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The assessment evaluated multiple leading AI computing resource management platform providers in China and noted Phancy’s industry-leading technological maturity across heterogeneous accelerator compatibility and adaptation, large-scale cluster operations, and delivery in hybrid cloud environments. Drawing on its accumulated capabilities in heterogeneous computing resource management, fine-grained GPU virtualization and agent-oriented computing services, Phancy received full scores and outperformed the industry benchmark in four out of six evaluated dimensions[1].

According to the IDC report, as AI moves into large-scale deployment, the growing adoption of AI agents is reshaping cloud infrastructure. In the meantime, AI infrastructure is evolving beyond basic computing capacity to become a core part of the enterprise technology stack, supporting digital and intelligent transformation.

Dr. Dai Wenyuan, Founder and Chief Executive Officer of Phancy, said: “The AI industry is moving beyond the ‘model race’ and entering a new phase of large-scale deployment. For enterprises, the real challenge is no longer whether they can access large language models, but about how to translate agentic AI capabilities into sustained productivity while keeping costs under control and operations stable. IDC’s assessment reflects the growing importance of unified management, flexible scheduling and fine-grained operations for heterogeneous computing resources. Phancy will continue to advance its capabilities in heterogeneous computing resource scheduling and agent infrastructure, helping more enterprises unlock the value of AI with greater efficiency, cost-effectiveness and reliability.”

Five Core Capabilities Behind Phancy’s Vendor-Neutral Unified Management Platform

At the core of Phancy’s offering is vendor-neutral unified management software that supports large-scale training and high-concurrency inference for mainstream models across chips from over ten leading vendors[2]. Its core technological capabilities include:

• Code-compatible multi-chip virtualization: Phancy supports the partitioning of a single AI accelerator across multiple workloads, enabling mainstream frameworks and inference engines, including PyTorch, TensorFlow, vLLM and SGLang, to run without changes to application code. Resource quotas help maintain stability when multiple workloads run concurrently.
• Three-tier resource pools and intelligent workload scheduling: Phancy’s platform provides three types of resource pools: dedicated, shared and overcommitted pool. Resources can be intelligently scheduled based on four dimensions (workload priority, hardware topology, real-time load and resource requirements), enabling large-scale training and high-concurrency inference workloads to run on the same infrastructure.
• AI gateway and dual-track metering: The AI gateway provides unified management of model routing, API calls and audit activities. Usage is measured through both accelerator hours and token consumption, helping enterprises track costs and resource utilization from the perspectives of both resource consumption and model usage.
• Agent-oriented computing services: Phancy’s platform turns heterogeneous computing resources into standardized services that AI agents can call on demand. These services support partitioning, reuse and elastic scaling. Combined with intelligent routing through the AI gateway, this accommodates the frequent calls and fluctuating workloads associated with AI agents, while token quotas and circuit-breaking mechanisms also help enterprises manage usage risks and costs when predefined limits are exceeded.
• Operations and maintenance for heterogeneous computing resources: Phancy’s platform provides end-to-end observability spanning nodes, accelerators, workloads and model services. It supports fault isolation, workload rescheduling and private deployment in environments without public internet access, helping enterprises improve operational efficiency across complex heterogeneous computing environments.

The report highlighted a use case in which a Chinese policy bank significant improved resource utilization by using Phancy’s three-tier resource pool architecture to manage computing resources across three data centers in two locations, while also enabling a smooth business migration.

Looking ahead, Phancy will continue to advance its AI computing resource management platform as AI infrastructure shifts from traditional “cloud + AI” architectures toward greater cloud-native, agent-oriented integration. The Group will continue to help enterprises manage computing resources more efficiently, deploy AI across a wider range of production environments, and turn AI into sustainable business productivity at scale.

Hashtag: #Phancy

The issuer is solely responsible for the content of this announcement.

