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Advancing Research Commercialization and Building a Vibrant I&T Ecosystem

HONG KONG SAR – Media OutReach Newswire – 2 June 2026 – The Hong Kong University of Science and Technology (HKUST) today successfully hosted its annual “Unicorn Day,” one of Hong Kong’s flagship innovation and entrepreneurship events. The event brought together over 1,800 participants, including students, faculty, and alumni, as well as international and local government representatives, industry partners, investors, innovation and technology entrepreneurs, and researchers. Participants exchanged insights on strategies to strengthen collaboration across the innovation ecosystem, foster cross-disciplinary partnerships, and accelerate the translation of research outcomes into real-world impact.

The event was officiated by Prof. SUN Dong, Secretary for Innovation, Technology and Industry of the HKSAR Government, alongside consuls-generals and senior officials from countries including Australia, Chile, France, Hungary, India, Japan, Malaysia, the Netherlands, Vietnam, and the United Arab Emirates. They were joined by Prof. Nancy IP, HKUST President; Prof. Lionel NI, HKUST (Guangzhou) President; and Prof. Tim CHENG, HKUST Vice-President for Research and Development; in touring over 100 HKUST-nurtured startups, showcasing innovations and applications spanning areas such as healthcare, electronics, and artificial intelligence systems, as well as new materials, green energy, and sustainability.

Prof. Sun Dong remarked, “Innovation and technology (I&T) has always been at the top of the Hong Kong SAR Government’s agenda. We fully recognise the crucial role of local universities — not only as key partners, but as the bedrock of Hong Kong’s I&T ecosystem. In just three and a half decades, HKUST has risen to become a global powerhouse in deep tech, entrepreneurship, and innovation as demonstrated by its ability to nurture unicorns and deep-tech ventures. Hong Kong is entering a golden era of I&T development. We are building new engines to drive Hong Kong’s high-quality development, focusing on research and development in key fields and leading industry applications. I am confident that Hong Kong will rise as a leading international I&T center and contribute meaningfully to our nation’s high-quality development, and that HKUST will continue to be a driving force in this amazing journey.”

President Ip said, “As we mark the 35th anniversary of HKUST this year, we also celebrate the spirit of innovation and entrepreneurship that has long been embedded in our DNA. Both the Technology Transfer Center and the Entrepreneurship Center were established in the University’s early years to support faculty and students in realizing their entrepreneurial aspirations and to promote the translation of research outcomes into practical solutions. Over the past 35 years, the University has forged ahead with determination, sowing the seeds of innovation and yielding remarkable achievements across multiple frontier fields. Today, HKUST continues to broaden its horizons, strategically positioning itself in key domains. One example is medical education. The establishment of the HKUST Medical School will integrate the life sciences with cutting-edge technologies to nurture a new generation of interdisciplinary medical professionals.

Concurrently, HKUST has been actively involved in national initiatives such as the Chang’E 8 lunar exploration mission and research projects for the Tiangong Space Station, and the launch of the first commercially viable aerospace project under the RAISe+ Scheme. These achievements exemplify HKUST’s enduring ‘can do’ spirit over the past decades and echo the theme of today’s event—’From Ideas to Miracles—35 Years of Impact and Beyond’. Looking ahead, HKUST will continue to nurture bold ideas and action, working hand in hand with partners across different sectors to cultivate a vibrant innovation ecosystem, ensuring that research achievements benefit society and create lasting global impact.”

To support startups in expanding into global markets and to promote cross-border collaboration, HKUST introduced an “International Pavilion,” featuring startups and innovation organizations from various countries and regions. Participants from Thailand, Singapore and Korea were among those represented, strengthening connections between Hong Kong, and countries and regions along the Belt and Road in technology application and industry development.

The event also saw the signing of multiple partnership agreements, including six strategic collaborations with:

• GPTX Investment Management Limited
• China Everbright Water Limited
• Jiangsu Daotop Environmental Technology
• Samsung R&D Institute China – Guangzhou
• CalmCar Physical AI Innovation Center
• InnoAngel

to advance talent development and industry–academia integration, and foster innovation-driven research and real-world technology translation.

HKUST’s I&T Strength Driving Economic Growth

In addition, HKUST also released the report Driving Socioeconomic Impact Through Research and Innovation: Insights from HKUST, commissioned by the University and prepared by the international research information analytics organization Elsevier. The report highlights HKUST’s outstanding performance in innovation and entrepreneurship. Over the past five years, research output has recorded an average growth of 10%, approximately 9% higher than that of other local institutions. More than 65% of the research is concentrated in engineering and computer science, while 6.2% involves academia-industry collaboration, significantly higher than the global average of 2.7%. These collaborations have translated into impactful intellectual property, with approximately 1,670 patent applications and 700 grants over the same period, and a high IP utilization rate of above 30%.

