"Overview of Mainland's Semiconductor Venture Investment"

Dr. Yan ZHENG (Riverhead Capital Investment Management Co., Ltd.——RHC)

Abstract

Mainland Domestic Semiconductor Startup Ecosystem: History and Trends; Semiconductor Investment Case Studies; and Introduction to Riverhead Capital Investment Management Co., Ltd. - RHC.

"Venture Capital Insights and Opportunities in the Age of AI Revolution"

Ms. Yuan GONG (HongShan Capital Group)

Abstract

The rapid advancement of artificial intelligence (AI) is reshaping industries, economies, and societal structures, presenting unprecedented opportunities for venture capital (VC) investors. This report explores the transformative impact of AI on global innovation ecosystems and identifies key investment trends, challenges, and emerging opportunities in this dynamic landscape.  

As AI technologies—from generative models to autonomous systems—mature, startups leveraging AI are attracting record-breaking funding, disrupting traditional sectors, and creating new markets. The report analyzes critical domains where AI-driven innovation thrives, including healthcare, fintech, enterprise automation, and climate tech, while highlighting the risks of market saturation and ethical concerns. Additionally, it examines the evolving strategies of VC firms, from early-stage bets on foundational AI models to late-stage investments in scalable applications.  

Geopolitical factors, regulatory developments, and talent acquisition challenges are also discussed as pivotal influences on AI investment trajectories. By synthesizing data from leading markets and interviews with industry experts, this report provides actionable insights for investors seeking to navigate the AI boom. Ultimately, it underscores the importance of balancing aggressive growth with responsible innovation to harness AI's long-term potential while mitigating its risks.  

"Introduction and case study on ZJU-IC Industry & Academic Collaboration"

Dr. Feijun ZHENG (Zhejiang University) 

Abstract

The principles of IC college at Zhejiang University is  integration of industry and R&D, collaboration of science and education, we are actively exploring a new type of education and scientific research system and system innovation oriented to industry needs. With the 300mm 55nm CMOS mini-line based-in Zhejiang University, Hangzhou, we bring together brilliant ideas from university to support IC Industry. We provide Industry-level facilities and capability for R&D and low-volume manufacturing. With the capability of DTCO, providing standard and customized process development for customers.  The institute of VLSI Design focus on embedded IP core and processor design field, the series of CPU cores have accumulated more than 1 billion devices.

"Building Computing Systems for Embodied Artificial Intelligence"

Dr. Shaoshan LIU (Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS)) 

Abstract

Embodied AI integrates artificial intelligence into physical systems, enabling robots to perceive, learn, and interact with dynamic environments. However, its development faces key computing challenges: integrating diverse functions like perception and control into cohesive software, processing multimodal sensor data in real time under energy and concurrency constraints, and overcoming data scarcity due to the difficulty of collecting diverse real-world robotic interactions. To address these issues, a layered software architecture is proposed to abstract hardware complexity, streamline function integration, and support foundational AI models. A novel computing architecture enhances efficiency through synchronized sensor fusion, dataflow accelerators, and hardware-software co-design, enabling real-time AI execution on edge devices. Additionally, design automation leverages synthetic data and digital twin simulations to train models in virtual environments, minimizing reliance on extensive physical data collection. Together, these approaches aim to enhance the flexibility, efficiency, and scalability of embodied AI systems. 

"Empowering the Future of Embodied AI"

Mr. Mark MOK (ACCESS)

Abstract

HarbourTek aims to advance embodied AI, combining artificial intelligence and chip technologies to create intelligent systems. The development focus is on developing energy-efficient edge computing devices for large AI models, addressing challenges like real-time computing, privacy, and cost. Existing devices, like GPUs, are power-hungry and costly. To overcome these challenges, HarbourTek leverages software-hardware co-design, model compression techniques, and advanced digital in-memory computing technology. The goal is to create flexible and configurable systems for embodied AI applications, enhancing performance, energy efficiency, and adaptability.

"Innovations and Developments in GPU Open Source Ecosystem from MetaX"

Dr. Zeyao HAN (MetaX)

Abstract

1. DeepSeek Open Source Ushers in the Era of Large Model Equal Rights 
2. Analysis of AI Open Source Ecosystem Status 
3. Introduction to MetaX GPU Open Source Ecosystem 
4. Progress of MetaX GPU Ecosystem Open Source 
5. About Future Constraints