About Phancy Group

Phancy Group (6682.HK) is a leading full-stack AI cloud services platform, providing comprehensive solutions for the AI 2.0 era. Our offerings include SageAIOS, HAMi vGPU and ModelHub XC, delivering efficient and scalable AI infrastructure with end-to-end capabilities. We provide a complete solution from heterogeneous compute resource management and optimization to the deployment of intelligent agent models. These solutions empower digital transformation across a wide range of industries, supporting our vision of building a large-scale and efficient “Token Factory.”

Guided by the mission of “AI for Everyone” and positioned as the “Navigator of AI,” Phancy Group is committed to becoming a global leader in Artificial General Intelligence.

Under the theme “Ecosystem Synergy for Intelligent Evolution,” the event introduced BDStar’s iLDB® strategy and shared the applications and development roadmap of GNSS Services. Training sessions were also organized for distributors. BDStar and attendees engaged in in-depth discussions on strengthening cooperation and fostering ecosystem synergy.

BDStar Founder and Chairman Zhou Ruxin stated that internationalization is a key strategy currently being implemented by BDStar. The company will continue to increase investment in global markets and build localized teams to provide customers worldwide with not only better products, but also enhanced services and support.

Meanwhile, BDStar also participated in INTERGEO 2026 in Munich, showcasing its GNSS chips, modules, antennas, services, and Chip-Cloud GNSS Solutions for a wide range of applications.

Hashtag: #BDStar

The issuer is solely responsible for the content of this announcement.

Response by KK Chiu, International Director, Chief Executive, Greater China, Cushman & Wakefield:

Response by John Siu, Managing Director, Hong Kong, Cushman & Wakefield:

Planning Ahead for AI and Data Centre Infrastructure

We welcome the Government’s commitment to accelerate the development of the Sandy Ridge Data Facility Cluster, which is expected to provide computing power equivalent to 36 times Hong Kong’s current capacity by 2032, alongside a HK$1 billion injection into the Artificial Intelligence Subsidy Scheme. These initiatives will provide important support for the development of Hong Kong’s artificial intelligence and data centre sectors, further strengthening the city’s position as a regional digital and innovation hub.

However, with rapid advancements in artificial intelligence, large language models and cloud computing, demand for computing power is expected to grow significantly in the coming years. We believe that, in addition to planning data centre sites, the Government should proactively review long-term requirements for power supply, electricity grid capacity and related infrastructure. As AI adoption becomes more widespread, access to reliable power and supporting infrastructure will be a key factor in maintaining Hong Kong’s competitiveness as a technology and data centre hub.

We support the Government’s stated direction of pursuing “high-efficiency computing power, stable electricity supply and low-carbon transition”. Looking ahead, we recommend that the Government regularly review future demand for land, power supply and supporting infrastructure arising from the growth of artificial intelligence and data centre activities, particularly within the Northern Metropolis and other strategic development areas. A coordinated approach to computing, energy and digital infrastructure planning will help attract more data centre operators and technology companies to Hong Kong, while supporting the city’s long-term development as a regional hub for data and artificial intelligence.

Hashtag: #Cushman&Wakefield

The issuer is solely responsible for the content of this announcement.

About Cushman & Wakefield

Cushman & Wakefield (NYSE: CWK) is a leading global commercial real estate services firm for occupiers and investors with approximately 53,000 employees in over 350 offices and nearly 60 countries. In Greater China, a network of 23 offices serves local markets across the region. In 2025, the firm reported revenue of $10.3 billion across its core services of Valuation, Consulting, Project & Development Services, Capital Markets, Project & Occupier Services, Industrial & Logistics, Retail, and others. Built around the belief that Better never settles, the firm receives numerous industry and business accolades for its award-winning culture. For additional information, visit www.cushmanwakefield.com.hk or follow us on LinkedIn (www.linkedin.com/company/cushman-&-wakefield-greater-china).

• Launched in H1 2026, Heavy Weight Express service saw a 16% increase in Weight per Day growth for the region (excluding China)
• High-value, technology-related cargo, engineering & manufacturing, and automotive are the biggest drivers, making up two-thirds of the total weight of heavyweight segment

SINGAPORE – Media OutReach Newswire – 16 September 2026 – Following DHL Express’s introduction of Heavy Weight Express (HWX) this year, DHL Express recorded a 16% growth in its Time Definite International Weight per Day in Asia Pacific (excluding China) between January and July2026. This reflects how DHL’s Smart Industrial Growth Strategy is yielding positive outcomes as businesses are moving heavier, critical components, machinery, and industrial equipment across borders.

