a social deduction game, revealing model performance trends, participant insights, and future directions for multi‑agent AI research.
Baidu’s SRE digital‑immune system, evolved into an AI‑powered intelligent immunity platform, quantifies and mitigates risk across thousands of services by integrating data‑driven monitoring, rule‑based detection, and large‑model GraphRAG knowledge mining, cutting degradation cases by ~40% and shifting operations from reactive troubleshooting to proactive, data‑centric quality assurance.
Elasticsearch 9.0, released on April 15, 2025, builds on Lucene 10.1.0 to deliver major performance gains, introduces Better Binary Quantization, Elastic Distributions of OpenTelemetry, LLM observability, AI‑driven attack discovery, enhanced ES|QL, and is available via Elastic Cloud with deployment tips and examples.
This article outlines the complete cloud computing technology stack, from foundational resource virtualization and shared infrastructure to advanced services such as AI/ML platforms, serverless computing, edge and quantum cloud offerings, highlighting their roles, key components, typical scenarios, and why enterprises should choose the right combination for cost, scalability, and security.
This article explains the fundamentals of Retrieval‑Augmented Generation, demonstrates how to create and query vector indexes using StarRocks, shows how DeepSeek provides embeddings and answer generation, and walks through a complete end‑to‑end RAG pipeline with code examples and a web UI.
This step‑by‑step guide explains how to deploy a 1Panel MCP Server using Docker, enable SSE mode, and integrate it into Dify via the Agent strategy plugin, covering required configurations, common pitfalls, and testing procedures.
The article examines how the COVID‑19 pandemic accelerated digital transformation, highlighting four lessons for technology leaders—understanding consumer expectations, eliminating infrastructure fragmentation, building resilience through scalability, and embracing AI with high‑quality data—to create a secure, interoperable ecosystem that drives better customer experiences.
This article presents a comprehensive AI‑driven pipeline that converts 2D video into immersive 3D spatial video by leveraging monocular depth estimation, depth‑warping novel view synthesis, a multi‑branch inpainting module, a large‑scale StereoV1K dataset, and efficient MV‑HEVC compression, with results validated at ICME 2025 and deployed in JD Vision services.
This tutorial explains how to use LangChain4j's Model Context Protocol (MCP) to create a tool provider, configure HTTP or stdio transports, run a GitHub MCP server in Docker, and employ a language model to summarize recent repository commits, complete with code samples and logging customization.
This article explores how knowledge graphs can be tightly integrated with large language models through prompt engineering, fine‑tuning, retrieval‑augmented generation, reasoning collaboration, and knowledge agents, outlining technical pathways, practical implementations, and future research directions across AI domains.
