Alibaba Cloud - Experts & Thought Leaders

Alibaba has released Qwen3.6-Plus, the latest iteration of its flagship series of large language models, delivering a significant advancement in agentic coding, as well as multimodal perception and reasoning. Qwen3.6-Plus is designed to empower the latest market demand to shift towards agentic AI: building models that move beyond passive assistance to ones capable of autonomously navigating complex, repository-level engineering and real-world visual environments. AI-native enterprise platform The latest Qwen3.6-Plus model will be integrated into Alibaba’s ecosystem, including Wukong, an AI-native enterprise platform that automates complex business tasks using multiple AI agents, and Qwen App, Alibaba's flagship AI application. While the Qwen series established a strong foundation for the development of AI solutions, Qwen3.6-Plus is optimized for the "capability loop" - the ability to perceive, reason, and act within a single workflow. By incorporating developers’ feedback, the model offers a stable, production-ready framework designed to bridge the gap between initial code concepts and deployed products. Production-ready solutions In frontend website development and repository-level engineering, Qwen3.6-Plus autonomously plans, tests, and iterates on code to deliver production-ready solutions. By managing the full execution loop from objective breakdown to final refinement, the model functions as an end-to-end partner in the development lifecycle. To support complex, repository-level engineering, Qwen3.6-Plus provides a 1-million-token context window by default. Across a broad set of benchmarks, Qwen3.6-Plus demonstrates strong performance across agentic coding and multimodal reasoning capabilities. Qwen3.6-Plus’ strategic advancement in multimodal reasoning, moves beyond simple recognition toward sophisticated analysis and decision-making. The model is engineered to integrate cross-modal information to solve complex challenges, including high-density document parsing, physical-world visual analysis, and long-form video reasoning. Multimodal reasoning capabilities This progress also extends to visual coding, where the model interprets visual designs and prototypes to generate functional code, effectively bridging the gap between perception and execution. The model can now interpret user interface screenshots, hand-drawn wireframes, or product prototypes and instantly generate functional frontend code. To ensure practical utility, Qwen3.6-Plus has been optimized for the stability and precision required in professional business environments. It delivers high-accuracy performance in instruction following, complex text recognition, and fine-grained visual perception. These improvements make the model a reliable solution for demanding real-world scenarios - such as retail intelligence and automated inspections - where consistent, multi-step task execution is necessary to move AI from experimental pilots into broad production. AI development platform Users can access and deploy the model through Model Studio, Alibaba Cloud's AI development platform, and experience it through Qwen Chat. For integrated development, it is compatible with leading third-party coding assistants - including OpenClaw, Claude Code, and Cline - enabling automated, context-aware workflows that translate complex project requirements into functional code. In addition, Alibaba will continue to support the open-source community with selected Qwen3.6 models in developer-friendly sizes.

Alibaba now unveiled the latest evolution of its visual generation models, the Wan2.6 series. It enables creators to appear in AI-generated videos as themselves and in their own voices with flexible multi-shot storytelling – new features designed to unlock creative possibilities for professional-grade content production with enhanced multi-person dialog and extended duration for richer narratives. new reference-to-video generation model The Wan2.6 series features a new reference-to-video generation model as well as comprehensive upgrades to its four existing models. Wan2.6-R2V enables users to upload a character reference video with both appearance and voice, utilising text prompts to generate vivid new scenes starring that same character. Users can create videos featuring a person, animal or object, or even multiple subjects together, while preserving the distinctive look and sound of the original reference. Multimodal reference generation capabilities Powered by multimodal reference generation capabilities, Wan2.6-R2V is China’s first reference-to-video generation model that makes it possible for users to insert themselves or other subjects into AI-generated scenes with consistent visuals and audio. This changes the way short-form drama creators tell stories and streamlines their production process.  The Wan2.6 series also includes enhancements to its text-to-video model (Wan2.6-T2V), its image-to-video model (Wan2.6-I2V), and to its two image generation models (Wan2.6-image and Wan2.6-T2I). Intelligent multi-shot storytelling capabilities The new models introduce intelligent multi-shot storytelling capabilities that allow for richer, more expressive narratives with visual consistency throughout. Its improved capabilities in audio-visual synchronization and audio-to-video generation deliver more realistic scenes with richer sound effects. Supporting video outputs of up to 15 seconds, the models give creators more room to develop their stories. Combined with enhanced instruction-following precision and improved visual quality, they enable creators to produce cinematic-style content with professional-grade results. Advanced logical reasoning capabilities For image generation, the Wan2.6 series enables users to create interleaved text-image output with advanced logical reasoning capabilities, to further support coherent visual storytelling. It also demonstrates outstanding capabilities in precise artistic style control, generating realistic portraits with remarkable fidelity and image editing. Advanced understanding of lengthy Chinese and English text prompts enables creators to produce high-quality, expressive visual content that captures nuance and artistic intent.  Alibaba Cloud's AI development platform Users can access and deploy the models through Model Studio - Alibaba Cloud's AI development platform - and Wan’s official website. The models will also be integrated into Qwen App, Alibaba's flagship AI application. First unveiled earlier this year, the Wan series has undergone continuous upgrades, reflecting Alibaba’s leadership and innovation in AI-driven multimedia technologies.

