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Powering What Comes Next: JRH Explores AI Opportunities at HKSTP Summer Talent Fest 2026
July 16, 2026
From robot dogs to AI-assisted battery design, the event showed how JRH can combine traditional energy expertise with intelligent AI tools to develop better products.
HONG KONG, 14 July 2026 — Representatives of JRH attended Blooming with AI: HKSTP Summer Talent Fest 2026 at the Golden Egg in Hong Kong Science Park. Combining an AI+ Tech Showcase, the AI Leadership Forum, and “Meet & Spark” networking, the event brought together technology companies, industry leaders, professionals and emerging talent.
For JRH, the event was an opportunity to consider how AI could support both its products and its internal development processes. Established in 2019, Shenzhen JRH Technology Co., Ltd. works across batteries, power banks and household energy storage, supported by a diverse product portfolio and stable supply capabilities. Hong Kong JR Group Co., Ltd. was established in 2024 to advance research on high-energy solid-state batteries and expand overseas applications in the consumer battery market.
A Quick View Across the Showcase
The opening showcase featured ten selected companies applying AI and digital technologies in different industries. For example: Fano Labs presented multilingual speech recognition and language-analysis technologies for customer service, compliance and business insights. Blue Pin demonstrated indoor positioning and hotel-automation solutions designed to improve navigation, check-in and visitor experiences. Wo Lee Green Solutions Limited showed how modular construction, green materials, automated fabrication and digital traceability are contributing to a more efficient built environment.
Together, these exhibits provided a concise view of how AI is improving communication, services and traditional industries. The most relevant opportunities for JRH, however, emerged from robotics and AI-platform technologies.
New Opportunities in AI-Aided Product Design
Among the ten companies, several captured JRH’s particular interest. We recognise that some have significant potential to leverage our solutions to enhance their products, while others impress us with innovative approaches to utilising AI.
IG Inno Limited displayed autonomous mobile robots and quadruped robots, commonly known as robot dogs. Their need for reliable runtime, manageable weight and stable performance highlighted a possible area for future discussion around tailored battery packs for new robotic platforms or auxiliary equipment, subject to full technical evaluation.
Asiabots Limited attracted particular interest from our team. Rather than viewing the company primarily as a potential battery customer, JRH was interested in how Asiabots brings different AI capabilities together within practical, user-facing platforms.
The demonstration inspired JRH to consider developing an AI-assisted battery-design platform. Engineers could describe a design difficulty—for example, balancing energy density with limited space, reducing weight while maintaining runtime, etc. The platform would first identify the problem and organise the relevant constraints. Then, the system could automatically select the most suitable approved AI model for the task, rather than relying on one model for every question.
Using an authorised knowledge base containing internal design experience, cell specifications, test results, supplier information and applicable standards, the system could generate several viable solution pathways. Instead of presenting just an unsupported answer, it should explain its assumptions, compare trade-offs and identify what information or testing would still be required.
Such a platform could shorten early design iterations, preserve engineering knowledge and make it easier for different teams to learn from previous projects. It could also improve communication between customers, sales teams and engineers by converting an initial product requirement into a more structured technical brief.
AI would support—not replace—JRH’s engineers. Every recommendation would still require professional review, prototyping, testing and confirmation against safety requirements. Confidential data would also need to remain within a controlled and secure environment.
Westwell Technology (Hong Kong) Limited presented intelligent logistics robots and autonomous new-energy vehicles. For JRH, the most relevant possibilities concern compact robotic systems, sensors and auxiliary equipment in which high-energy, safety-managed battery packs may improve operating time or deployment flexibility.
This showcase event allowed us to see technologies operating in person and to examine ideas in greater depth. We are excited about how we can collaborate with potential customers and integrate AI into our business.
JRH’s main takeaways are two connected ideas: its battery expertise could support selected physical AI applications, and AI could help JRH improve the process through which those battery solutions are designed.
Leadership, Ethics and Real-World AI
The session included the kick-off of the “AI for All” Inclusive Programme, reinforcing the importance of making AI knowledge and opportunities more widely accessible.
Next, we saw the AI Leadership Forum: From Academic to Industry Practices, which was moderated by Dr Charleston Sin, Head of AI & Data at HKSTP. He was joined by Professor Helen Meng of The Chinese University of Hong Kong and Mr Lewis Fung, Managing Director of SenseTime Hong Kong and Macau, Asia Business Group.
Professor Meng emphasised the importance of continuing to learn and adapt as technology develops rapidly. She also highlighted that responsible AI capability increasingly requires ethical judgement alongside technical knowledge. Knowing how to use AI is not enough; one must also consider reliability, privacy, and how the technology affects its users.
Mr Fung focused on practical business value. He encouraged talents to first identify real entrepreneurial problems, and then decide how AI can help solve them. He also observed that education and professional training must continue evolving to keep pace with real-world industry applications.
These messages directly support JRH’s vision for an AI-assisted battery-design platform. The objective should not be to use AI simply because it is available. The platform must address real engineering difficulties, protect confidential information, produce explainable recommendations and keep qualified engineers responsible for final decisions.
Building Complete AI Capability
In a smaller session upstairs, several speakers shared their thoughts about AI development. One memorable guest, Martin Liu, used an illustrative hamburger analogy to explain the different layers of AI capability.
The “bread” represented essential general knowledge, including AI orientation, ethics, trends and fundamentals. The professional “meat” covered areas such as AI product management, technology ecosystems, ideation and innovation. The “sauces” represented soft skills including storytelling, decision-making and problem framing, while the “vegetables” represented technical skills such as AI integration, Python, large language models, prompting and retrieval-augmented generation.
The analogy demonstrated that AI capability is not built from technical knowledge alone. A successful platform also requires people who can define the right problem, gather reliable information, express an idea clearly and judge whether a proposed solution is appropriate.
This is particularly relevant to battery design. Engineering challenges often involve competing requirements rather than a single correct answer. A higher-energy solution may affect weight, temperature, cycle life, cost or charging time. An effective AI platform should help teams understand these relationships rather than merely produce quick answers.
From New Connections to Future Applications
The event concluded with informal “Meet & Spark” networking, where founders, speakers, professionals and young talent continued exchanging ideas after the formal programme.
JRH left the event with a broader understanding of emerging AI products and a clearer direction for applying AI within its own business. Potential next steps include studying an AI-assisted battery-design workflow, organising suitable internal engineering knowledge, and continuing technical discussions with developers of battery-powered intelligent products.
For customers, such a platform could eventually make early technical communication more efficient. Product requirements could be structured more clearly, relevant design experience could be identified more quickly, and several feasible battery directions could be compared before physical development begins.
For developers of robots, smart devices, portable electronics and other battery-powered products, JRH welcomes discussions about cell and pack selection, form factor, runtime, charging, reliability and stable supply. By combining experienced engineering judgement with carefully governed AI, JRH aims to develop better battery solutions and help customers move from an initial design challenge to a dependable product more efficiently.