Tencent is orchestrating a $20 billion buyback of AI agent startup Manus from Meta, becoming its largest single shareholder while keeping Manus independent, a move driven by regulatory pressure, rapid ARR growth, and strategic synergy with Tencent's ecosystem.
The article reviews Office Raccoon 2.0, explaining how it solves AI tool fragmentation and memory loss by combining local command execution, browser automation, and cloud‑based creation in a single client, while comparing it with OpenClaw and Hermes and showcasing real‑world use cases.
Google's Gemini Spark, announced at I/O 2026, is a cloud‑based personal AI assistant that runs on Gemini 3.5 and the Antigravity framework, allowing users to schedule long‑running tasks without keeping a computer or browser open, and integrates with Google tools via the MCP protocol.
This article compiles a comprehensive list of free AI APIs from China and abroad, explains the three hard truths about free tiers, details each provider’s token limits, rate limits, and ideal use cases, and offers practical tips for handling rate‑limiting, key management, and fallback strategies.
Facing a projected 175ZB of global data by 2025 and 80% unstructured content, Alibaba Cloud Elasticsearch re‑architects its engine to deliver Agent‑native search, offering structured JSON/Markdown results, high‑performance vector indexing, and a unified enterprise knowledge lake for AI agents.
The article analyzes how the rise of AI agents transforms the industry from dialogue‑centric models to 24/7 digital employees, driving a shift toward CPU‑centric compute, domestic MoE models with strong coding abilities, and cloud platforms that become the core deployment and billing ecosystem, all fueled by massive token inflation.
When enterprise IT blocks cloud AI access to protect sensitive data, this guide shows a three‑step mixed‑route protocol that classifies tasks, applies sandboxed sanitization, and defines SOPs so users can comply with security policies while still leveraging AI productivity.
Anthropic’s Claude Managed Agents provide a cloud‑based API that lets you build, deploy, and orchestrate long‑running AI agents without handling sandboxing, state management, or error recovery, while offering versioned agents, configurable environments, streaming events, custom tools, pricing details, and real‑world use‑case examples.
Claude Managed Agents, Anthropic's cloud‑hosted AI agent service, lets enterprises embed autonomous bug‑fixing, code‑writing, and reporting bots without building heavy infrastructure, offering managed runtimes, scalable sessions, and API integration while highlighting use‑case categories, architectural design, limitations, and industry impact.
OpenClaw attracted massive attention but is hard to deploy, insecure, and plugin‑heavy, while SkyBot offers a zero‑setup cloud AI assistant with sandboxed security, integrated skills, and step‑by‑step demos such as PDF‑to‑PPT generation and automated daily AI news digests.
At re:Invent 2025 Amazon announced four new Nova models—Lite, Pro, Sonic, and Omni—each with benchmark‑backed performance gains over competitors, introduced the open‑training Nova Forge service for custom frontier models, and launched the high‑reliability Nova Act AI Agent platform, highlighting real‑world enterprise use cases.
This article compiles the entry points, documentation links, pricing details, and hands‑on API examples for several leading large‑language‑model providers—including DeepSeek, Alibaba Cloud, Baidu Qianfan, ByteDance Volcengine, OpenRouter, and Google Gemini—while comparing their usability, free‑tier offers, and developer experience.
This article explains how Alibaba Cloud's PAI platform uses an asynchronous inference framework with dedicated queue and inference services to overcome high‑latency challenges, enable load‑balanced request distribution, provide health‑check failover, and support automatic scaling for large‑model AI workloads.
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 explains how to combine PHP web applications with modern cloud-native AI services—via REST APIs, SDKs, and message queues—to build efficient real-time decision systems, covering integration methods, sample code, use-case implementations such as recommendation, dynamic pricing, fraud detection, and performance optimization best practices.
The article explains why combining powerful cloud AI models with lightweight edge models is essential for overcoming compute‑cost trade‑offs, privacy constraints, and scenario gaps, and provides a four‑step guide, real‑world case studies, and future directions for collaborative AI deployment.
This guide walks you through creating a lightweight compute instance, adding it to Baidu Baige AI heterogeneous computing platform, deploying the vLLM tool, loading and serving small‑scale dense models such as DeepSeek, Llama and Qwen, and provides recommended configuration lists to achieve low‑cost, high‑performance inference.
Facing frequent overloads on DeepSeek's official service, this guide details how to run DeepSeek locally with Ollama, deploy it on major cloud platforms such as Huawei, Alibaba, Tencent, Baidu and ZStack, integrate it into enterprise private clusters, leverage open‑source tools like HuggingFace, vLLM and Dify, and showcases real‑world applications in finance, education, and cross‑domain testing.