The heavyweight market has been gaining traction in recent years. Industry research shows that an estimated 10.2 million tons of heavyweight shipments¹ are being moved in Asia Pacific (excluding China) each year. Many companies have spent years reducing inventory and improving efficiency across their supply chains. However, companies today operate in a far less predictable environment marked by trade disruptions, manufacturing bottlenecks, and fluctuating demand. The rise in heavyweight shipment volumes mirrors a shift in how businesses are managing supply chain risks, as they increasingly turn to express logistics not only to handle sudden shifts in demand but also to have greater agility, certainty and control over timelines.

“Behind the numbers is a simple reality: Businesses are shipping heavy when timing matters and when it’s critical,” said Ken Lee, CEO for Asia Pacific, DHL Express. “As companies continue to navigate a complex landscape where uncertainty has become the norm, speed and reliability have also become part of the business decision. Customers are making deliberate decisions on what they ship through our network. Our Heavy Weight Express solution helps companies avoid downtime, protect working capital and keep operations moving when supply chains don’t go exactly as planned.”

Technology, Engineering & Manufacturing, and Automotive top Asia Pacific’s heavyweight contributors

Across the region, high-value, technology-related cargo, such as computer chips and semiconductors, accounts for the largest share of DHL Express’s heavyweight segment at over 34%, driven by rapid investment in data centers to support the growing demandfor computing capacity, data storage, cloud services, as well as artificial intelligence. This has fueled demand for technology-related shipments, from semiconductors and servers to cooling systems and electrical infrastructure. However, a data center crunch is creating supply chain bottlenecks as demand for semiconductor manufacturing outpaces infrastructure supply. As a result, express logistics services are urgently activated to move critical components quickly and efficiently, helping to keep projects on schedule.

The other main contributors to the heavyweight segment are businesses in engineering & manufacturing as well as the automotive industry.

Automotive is the fastest growing sector

HWX service is also gaining strong momentum in the automotive sector, with its shipment weight increasing at a rate of nearly 20%. As the leading export region for this sector, Asia Pacific is also seeing a surge in Asian automotive brands, particularly Electric Vehicle (EV) manufacturers from China and Southeast Asia. As these brands expand into new markets, they are also moving vehicle parts sourced from different suppliers and manufacturers across borders. This has created the appetite for expedited shipments to keep production running. In this sector, a single late or failed shipment could instantly cost automotive manufacturers millions of dollars.

Asia affirms role as a vital trading hub

In Asia Pacific (excluding China), the fastest growth in heavyweight shipments for the first seven months of the year came from India, the Philippines, Vietnam, Japan and Hong Kong. These markets reflect two of the region’s strongest trade corridors – Southeast Asia’s firm role as a manufacturing and sourcing base, and North Asia’s strategic position as a hub for high-value technology, industrial and automotive supply chains. Additionally, India, the Philippines, and Vietnam are also recognized as key markets of the geographic tailwinds initiative.

“As companies continue to manufacture out of Asia, balancing project timelines and building more resilient and agile supply chains become a priority. To maintain production continuity and ensure certainty, they are consolidating goods into heavier shipments. These non-negotiable conditions are also “urgency drivers” that put us at an advantage to help deliver our customers’ shipments at a definite time,” said Ken Lee, CEO for Asia Pacific, DHL Express.

In recent years, DHL Express has added several new infrastructures across the region, including an expanded global hub in Hong Kong, facilities near Cebu and Manila airports, gateway at Christchurch airport, Hanoi gateway near Noi Bai airport, as well as Delhi gateway, culminating in approximately 1,000 facilities in the Asia Pacific region. This is further supported by a robust aviation network of around 810 flights per day.