Prof. Tim Cheng noted that the findings demonstrate HKUST’s steadily strengthening capabilities in research translation and academia-industry collaboration. HKUST’s publications achieved a Field-Weighted Citation Impact of 4.40, indicating that their citation impact is 4.4 times the global average. This underscores HKUST’s significant contributions to advancing Hong Kong’s socioeconomic development and enhancing its competitiveness in innovation and technology.

In addition, a “Marketplace” was also featured, showcasing products already launched by startups, including AI analytics tools, healthcare technologies, and smart city solutions, demonstrating the progress of translating research into practical applications.

Hashtag: #unicorn #unicornday #HKUST #partnership #innovation #startup #tech #AI #space #robotics #materialscience

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Financial markets are inherently complex systems shaped by price dynamics, capital flows, macroeconomic cycles, policy changes, and investor sentiment. Traditional financial modeling approaches, typically grounded in historical data, empirical assumptions, and linear analysis, face limitations in capturing such multidimensional interactions. AI for Science introduces new methodologies through simulation, advanced reasoning, and multivariable modeling, offering a broader analytical perspective.

The application of AI is not positioned as a replacement for traditional financial models, but as an enhancement to analytical capabilities in conditions of uncertainty. In areas such as asset valuation, risk exposure assessment, and macroeconomic scenario simulation, the central challenge lies in understanding variable interactions and maintaining model interpretability under extreme conditions. AI-driven approaches contribute to improved analysis by enabling more comprehensive scenario testing and deeper insight into systemic relationships.

Chow Kit Hui, founder of KitHui Growth Financial Academy, continues to monitor advancements in AI training architectures, algorithm optimization, and scientific research-grade artificial intelligence. Ongoing engagement with developments in intelligent decision-making and financial technology reflects a commitment to integrating emerging methodologies into financial research and education frameworks.

Insights from the Science x AI Summit 2026 indicate that the long-term value of AI extends beyond efficiency gains and content generation. Greater potential lies in supporting the analysis of complex systemic challenges. In financial applications, AI is not expected to eliminate risk or replace professional judgment; however, it can contribute to earlier risk identification, more robust assumption testing, and decision-making processes that more accurately reflect real-world complexity.

Hashtag: #ScienceXAI #ChowKitHui #AIforScience

https://www.kithuiacademy.com/

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

About KitHui Growth Financial Academy

KitHui Growth Financial Academy focuses on advancing structured and long-term financial understanding across key areas including global asset allocation, corporate mergers and acquisitions, private equity, derivatives, risk management, macroeconomic research, and financial valuation modeling. The academy emphasizes systematic thinking and rational analysis rather than short-term market forecasting or speculative investment strategies.

The stock climbed about 6 per cent on Tuesday as investors reacted to signs that Tencent is moving closer to embedding a task-performing assistant inside WeChat, the messaging, payments and social platform used by more than 1.4 billion people. The prototype is designed to help users complete everyday actions within the app, including finding venues, interacting with mini-programmes and placing customised orders, rather than merely answering questions in chatbot form.

The planned agent would mark a significant step in Tencent’s push to convert its AI investments into consumer products at scale. WeChat already functions as a digital operating system for daily life in China, covering messaging, payments, shopping, food delivery, public services, entertainment, ride-hailing and enterprise communication. That reach gives Tencent an advantage that few rivals can match: a single platform with a vast user base, heavy daily engagement and a dense network of third-party services.

People familiar with the prototype have indicated that users would be able to access the AI agent through a swipe gesture on the main WeChat screen. Tencent is expected to begin the regulatory compliance process before wider testing, with a small group of external users likely to receive access before any phased public launch. A firm release date has not been set, reflecting both regulatory uncertainty and the technical demands of deploying agentic AI across a platform of WeChat’s size.

The market response underscores how investors are reassessing Tencent’s AI position after months of concern that the company was trailing Alibaba, ByteDance and Baidu in the race to commercialise generative AI. Tencent has promoted Yuanbao, its AI chatbot, developed its Hunyuan foundation model and introduced productivity-focused AI tools, but WeChat remains the asset most capable of turning those efforts into a daily consumer habit.

