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Spotlighting the AI Wave and Exploring Paths Forward for Private Enterprises

HONG KONG SAR – Media OutReach Newswire – 29 September 2026 – The second “Jun’s Circle” Fireside Chat, initiated by Ge Jun, an Academician of the International Eurasian Academy of Sciences and Chairman and CEO of TOJOY Shared Smart Enterprise Services Co., Ltd. (“TOJOY”), was recently held on the shores of Dianchi Lake in Kunming. The event was livestreamed simultaneously on Xinhuanet, TOJOY Boss Cloud and other platforms, drawing more than 3.1 million cumulative views online. Online and in-person audiences together took part in an in-depth exchange of ideas, creating an experience in which they were “surrounded by ideas.”

In 2025, the inaugural “Jun’s Circle” Fireside Chat debuted in Hangzhou. Its core proposition — “With vision, break the impasse and build a new landscape” — resonated widely across China’s private sector. On 22 September, the 2026 event came to Kunming, a frontier hub for China’s opening-up to South and Southeast Asia. It directly addressed the central concerns of private enterprises amid AI-driven technological change, the reconfiguration of the overseas expansion landscape and economic-cycle adjustments, helping entrepreneurs clarify their direction and strengthen confidence.

Blueprint for Private-Enterprise Transformation under AI Technological Disruption

Addressing business development amid the AI wave, Ge Jun systematically presented the “Five-Layer Tree Theory” for enterprise AI transformation. Covering the accumulation of data assets, upgrades in entrepreneurs’ cognitive capabilities, workforce-wide capability building, forward-looking strategic planning and symbiosis across industry ecosystems, it provides private enterprises with a comprehensive implementation framework for AI transformation.

Drawing on Kunming’s geographic advantages, the dialogue explored a long-term approach to expansion into ASEAN markets. Ge Jun proposed an “In ASEAN, With ASEAN, For ASEAN” development philosophy, stressing that sustainable overseas growth can only be achieved by establishing deeply rooted local operations, building symbiotic partnerships with local industries and creating social value for local communities. Manuel C. Menendez III, founder and CEO of MCM Group Holdings Ltd. and an expert on international economic and trade issues, drew on frontline experience to stress that managing compliance risk is a fundamental prerequisite for survival for companies expanding overseas. He noted that resource-constrained small and medium-sized private enterprises can leverage professional platforms to pool resources when expanding overseas, advance localization step by step and avoid the risks of going it alone.

The Critical Role of Entrepreneurship and Long-Termism

Turning to the question of how to navigate economic cycles, the dialogue returned to the fundamentals of entrepreneurship, exploring the underlying forces that enable businesses to weather volatility. Xue Jingxia, Chairwoman of the Henan-based investment and construction group, KONITA GROUP, and a deputy to the National People’s Congress for four consecutive terms, said, drawing on four decades of hands-on business experience, that there are no shortcuts to navigating cycles: it takes the creativity to build something from nothing and the resolve to hold firmly to one’s principles. Ge Jun added that entrepreneurs in the AI era need to strengthen their learning capabilities across four dimensions—questioning, command, staying power and transmission—to respond to a rapidly changing market environment, remain committed to doing what is difficult but right, and navigate cyclical ups and downs with a long-term mindset.

As one of the flagship programs in Ge Jun’s four-part thought-leadership series for empowering private enterprises, this year’s “Jun’s Circle” Fireside Chat used a systematic framework of ideas to address the widespread concerns of today’s private entrepreneurs.

Hashtag: #天九企服 #TOJOY

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Alibaba to become Nets’ Official Jersey Patch Partner, and bring Real-Time 360° Replay and personalized fan collectibles to Barclays Center

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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.

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.

The Hyderabad region operates across three availability zones and is designed to provide resilience for organisations running critical applications. Microsoft said the architecture is aligned with applicable regulatory and seismic requirements in India, while giving customers additional options for data residency, continuity and governance.

The company said the region is now live with a broad set of Azure services, with more cloud and AI capabilities scheduled to be added over the coming months. It is also intended to support Microsoft Foundry and other advanced AI services as capacity expands.

Puneet Chandok, president of Microsoft India and South Asia, said at the Microsoft AI Infrastructure Summit in New Delhi that the Hyderabad facility was built for advanced AI workloads and would serve as a strategic hub for Asia and the Global South. Microsoft also said its data centre regions across the country are now AI-enabled, combining specialised hardware, cooling systems and the platform infrastructure needed to run advanced models.

India South Central joins Microsoft’s Central India region in Pune, South India region in Chennai and West India region in Mumbai. Microsoft’s Azure region list identifies Hyderabad as India South Central and shows Central India as its paired region for disaster-recovery planning.

The Hyderabad expansion forms part of Microsoft’s $20.5 billion investment commitment to India, comprising a $3 billion investment announced in January 2025 and a further $17.5 billion commitment announced in December 2025. The company has linked that spending to cloud capacity, AI infrastructure and skills development.

The launch comes as data-centre investment accelerates across the country alongside demand for computing capacity needed to train and run AI systems. A Boston Consulting Group study cited by Microsoft estimates that India’s data-centre build-out could generate $140 billion to $200 billion in economic output through 2030. Microsoft said its infrastructure is intended to serve enterprises, start-ups and public-sector organisations.