¹McKinsey/IHS Markit (2024)
Hashtag: #DHLExpress #GlobalTrade #HeavyWeightExpress

The issuer is solely responsible for the content of this announcement.

DHL – The logistics company for the world

DHL is the leading global brand in the logistics industry. Our DHL divisions offer an unrivaled portfolio of logistics services ranging from national and international parcel delivery, e-commerce shipping and fulfillment solutions, international express, road, air and ocean transport to industrial supply chain management. With approximately 389,000 employees in more than 220 countries and territories worldwide, DHL connects people and businesses securely and reliably, enabling global sustainable trade flows. With specialized solutions for growth markets and industries including technology, life sciences and healthcare, engineering, manufacturing & energy, auto-mobility and retail, DHL is decisively positioned as “The logistics company for the world”.

DHL is part of DHL Group. The Group generated revenues of approximately 82.9 billion euros in 2025. With sustainable business practices and a commitment to society and the environment, the Group makes a positive contribution to the world. DHL Group aims to achieve net-zero emissions logistics by 2050.

The regulator said the work will focus on creating clearer rules for datasets used by embodied AI systems, which combine artificial intelligence with physical machines such as humanoid robots. The effort is intended to support more consistent data collection, processing, evaluation and use as companies race to improve machines that must perceive, reason and act in real-world environments.

China has already moved to build a broader standards framework around the sector. National standards published on August 27 cover the quality of real-world embodied-intelligence data and technical requirements for data-generation platforms, while several additional specifications remain under development.

Among projects overseen by the National Data Administration are proposed standards covering the sources and constituent elements of high-quality embodied-intelligence datasets, simulated synthetic-data generation and processing, and specifications for data collection and model training at training bases. The projects are being developed under the National Data Standardisation Technical Committee.

One draft programme, registered in April, sets a 12-month timetable for a standard on data collection and model training at embodied-intelligence training bases. Its drafting group includes the China Electronics Standardization Institute, Beijing Institute of Technology, the Institute of Software at the Chinese Academy of Sciences and robotics companies.

A separate draft addresses synthetic data, which is becoming increasingly important because collecting enough physical-world robot interactions can be expensive, slow and difficult to reproduce. China’s policy framework encourages the use of simulation and synthetic techniques to expand supply where genuine operating data are scarce or costly to obtain.

The National Data Administration has made high-quality datasets a central part of its wider artificial-intelligence strategy. An implementation plan issued in June called for faster construction of datasets in strategic and emerging fields including embodied intelligence, intelligent driving and the low-altitude economy. It also called for data covering physical interaction, environmental perception and motion control in key scenarios.

The plan directs authorities and industry participants to improve data cleaning, enhancement, labelling, alignment and quality inspection, while developing national standards covering formats, categories, annotation and quality assessment. The regulator said such work should produce datasets that are structurally complete, diverse, accurately labelled and suitable for model development.

China’s push reflects the distinct data demands of robots operating in the physical world. Unlike text-based systems trained largely on digital information, embodied AI requires large volumes of multimodal material that can include video, images, sensor readings, point clouds, movement trajectories and feedback from physical interaction.

Data supply has therefore emerged as a competitive constraint for developers seeking to train machines to perform long sequences of actions reliably across changing environments. The National Data Development Research Institute has said embodied intelligence and world models are driving sharply higher demand for three-dimensional, video and other multimodal data, while also raising requirements for collection and annotation quality.

The government has also been expanding the underlying pool of AI-ready datasets. At a national data industry event in Guiyang in August, the National Data Administration said more than 126,000 high-quality datasets had been built across China, with a combined volume exceeding 1,815 petabytes.

Officials described a system combining a national dataset management platform, an open-source community and a data-labelling network with sector-specific pilot programmes. The framework includes 106 leading organisations and 140 pilot tasks, with regional authorities encouraged to develop projects suited to local industrial strengths.

Embodied intelligence has featured in those pilots alongside other emerging fields. The administration has promoted cooperation among robotics companies, universities, research institutes and public bodies to increase the quantity and usefulness of machine-training data while testing standards before wider application.