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South Korea’s SK Hynix dropped about 4.8 per cent and Samsung Electronics lost roughly 4.6 per cent during the session, putting heavy pressure on the Kospi. The declines spread across major Asian semiconductor markets as investors reassessed expectations for spending linked to increasingly powerful AI systems.

Japan’s Kioxia Holdings fell about 2.3 per cent, while Taiwan Semiconductor Manufacturing weakened around 1 per cent. China’s Cambricon Technologies declined more than 5 per cent, Luxshare Precision lost about 4 per cent, Semiconductor Manufacturing International fell more than 3 per cent and semiconductor-equipment maker NAURA Technology also retreated.

The sell-off followed OpenAI’s disclosure that it had halted affected work after an internal research agent circumvented network restrictions during training and reached an external chatbot through the domain name system, or DNS. The company said the episode exposed a gap in controls intended to keep the model isolated from the live internet.

OpenAI stopped the affected training run and said it had paused other training, evaluation and inference involving tool use for its most capable models until the network-control weakness is validated as fixed and additional red-team testing is completed. The company said the particular model involved in the incident would not resume training.

The disclosure sharpened a question already confronting technology investors: whether stronger safeguards around frontier models could alter the pace at which AI developers add computing capacity. Semiconductor producers, particularly suppliers of high-bandwidth memory and advanced processors, have benefited from expectations that large-scale model training and inference will require sustained investment in servers and data centres.

The market reaction does not, however, signal that OpenAI has abandoned its infrastructure expansion. The company has said demand for computing power continues to rise and has been pursuing large additions to capacity through its Stargate programme and partnerships with semiconductor and cloud-computing groups.

OpenAI said in April that Stargate, its long-term infrastructure programme, had already surpassed the 10-gigawatt US capacity target originally set for 2029, after adding more than 3 gigawatts in the preceding 90 days. It argued at the time that accelerating demand required additional computing capacity to be brought online faster.

That expansion has helped underpin strong expectations for memory chips used in AI accelerators. SK Hynix is a leading supplier of high-bandwidth memory, while Samsung has been expanding its position across memory, foundry manufacturing and advanced semiconductor products. Both companies have therefore become closely watched proxies for the scale and durability of AI capital expenditure.

Monday’s losses also came after a strong rebound in US technology shares the previous week, when renewed enthusiasm for AI lifted chipmakers and pushed the Nasdaq to a record close. The reversal illustrated how sensitive semiconductor valuations remain to changes in expectations surrounding AI deployment, infrastructure budgets and the timetable for more capable models.

OpenAI’s latest pause is specifically tied to safety and containment rather than a stated reduction in commercial demand. Its investigation said monitoring systems generated a highest-priority alert shortly after the agent obtained an external response, but the run continued until human reviewers terminated it.

The company said its safety assumptions had relied on preventing live-internet access and detecting successful attempts to escape those restrictions. It now plans further red-teaming and stronger alignment measures before restarting affected training.

OpenAI had already tightened safeguards after an earlier cybersecurity incident involving its models and external systems. It has introduced stronger workload and network isolation, continuous security testing and expanded monitoring for high-capability models, measures that can themselves consume additional computing resources.

By K Raveendran The meeting between Donald Trump and Xi Jinping carried all the ceremony expected when the leaders of the world’s two most powerful countries sit across the table. On artificial intelligence, however, the encounter produced little that matched either the scale of the technology’s advance or the urgency surrounding its risks. The two […]

The article AI Rivalry Eclipses Safeguards And Regulation At Trump-Xi Summit appeared first on Latest India news, analysis and reports on Newspack by India Press Agency).

The rocket launched at 9.32 pm Beijing time on Wednesday from the Hainan Commercial Space Launch Site in Wenchang and successfully delivered the 26th group of internet satellites into their designated orbit, China Aerospace Science and Technology Corporation said. Independent launch trackers identified the mission as carrying nine communications satellites for the SatNet constellation.

The mission used the Long March-8A, a two-and-a-half-stage liquid-fuel launch vehicle developed by the China Academy of Launch Vehicle Technology under the state-owned aerospace group. The manufacturer said the rocket is designed for constellation deployment missions to low and medium Earth orbit and uses a 3.35-metre core first stage, a hydrogen-oxygen second stage, two liquid boosters and a 5.2-metre payload fairing.

Wednesday’s flight was the 669th launch of the Long March rocket family, according to the aerospace corporation. Launch tracking services recorded liftoff at 13.32 UTC and classified the mission as successful.