This guide explains how to use Alibaba Cloud's Function Compute, OSS, and Vision AI to quickly set up a face‑matching service, covering architecture, deployment steps, and practical usage scenarios such as identity verification, access control, and security monitoring.
This article examines the Model-as-a-Service (MaaS) paradigm, tracing its origins, defining its expanded capabilities for large‑model ecosystems, outlining the full‑stack services it offers, and analyzing current industry adoption, deployment models, and the technical and regulatory challenges that must be addressed for scalable AI rollout.
The LARA approach, presented at WWW2024, offers a lightweight, anti‑overfitting retraining solution for unsupervised time‑series anomaly detection in cloud services, achieving state‑of‑the‑art accuracy with minimal new data and dramatically reducing training overhead.
The article reviews Baidu Cloud’s Qianfan 2.0 platform, detailing its expanded model catalog, dataset library, Chinese‑language enhancements, compression and speed gains, robust AI infrastructure, application templates, and end‑to‑end data‑labeling pipeline that together lower cost and accelerate large‑model adoption across industries.
This tutorial explains how to create unique, anime‑style avatars from personal photos by leveraging Alibaba Cloud's Vision AI service, covering account setup, AccessKey creation, required SDK installations, Python code for configuring the client, sending requests, and retrieving the generated image URLs.
This article explains how Google Cloud Vertex AI improves large‑scale distributed machine learning training performance by addressing the memory‑wall challenge with Fast Socket network stack enhancements for NCCL and a Reduction Server that accelerates gradient aggregation, delivering higher throughput and lower TCO for AI workloads.
This article explains how Google Vertex AI tackles the memory‑wall challenge of large‑scale distributed training by introducing Fast Socket, a high‑performance NCCL network stack, and a Reduction Server that halves gradient‑aggregation traffic, delivering significant speed‑up and cost‑reduction for AI workloads.
The 2021 report analyzes the scope of AI chips, examines global and Chinese market dynamics, profiles typical AI chip manufacturers, and provides concise overviews of cloud and edge AI chip segments while highlighting current challenges and future trends shaping the industry.
This article explains how UCloud’s AI team leveraged the UAI‑Train and UAI‑Inference platforms to develop, train, and deploy a high‑accuracy face‑mask detection service within a week, detailing the algorithmic approach, challenges, deployment pipeline, and real‑world applications.
At the Cloud Expo, Alibaba revealed it processes over 10 trillion AI calls daily, unveiled its record‑breaking Hanguang 800 chip, detailed its massive AI cloud infrastructure, and highlighted breakthroughs in AI platforms, algorithms, and industry applications, underscoring its leadership in Chinese artificial intelligence.
The article provides a comprehensive overview of Tencent Cloud’s OCR platform, detailing its service architecture, product capabilities, integration methods, performance metrics, engineering improvements, testing automation, and operational considerations, offering developers practical insights into building and deploying OCR solutions on the cloud.
Didi’s Elastic Inference Service (EIS) and its IFX AI acceleration engine provide a distributed, cost‑effective inference platform that automatically scales resources based on QPS and latency requirements, supports major deep‑learning frameworks, excels in public‑cloud, private‑cloud, IoT and edge scenarios, and achieved top‑rank DAWNBench latency and cost scores on ImageNet with P4 GPUs.
Tencent Cloud experts showcased their AI‑powered video intelligence platform Zhimo, detailing its four‑layer architecture, scene‑aware retrieval, context‑adjusted thresholds, voice‑activity detection, efficient frame filtering, and flexible public‑or private‑cloud deployment, while highlighting applications such as media asset search, content moderation, real‑time subtitles, and automated clip generation.
This article provides a comprehensive overview of computer vision, covering its basic concepts, traditional image processing techniques, modern deep‑learning approaches, real‑world AI application cases, and the cloud infrastructure needed to support large‑scale deployment, while also offering skill‑advancement guidance.
The July 28 Tencent Cloud community salon in Beijing gathered five AI experts who demonstrated practical AI applications—including computer‑vision face filters, OCR services, smart construction attendance, game AI, and breast‑cancer detection—showing how cloud‑based models, data pipelines, and deployment strategies turn research into usable products.
In this interview, Long Mingkang, Vice President of iFlytek's Cloud Computing Institute, shares his experience building large‑scale speech cloud services, discusses the technical hurdles of speech recognition and AI platform development, compares TensorFlow and MXNet, and offers insights on AutoML, industry trends, and how engineers can master AI.
This week’s front‑end roundup covers Tencent’s new “Intelligent Cloud” AI‑as‑a‑Service platform, Walmart’s ban on AWS, releases of React 15.6.0, Angular 4.2, ESLint 4.0.0, Firefox 54 and Chrome 60 Beta, plus updates on Apple Music licensing, Visual Studio 2017 preview and Owl Labs’ robotic conference camera.