Tencent’s first-quarter earnings showed both the strength and the cost of that strategy. Revenue rose 9 per cent year on year to RMB196.5 billion, while IFRS net profit attributable to equity holders increased 21 per cent to RMB58.1 billion. Marketing services revenue rose 20 per cent to RMB38.2 billion, helped by AI-driven advertising improvements, while domestic games revenue grew 6 per cent and international games revenue climbed 13 per cent. Capital expenditure reached RMB31.9 billion, up 16 per cent, as spending on AI infrastructure continued to rise.

The company has told investors that new AI products are weighing on margins, even as core businesses continue to generate strong cash flow. Excluding new AI products, non-IFRS operating profit rose 17 per cent in the first quarter, compared with a 9 per cent increase overall. That gap highlights the near-term drag from AI investment, but also explains why investors are sensitive to any sign that Tencent can place AI directly into revenue-generating services.

Competition is intensifying across China’s technology sector. Alibaba has pushed Qwen into consumer and enterprise markets, ByteDance has expanded AI features across its content ecosystem, and Baidu continues to build around Ernie and AI cloud services. The key battleground is shifting from chatbots to agents that can perform tasks, connect with apps and act across digital services with limited user input.

WeChat’s mini-programme ecosystem could be central to Tencent’s approach. Millions of merchants, developers and service providers already operate within the platform, allowing an AI agent to navigate services without pushing users outside Tencent’s environment. For merchants, an effective agent could increase conversion rates by shortening the path from search to purchase. For Tencent, it could deepen engagement, improve advertising relevance and strengthen its fintech and business services ecosystem.

Regulation remains a critical constraint. China requires generative AI services offered to the public to comply with rules covering data security, content control and algorithmic governance. Any WeChat agent would need to satisfy those requirements before broad release, especially because it could interact with payments, commerce and public services.

The Provisions on the Protection of Trade Secrets, issued by the State Administration for Market Regulation under Order No. 126, came into force on 1 June 2026 and replace rules first introduced in 1995. The overhaul gives regulators clearer authority to handle disputes involving digital assets that now sit at the centre of corporate value, from AI model architecture and training datasets to platform recommendation systems, software code and commercially valuable operational data.

The change marks a significant shift in China’s treatment of intangible technology assets. Earlier rules were drafted before cloud computing, AI systems and large-scale data operations became central to business competition. The new framework defines trade secrets as technical or business information that is not publicly known, has commercial value and has been subject to confidentiality measures by the rights holder. Technical information now expressly covers data, algorithms, computer programs and code, while business information can include management, sales, finance, planning, customer and operational data.

The timing gives the regulation wider strategic weight. China and the United States are locked in a prolonged technology rivalry involving semiconductor controls, restrictions on advanced computing hardware, limits on investment in sensitive sectors and scrutiny of cross-border technology transfers. Washington has tightened export controls on high-end chips and chipmaking equipment, while Beijing has expanded its own legal toolkit to protect critical technology, secure data flows and prevent overseas transfer of capabilities it regards as strategically important.

The new rules do not create a separate trade secret law, but provide more detailed administrative guidance under China’s Anti-Unfair Competition Law. They clarify how regulators should assess whether information is secret, whether it has commercial value, what counts as reasonable confidentiality measures and how infringement should be investigated. For companies, the central message is that protection will depend not only on the value of the information, but also on whether internal controls, access limits, confidentiality agreements, digital safeguards and evidence trails are in place.

The provisions also recognise that unsuccessful research can have commercial value. Stage-by-stage technical results, failed experimental data and development paths that save time or cost in future research may qualify for protection if they meet the legal conditions. That is especially relevant for AI labs, pharmaceutical developers, electric vehicle makers, chip design firms and advanced manufacturing groups, where failed trials can reveal important technical boundaries and prevent competitors from repeating expensive mistakes.

Regulators have been given practical enforcement tools, including powers to inspect business premises, question individuals, copy documents, examine electronic records and take action against materials linked to suspected infringement. Penalties can include orders to stop unlawful conduct, confiscation of illegal gains and fines that may reach CNY5 million in serious cases. The framework also covers improper acquisition, disclosure, use or permission to use trade secrets obtained through theft, bribery, fraud, coercion, electronic intrusion or breach of confidentiality obligations.

For multinational companies operating in China, the new rules create a mixed picture. Stronger protection could help firms defend proprietary data, software systems and industrial processes in a market where trade secret disputes have often been difficult to pursue. At the same time, wider protection for data and algorithms may increase compliance complexity, particularly in joint ventures, outsourced research, cloud services, employee mobility, cross-border collaboration and licensing arrangements.