Alibaba Cloud, the digital technology and intelligence backbone of Alibaba Group, announced that it has been named a pioneer in Gartner 2025 Magic Quadrant for Container Management and the 2025 Magic Quadrant for Cloud-Native Application Platforms. Alibaba Cloud believes these recognitions underscore Alibaba Cloud’s continued commitment to pioneering innovations that empowers global enterprises and drives digital transformation. Focus on delivering solutions “We believe being recognized by Gartner as a Leader in both Container Management and Cloud-Native Application Platforms reflects our unwavering focus on delivering solutions that meet the rapidly evolving technology needs of today’s businesses.” “With digital competency quickly becoming a non-negotiable, we’re fully committed to making the adoption of digital tools as easy and effective as possible while pushing the boundaries of what’s possible in these technologies,” said Jiangwei Jiang, Senior Researcher and General Manager of Infrastructure Products, Alibaba Cloud Intelligence. According to Gartner, “Leaders distinguish themselves by offering a service suitable for strategic adoption and having an ambitious roadmap.” Comprehensive container service portfolio For Container Management, Alibaba Cloud has a comprehensive container service portfolio, which delivers strategic flexibility across public, hybrid, and multi-cloud environments. The container management market reached over USD2.5 billion in value in 2024, and by 2028, 95% of new AI deployments will use Kubernetes, up from less than 30% today, according to the Gartner report. For Cloud-Native Application Platforms, Alibaba Cloud’s dominant position is attributed to its full-featured modern development environment, which integrates developer productivity, AI, and serverless compute. Its Serverless App Engine (SAE), Function Compute, and Container Compute Service (ACS) enable organizations to rapidly build, deploy, and scale AI-enabled applications with ease. Cloud-native application platform The cloud-native application platform market exceeded $3.5 billion revenue in 2024, with worldwide spending growing at a double-digit, year-over-year rate of 16.4%. This market is projected to exceed the $7 billion revenue mark by 2029, at a five-year CAGR of 15.1% from 2024 through 2029 in constant currency, according to Gartner. Alibaba Cloud believes it is well positioned to capture the resulting opportunities as its key strengths include empowering developers with advanced toolchains and serverless orchestration; driving AI innovation through offerings such as AI models, AI gateways, and one click AI application templates; and strong market awareness underpinned by a product strategy designed to meet growing demand for scalable, flexible, and secure solutions. Auto-scaling capabilities During this year’s Apsara conference, Alibaba Cloud’s annual flagship technology conference, Alibaba Cloud has upgraded its ACS to enhance its auto-scaling capabilities through optimized scheduling and container image cache acceleration technologies. This enables elasticity, supporting the scaling of up to 15,000 pods per minute to handle massive, highly concurrent agent requests.

