This move strengthens the company’s technical leadership and reinforces its long-term competitive moat in AI inference and Token production.
World-Class Expertise Reinforcing Technical Moat
Academician Wei-Min Zheng is a globally recognized authority in high-performance computing, distributed systems, and AI. His work on scalable storage architectures and parallel systems has had significant academic and industrial impact, earning multiple national science and technology awards.
Professor Yongwei Wu, an IEEE Fellow and AAIA Fellow, is an internationally recognized expert in parallel and distributed systems, cloud storage, and big data infrastructure, with multiple prestigious awards.
Their addition significantly enhances Approaching.ai’s ability to drive system-level innovation in large-scale AI inference—an area increasingly viewed as the core value layer of the AI industry.
Capturing the Core Value Layer: Inference and Token Production
As large models scale globally, demand for AI Tokens is growing exponentially. Inference is rapidly becoming the primary cost center and a key determinant of commercial viability.
Approaching.ai focuses on high-efficiency AI Token production, improving Token output per unit of compute and reducing deployment costs for enterprises.
Through system-level innovation, the company addresses key industry challenges:
- Fragmented computing resources
- Low inference efficiency
- Lack of standardized infrastructure
Its technologies—such as heterogeneous computing coordination and memory-compute optimization—enable unified execution across diverse hardware and models, creating a scalable and cost-efficient inference layer.
Strong Origin and Execution Capability
Originating from Tsinghua University’s High-Performance Computing Institute, Approaching.ai brings over 20 years of expertise in computing and storage systems, along with proven capability in translating research into industrial deployment.
Capital Validation and Market Confidence
Approaching.ai has attracted strong backing from leading venture capital firms and strategic investors, including GL Ventures, Verity Ventures, Shanghai Guofang Innovation Private Equity Fund Partnership (Limited Partnership), Xinglian Capital, Shangshi Capital, Tsinghua Capital, and other industry partners.
This reflects strong market confidence in the company’s positioning within the rapidly growing AI infrastructure market, particularly in inference optimization.
Looking Ahead
With strengthened scientific leadership, Approaching.ai will continue advancing enterprise-grade inference solutions and scalable AI infrastructure.
By focusing on Token production, the company targets one of the highest-leverage segments in the AI value chain and is well positioned to benefit from continued growth in AI adoption.
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The issuer is solely responsible for the content of this announcement.