Technology companies are likely to face tougher expectations over documentation. Firms seeking protection will need to show that the information was not easily accessible, carried economic value and was actively protected. Generic claims that an algorithm or dataset is confidential may not be enough. Companies will be expected to classify sensitive assets, restrict access by role, track downloads and transfers, maintain logs, use encryption or watermarking where appropriate, and ensure that employment and partnership contracts define confidentiality obligations with precision.

The rules also sit alongside China’s broader data and security regime, including laws on data security, personal information protection, cybersecurity and export control. That overlap could make enforcement more powerful but also more complicated. A dataset may be a trade secret, a regulated data asset and a cross-border transfer concern at the same time. Businesses handling AI training material, user behaviour data or industrial performance data will need to assess those obligations together rather than treating trade secret protection as a standalone issue.

Shares in Masayoshi Son’s technology investment group surged in Tokyo trading, lifting its market value to about ¥47.2 trillion, or roughly $296 billion, ahead of Toyota’s ¥45.7 trillion after the carmaker’s stock fell nearly 5 per cent. The move placed SoftBank at the top of Japan’s corporate valuation table for the first time in more than two decades and added momentum to a Nikkei 225 rally that pushed the index above 67,000.

The change is more than a stock-market milestone. It reflects how the AI boom has reshaped capital allocation in Japan, where investors are assigning higher value to companies with exposure to semiconductors, data centres, power infrastructure and generative AI platforms. Toyota remains one of the world’s largest and most profitable carmakers, but its valuation is now being weighed against a slower earnings outlook, tariff pressure, currency swings and the heavy cost of electrification.

SoftBank’s advance has been driven by a powerful combination of portfolio gains and expectations that its AI-linked holdings could generate fresh liquidity. The group’s exposure to Arm, the British chip-design company it took public in 2023, has become a key pillar of its market value. Arm’s technology is used widely across smartphones, cloud computing and increasingly AI-related chips, giving SoftBank a central position in the semiconductor supply chain.

OpenAI has become the second major driver of investor attention. SoftBank has committed tens of billions of dollars to the ChatGPT developer and is positioning itself as a core financier of AI infrastructure. Expectations that OpenAI could move towards a public listing have intensified interest in SoftBank’s asset base, even as analysts continue to debate how much of the group’s valuation depends on private-market pricing and future monetisation.

The latest surge followed SoftBank’s plan to invest up to €75 billion in AI infrastructure in France, including data centres and power-intensive computing capacity. The first phase is expected to involve about €45 billion of investment to build 3.1 gigawatts of capacity by 2031, with further expansion potentially taking the total to 5 gigawatts. The project places France at the centre of Europe’s push to develop sovereign AI infrastructure, helped by its nuclear-heavy power system and available industrial sites.

SoftBank is also moving to create public-market vehicles around AI infrastructure. SB Energy, its power and data-centre platform, is preparing for a potential US listing and has been linked to a valuation above $50 billion. The company is involved in large-scale power projects designed to support AI workloads, including a 1.2-gigawatt data-centre development in Texas. A separate robotics venture, Roze, is also being prepared for a possible listing, highlighting SoftBank’s attempt to build an ecosystem around energy, construction automation and computing capacity.

Toyota’s fall in ranking does not signal operational weakness. The carmaker reported operating income of ¥3.8 trillion for the financial year ended March 2026, supported by vehicle sales and pricing power despite tariff costs and rising expenses. It remains a global force in hybrid technology, production efficiency and supply-chain management. However, investors have become more cautious about its growth outlook as the auto sector faces higher regulatory costs, slower battery-electric vehicle adoption in some markets, and intensifying competition from China-based manufacturers.

The contrast between SoftBank and Toyota captures a broader reordering of Japan’s equity market. AI-linked names, chip suppliers and infrastructure companies are drawing strong inflows, while parts of the auto sector and older industrial groups face questions over margin durability. Kioxia, the memory-chip maker, has also climbed sharply this year, showing how investor enthusiasm has spread beyond SoftBank into companies tied to storage and high-performance computing.

The rally has strengthened the profile of Son, whose investment record has swung between spectacular gains and painful losses. SoftBank’s Vision Fund suffered heavy write-downs after the collapse in technology valuations in 2021 and 2022, while earlier bets such as WeWork damaged confidence in the group’s risk controls. Its comeback has been powered by a more concentrated AI narrative, but that also leaves the shares vulnerable if expectations around OpenAI, Arm or infrastructure listings are revised lower.