Where and how to store security camera footage usually depends on the scale of the video surveillance project, the way you are using to record the video and how long you want to keep the recordings. If there are only few IP cameras, say 2~3 IP cameras for example, and you don’t need to keep the recordings for the month, usually using SD card which is installed in the camera is enough. Video management software A VMS provides a unified platform to manage all cameras and record footage onto centralized local storage servers If there are more than four cameras, even up to 128 cameras, NVR or CVR become the practical choice for managing and storing recordings reliably. However, if there are hundreds or thousands cameras, which need to managed and recorded, in this way video management software with centralized recording storage becomes essential. A VMS provides a unified platform to manage all cameras and record footage onto centralized local storage servers. S3-compatible cloud platforms Critically, if the VMS supports the S3 object storage protocol, users gain the flexibility to store recordings on S3-compatible cloud platforms (public or private), offering significant hardware cost savings and enhanced scalability. For such demanding environments, selecting a VMS built on an open platform architecture is strongly advised, ensuring the system can expand infinitely to meet future project growth. Video surveillance management system Users can seamlessly add subordinate servers (or disk groups like IPSAN/NAS), disk arrays, and network bandwidth Take the video surveillance management system SVMS Pro as an example. Its foundation is an open 1+N stackable architecture, enabling unlimited expansion of recording storage servers. Users can seamlessly add subordinate servers (or disk groups like IPSAN/NAS), disk arrays, and network bandwidth.  This achieves extended recording durations and boosted storage performance while maintaining system stability during sustained operation (assuming environmental requirements are met). Key architectural advantages Each centralized storage module based on a Linux OS, supports up to 200 front-end video channels per server. Its N+1 stackable expansion capability utilizes a distributed architecture, forming clusters of storage servers. Scaling the project involves simply adding subordinate storage modules – no modifications to existing deployments are required. Seamless S3 object storage integration Furthermore, SVMS Pro features deep integration of the S3 object storage protocol Furthermore, SVMS Pro features deep integration of the S3 object storage protocol. This allows seamless connection to major public cloud services like Alibaba Cloud OSS, Tencent Cloud COS, and Amazon S3 cloud, as well as private S3-compatible object storage solutions. This integration delivers truly limitless capacity expansion, leveraging the inherent elasticity of the cloud to effortlessly accommodate petabyte-scale video growth. Dual insurance: Multi-layered data protection The critical value of security data comes with inherent risks; losing video footage can lead to immeasurable losses. To mitigate these risks comprehensively, SVMS Pro innovates with its "Local + Cloud" Dual-Backup mechanism, leveraging S3 features to build multiple security layers: Real-Time Dual-Writing: Recordings are first written to the local disk (acting as a cache buffer). Upon local persistence, data is simultaneously replicated to cloud-based S3 storage, guaranteeing instant failover if either node fails. Smart Hot/Cold Tiering: Frequently accessed ("hot") data remains on high-performance local storage, while historical footage is automatically archived to low-cost cloud tiers, optimizing storage expenses. Cross-Regional Disaster Recovery: Utilizing the multi-replica and cross-region replication features of carrier-grade S3 storage inherently protects against physical disasters like earthquakes or fires. Additionally, the platform ensures comprehensive data protection through integrity verification and encrypted transmission, safeguarding data integrity and confidentiality across its entire lifecycle – from storage and transmission to access. Conclusion In essence, selecting the optimal storage solution for security footage hinges on a fundamental understanding of scalability requirements, retention needs, and data protection imperatives. As surveillance deployments grow from a few cameras to enterprise-scale systems, the underlying architecture must evolve: Localized storage (SD cards/NVRs) suffices for limited scope and short retention. Centralized VMS platforms become essential for unified management at scale, with open, modular architectures providing critical future-proofing for expansion. S3 object storage integration represents a paradigm shift, decoupling storage capacity from physical hardware and enabling truly elastic, cost-efficient scaling – both on-premises and in the cloud. Ultimately, successful large-scale video surveillance storage relies on architecting for flexibility, embedding data protection intrinsically, and strategically leveraging object storage protocols to balance performance, cost, and resilience – principles essential for safeguarding critical security data now and in the future.