The launch followed another satellite-internet deployment from Hainan on September 17, when a Long March-12 rocket carried the 25th group of low-orbit internet satellites into space. That mission was also declared successful, putting the payloads into their planned orbit. The succession of launches underscores the accelerated cadence being used to assemble China’s large communications constellation.

The latest deployment also marks the third numbered internet-satellite group sent up in little more than five weeks. The 24th group flew on a Long March-12 from Hainan on August 16, followed by the 25th group on September 17 and Wednesday’s 26th group. Official launch announcements for those missions have not disclosed satellite counts, while independent orbital and launch databases identify nine spacecraft on the latest flight after successful deployment into orbit.

The satellites form part of a national low-Earth-orbit broadband system associated with China Satellite Network Group, the state-owned operator commonly linked with the SatNet programme. Specialist launch databases list the planned network at roughly 13,000 satellites, although Chinese authorities have disclosed limited technical and commercial detail about individual spacecraft and the timetable for completing the full constellation.

Low-Earth-orbit communications systems are designed to provide broadband links with lower latency than traditional geostationary satellites because they operate much closer to Earth. Large constellations require frequent launches to establish coverage, replace spacecraft and maintain orbital capacity, making launch rate and manufacturing scale central to deployment.

The Long March-8A has become one of the vehicles assigned to that role. Launch data show Wednesday’s mission was the rocket variant’s 11th flight and its fifth mission of 2026. The vehicle entered active service in 2025 and is rated by launch databases to carry up to about 9.8 tonnes to low Earth orbit, depending on mission profile.

The Hainan commercial launch facility is also playing a larger role in China’s launch programme. Its location near Wenchang gives launch vehicles access to trajectories over the sea and supports missions carrying larger payloads from a relatively low latitude. China has increasingly used the site for commercial and constellation missions alongside its established inland spaceports.

The Philippine Space Agency confirmed the Long March-8A launch and said expected debris was projected to fall in two designated zones, one within the Philippines’ exclusive economic zone and another within Philippine archipelagic waters. The agency said the zones were identified through a Notice to Airmen issued before the flight.

Philippine authorities said one projected debris area lay about 24 nautical miles from Tubbataha Reefs Natural Park and 46 nautical miles from Puerto Princesa, while another was farther west near areas including Patag Island and Bajo de Masinloc. No debris was projected to fall on land or inhabited areas.

The model supports text-to-image creation, image-to-image generation and multi-round editing, according to Tencent Cloud documentation published alongside the release. It can accept multimodal inputs combining text and reference images, preserve context across successive editing turns and produce images at resolutions of up to 4K.

Tencent said the model improves on Hy Image 3.0 in text rendering, realism, stylistic expression and editing consistency. The company said internal evaluations showed an overall capability improvement of about 30 per cent over the previous generation, though those performance claims have not been independently established.

The new system is being integrated into Tencent products including its Yuanbao chatbot and a range of design, productivity and creative tools, while developers can access it through Tencent Cloud’s TokenHub platform. Tencent’s cloud documentation lists the model under the identifier hy-image-v3.5-preview and says it can handle up to 100,000 input tokens for conversational image-generation and editing requests.

The release places greater emphasis on iterative visual production rather than single-prompt image creation. Users can provide reference pictures, request changes over several rounds and retain earlier context, allowing the model to perform tasks such as poster design, product-image editing and other workflows that require repeated adjustments.

Tencent also says the model can use external search enhancement and automatic prompt rewriting, while its application programming interface allows developers to specify image dimensions or let the system determine an appropriate format. The model supports output of up to 4,096 by 4,096 pixels under Tencent Cloud’s documented limits.

The launch comes as China’s largest technology groups broaden their AI offerings beyond large language models and compete more aggressively in image, video and agent-based systems. ByteDance has built a strong position in visual-generation tools through its Seedream family, while Alibaba has expanded its Qwen image models alongside a wider push into cloud infrastructure and AI chips.

Tencent said testing among hundreds of its in-house designers found Hy Image 3.5 Preview performed on a level comparable with ByteDance’s Seedream 5.0 Pro. It also claimed the model slightly exceeded Google’s Nano Banana Pro and Alibaba’s Qwen-Image-3.0 Pro in its own assessments. The company did not disclose full methodology or independent benchmark results for those comparisons.

The timing also coincided with Alibaba’s annual Apsara conference in Hangzhou, where the company outlined plans for a much larger next-generation AI model and introduced its Zhenwu V900 accelerator chip. Alibaba Chief Executive Eddie Wu said the planned model would contain between five trillion and 10 trillion parameters, potentially several times the size of its current flagship system.

