HONG KONG, June 12, 2026 (GLOBE NEWSWIRE) — 3 E Network Technology Group Limited (Nasdaq: MASK) (the “Company” or “3 E Network”), a business-to-business (“B2B”) information technology (“IT”) business solutions provider, committed to becoming a next-generation artificial intelligence (“AI”) infrastructure solutions provider, today released strategic insights from its Chief Executive Officer, Dr. Tingjun Yang. Following the Company’s recent strategic partnership with California-based advanced robotics enterprise Aladdin Alaris AI, Dr. Yang shared 3 E Network’s assessment of the service robotics industry’s evolution and outlined the Company’s strategic roadmap spanning underlying silicon technologies and broader application ecosystem development.
Industry Insight: The Evolution from “Spatial Intelligence” to “Embodied AI”
Addressing industry trends, Dr. Yang noted: “AI models are accelerating their migration to the edge. Moving forward, robots will require not only basic semantic comprehension but also a mastery of complex ‘Spatial Intelligence’ and laws of physical interaction.”
“Robotics technology is gradually moving beyond traditional ‘Rule-based Programming,’ pivoting toward policy generation that integrates Reinforcement Learning and ‘Sim-to-Real’ transfer. Robotics are expected to evolve into ‘Advanced Embodied AI’ systems equipped with cross-scenario generalization and Lifelong Learning capabilities, enabling them to adapt to diverse commercial and home environments. One of the key drivers of this evolution is the continuous increase in edge computing density. 3 E Network’s strategic goal is to provide scalable and reliable underlying computational support for intelligent terminals in the physical world.”
Hardware Reconstruction: Silicon Innovation as the Key to Breaking Performance Bottlenecks
To overcome current computational bottlenecks, the CEO pointed out that upgrading underlying hardware would be essential: “When processing multi-modal sensor fusion, such as concurrent inputs from high-framerate vision, spatial radar, and tactile arrays, traditional merchant silicon may face limitations related to the ‘Von Neumann bottleneck’ and the ‘Memory Wall,’ which may contribute to higher power consumption and non-deterministic latency. The computing infrastructure for next-generation embodied intelligence cannot rely solely on the cloud; it must be efficiently deployed at the edge.”
Recognizing this shift, 3 E Network is advancing the hardware reconstruction of edge computing. “We believe that heterogeneous computing architectures and Edge AI SoCs optimized for multi-modal workloads are important technological pathways to address these bottlenecks. By optimizing the data path at the silicon level and integrating dedicated tensor acceleration engines with low-latency on-chip SRAM, our design aims to reduce the energy consumption associated with data movement at the hardware level. This is expected to enhance robots’ environmental perception precision and response speed, enabling the efficient execution of quantized Large Language Models and Vision-Language Models within controlled power budgets. Hardware will truly serve as a critical layer supporting real-time robotic perception and control.”
Software Synergy: Reducing System Friction via “Hardware-Software” Co-design
Beyond silicon, Dr. Yang emphasized that “full-stack synergy” is key to unlocking hardware potential: “In the era of Embodied AI, hardware lacking a deeply coupled software stack often underperforms. Traditional stacked systems cause the decision-making commands of AI models to experience friction across layers of middleware. In 3 E Network’s technological blueprint, we promote ‘Hardware-Software Co-design’, from chip-level design to upper-layer algorithmic frameworks.”
“The underlying real-time control algorithms and customized compilers we are developing aim for deep ‘Instruction-Set Level’ integration with our proprietary chips. This full-stack optimization is designed to translate semantic instructions generated by edge models into fine-grained motion control commands that drive joint motors with low latency. It is designed to reduce the scheduling latency inherent in traditional operating systems, with the goal of enabling computing power to be translated more efficiently into smooth, closed-loop control of the mechatronic system. This is the foundational support for enabling more responsive and adaptive robotic movements and for adapting to dynamic, unstructured environments.”
Scenario Expansion: Building a Pan-Robotics Computing Platform
Regarding commercial deployment, Dr. Yang noted: “The traditional robotics market is relatively fragmented. Developing different form factors, such as wheeled, quadruped, or bipedal humanoid robots, typically involves high Non-Recurring Engineering costs. 3 E Network is dedicated to building a versatile and scalable underlying computing platform, aligning with the industry trend of Software-Defined Robotics.”
“The needs of an aging population and the growth of the smart healthcare market represent our current commercial entry point. Through eldercare robots powered by 3 E Network’s computing foundation, we are actively exploring the potential of the silver economy. Leveraging a standardized underlying compute platform and a Modular Application Framework, our technology stack can potentially extend to industrial collaborative robots, logistics, and general-purpose humanoid robots, achieving cross-domain generalization and expanding the market boundaries of robotics.”
Commercial and Ecosystem Vision: Fostering a “Developer-Friendly” Ecosystem
Summarizing the Company’s commercialization path, Dr. Yang underscored the value of an open ecosystem: “In the era of AI computing, the commercial competitive advantage is not just silicon performance, but an active developer ecosystem. 3 E Network is actively establishing partnerships with robotics enterprises across various verticals.”
“Our recent strategic alliance with California-based advanced robotics enterprise Aladdin Alaris AI in the smart healthcare sector is an important step toward this vision. This provides a potential application environment for our technology in healthcare-related scenarios and marks a concrete step in building an open ecosystem. Moving forward, we will deepen our underlying chip technology while providing standardized, developer-friendly middleware and toolchains, with the goal of lowering hardware integration barriers for robotics startups and algorithmic developers. By empowering industry developers, 3 E Network strives to translate core technological advantages into long-term enterprise value across economic cycles.”
About 3 E Network Technology Group Limited
3 E Network Technology Group Limited is a business-to-business (“B2B”) information technology (“IT”) business solutions provider committed to becoming a next-generation artificial intelligence (“AI”) infrastructure solutions provider. It upholds the industry consensus of “AI and energy symbiosis” and has a strong vision in the field of energy investment. The Company’s business comprises two main portfolios: the data center operation services portfolio and the software development portfolio. For more information, please visit the Company’s website at https://3emask.com/.
Forward-Looking Statements
Certain statements in this announcement are forward-looking statements. These forward-looking statements involve known and unknown risks and uncertainties and are based on the Company’s current expectations and projections about future events that the Company believes may affect its financial condition, results of operations, business strategy, and financial needs. Investors can identify these forward-looking statements by words or phrases such as “approximates,” “assesses,” “believes,” “hopes,” “expects,” “anticipates,” “estimates,” “projects,” “intends,” “plans,” “will,” “would,” “should,” “could,” “may” or similar expressions. The Company undertakes no obligation to update or revise publicly any forward-looking statements to reflect subsequent events or circumstances, or changes in its expectations, except as may be required by law. Although the Company believes that the expectations expressed in these forward-looking statements are reasonable, it cannot assure you that such expectations will turn out to be correct, and the Company cautions investors that actual results may differ materially from the anticipated results and encourages investors to review other factors that may affect the Company’s future results in the Company’s registration statement and other filings with the U.S. Securities and Exchange Commission.
For more information, please contact:
3 E Network Technology Group Limited
Investor Relations Department
Email: ird@3emask.com
Website: https://3emask.com/