Microsoft said Adani Group, Bajaj Finserv, HDFC Bank and PB Pay have signed up to use the new region. The company said local capacity would allow eligible cloud and AI workloads to be deployed closer to users and operations while supporting security, compliance and sovereignty requirements.

The region expands Microsoft’s Sovereign Public Cloud foundation in India. The company said its cloud regions provide capabilities aligned with Ministry of Electronics and Information Technology guidelines and are designed to help customers address requirements under the Digital Personal Data Protection framework, as well as sector-specific expectations from the Reserve Bank of India and CERT-In. Microsoft stressed that customers remain responsible for determining which rules apply to their workloads.

Capabilities expected to become available as services are rolled out include Azure confidential computing, Customer Lockbox and Azure Key Vault. These are intended to give organisations additional controls over data protection, encryption keys and Microsoft’s operational access, particularly for sensitive workloads.

Microsoft also highlighted the cooling design of the Hyderabad region, saying high-efficiency mechanical systems enable effectively zero water use for cooling. The company has tied the design to its broader 2030 sustainability goals, which include becoming carbon negative, water positive and zero waste.

Alongside the infrastructure launch, Microsoft said its AI-skilling programmes have reached more than 10 million people in India, halfway towards a target of 20 million by 2030. It also operates a 600-hour data centre training programme with Young India Skills University in Telangana aimed at preparing students for infrastructure and operations roles.

Jitin Prasada, Minister of State for Commerce and Industry and Electronics and Information Technology, said the new region would strengthen the digital infrastructure required to support the IndiaAI Mission and expand the capacity available to developers, enterprises and public institutions.

South Korea and Taiwan led the regional gains, reflecting renewed buying in semiconductor companies tied to expanding demand for data centres, memory chips and advanced computing. South Korea’s Kospi rose about 1.4%, while Taiwan’s benchmark gained around 1% and reached a three-month high. MSCI’s broadest index of Asia-Pacific shares outside Japan added roughly 0.9%.

Chinese blue-chip shares were also firmer, rising about 0.2%, while Japan’s cash market was closed for the Silver Week holiday. Nikkei futures nevertheless edged 0.2% higher. Trading across parts of the region was thinner than usual because Japanese markets will remain shut through Wednesday.

The strength in Asian technology shares followed continued investor focus on the capital spending required to support generative AI and cloud computing. Samsung Electronics rose sharply in Seoul, while Taiwan Semiconductor Manufacturing Co gained in Taipei, reinforcing the technology-heavy tone across major regional bourses.

US equity futures also pointed higher during Asian trading. S&P 500 futures gained about 0.4% and Nasdaq futures rose 0.6%, while European futures indicated a firmer opening, with EUROSTOXX 50 and German DAX contracts advancing.

Oil prices moved in the opposite direction. Brent crude fell about 1.7% to just above $102 a barrel, while US West Texas Intermediate dropped close to 2% to around $98.50. Both benchmarks had already weakened at the end of last week.

The decline reflected signs that more crude and other energy cargoes were moving through the Gulf despite continuing disruption linked to the conflict in the region. Data from Kpler showed Saudi Arabian crude exports recovering to just above 4 million barrels per day so far in September after dropping to about 2.4 million barrels per day in August.

Saudi shipments through the Strait of Hormuz have increased after disruption to the East-West pipeline and reduced flows through the Red Sea export hub of Yanbu. JPMorgan analysts estimated that total Middle East oil flows averaged 17.1 million barrels per day over the previous 10 days, suggesting that physical supply had proved more resilient than traders initially feared.

Energy markets were also monitoring the possibility of diplomatic engagement this week, which helped reduce part of the geopolitical risk premium built into crude prices. However, tensions remained high after further attacks involving Saudi targets, leaving traders cautious about assuming that supply risks had disappeared.

Bond markets remained another constraint on risk appetite. The US two-year Treasury yield was around 4.76%, after rising sharply over the previous two weeks. Futures markets were pricing a greater-than-even chance of another Federal Reserve rate increase in October following the central bank’s hawkish guidance last week.

Higher borrowing costs have complicated the outlook for equities even as technology stocks continue to attract capital. Investors are balancing the earnings potential created by AI-related investment against the prospect that restrictive monetary policy could persist as central banks attempt to contain inflation.

The US 10-year Treasury yield was close to 5%, keeping pressure on rate-sensitive assets and supporting the dollar. The currency was little changed around 157 yen, with investors alert to the possibility of intervention by Japan’s authorities during the holiday-thinned session.

The yen had strengthened sharply on Friday after Japanese authorities conducted rate checks in the foreign-exchange market. The euro was broadly steady near $1.148 after losing ground against the dollar over the previous week.

Gold prices were little changed to slightly lower as higher bond yields offset safe-haven demand generated by Middle East tensions. Copper, meanwhile, remained supported by signs of stronger demand from China and constrained inventories.

Australia’s S&P/ASX 200 was broadly flat, lagging the technology-led advances elsewhere in the region. India’s benchmark Sensex traded higher during the session, while Hong Kong shares also advanced as investors continued to favour large technology and internet companies.

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
pr@aolani.com

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.