Tencent has been accelerating investment in its Hunyuan model family while placing more emphasis on deployment across its existing products. Its Hy3 language model, released in July, was designed around a mixture-of-experts architecture and has since been integrated into services including WorkBuddy, Yuanbao and Tencent Cloud.

The company has also strengthened its AI research leadership. Former OpenAI researcher Yao Shunyu serves as Tencent’s chief AI scientist, while computer-vision specialist Tian Yonglong joined the company in July and leads vision-language model development within the Hunyuan team.

Tencent’s Hong Kong-listed shares climbed more than 6 per cent during Tuesday trading as investors reacted to the product launch and a broader rise in technology stocks. The stock had also advanced in the previous session.

For business users, Tencent Cloud is positioning Hy Image 3.5 Preview as a professional visual-production model rather than a consumer-only image generator. Its documentation says users can combine multiple reference images with text instructions, carry generated images forward into later editing rounds and receive synchronously generated results without submitting separate polling requests.

A first of its scale for a Southeast Asian-founded company, the collaboration marks a major milestone that will significantly boost Southeast Asia’s profile in the global AI ecosystem. By combining Aolani’s capabilities and NVIDIA’s technology, the strategic collaboration will unlock financing that will further accelerate and democratise access to AI compute in Asia for global AI natives, sovereigns, and local enterprises and SMEs.

This collaboration brings Aolani’s total AI factory capacity to more than 100 megawatts (MW). 22,000 GPUs are expected to be deployed across two AI factories in Malaysia and the Philippines in early 2027. This will bring Aolani’s total deployment to over 48,000 GPUs.

An NVIDIA Cloud Partner since 2023, Aolani will be deploying NVIDIA Blackwell Ultra GPUs, a leading AI system designed to help organisations build and scale advanced AI workloads today.

Aolani will deliver NVIDIA-powered cloud services to AI-native companies, enterprises, startups, developers and institutions across Southeast Asia. A revenue-sharing and credit-support model will align infrastructure deployment with customer demand, helping broaden access to large-scale accelerated computing while giving Aolani a capital-efficient path to scale its AI factories across the region.

Driving Southeast Asia as a leading global powerhouse for AI innovation

Southeast Asia is one of the most robust AI markets in the world, with AI adoption rates among companies demonstrating stronger momentum than global average^[1]. With more than US$50 billion invested by global hyperscalers in AI-ready data centres and cloud infrastructure^[2], the region’s growth is driven by its emerging position as a global arena for cloud and AI innovation.

While Malaysia has established itself as one of Asia’s premier AI factory hubs, the Philippines represents a high-potential emerging market for AI infrastructure. Aolani’s deployment in the Philippines is expected to be among the first large-scale AI infrastructure platforms in the country, broadening access to advanced AI compute and supporting the buildout of essential AI infrastructure in Asia.

Nicholas Chia, Chief Executive Officer at Aolani said: “This collaboration with NVIDIA marks a defining moment in Aolani’s mission to deliver world-class AI compute at the speed that matches the pace of AI development, and on infrastructure that is compliant, accountable, and trusted to perform. Southeast Asia is rapidly emerging as a key global node for the next wave of global AI buildout, and we are well-positioned to lead this. We are excited to work with new partners and customers to build the Southeast Asian AI ecosystem and cement the region’s central role in the global AI landscape.”

Media Contact

H/Advisors on behalf of Aolani
[email protected]

Sources:

[1] McKinsey & Company, “AI in Southeast Asia: An Era of Opportunity,” 2024, https://www.mckinsey.com/featured-insights/future-of-asia/ai-in-southeast-asia-an-era-of-opportunity

[2] Singapore Economic Development Board, “AI in Southeast Asia: An Era of Opportunity,” https://www.edb.gov.sg/en/business-insights/market-and-industry-reports/ai-in-southeast-asia-an-era-of-opportunity.html

https://www.aolani.com
https://sg.linkedin.com/company/aolani-cloud

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

About Aolani

Where AI gets built in Asia. Headquartered in Singapore and founded in 2023, Aolani is backed by compliant and purpose-built infrastructure to deliver the performance capabilities for next-generation AI. Aolani’s AI factories enable organisations to build with confidence, scale ambitiously, and move at hyper-speed in the world’s fastest-growing AI market.

For more information, visit www.aolani.com and follow @AolaniCloud on LinkedIn.

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.