Exploring Innovations in AI Memory and Storage at GMIF2026 Summit in Shenzhen
The GMIF2026 Innovation Summit, a major event focused on advancements in memory and storage technologies, concluded successfully on September 23, 2026, at the Renaissance Shenzhen Bay Hotel. Co-hosted by the Shenzhen Memory Industry Association (SMIA) and the School of Integrated Circuits at Peking University, this year's summit featured the theme "The Future Built on AI Memory and Storage," drawing a diverse range of industry leaders from various sectors, such as IDMs, memory solution providers, equipment suppliers, and automotive electronics.
This fifth installment of the GMIF has tracked the evolution of memory and storage technologies as they adapt to the increasing demands of artificial intelligence (AI). The summit spotlighted critical trends in inference efficiency, enterprise storage, and cloud-edge-device coordination, exploring the implications of the burgeoning token economy on industry dynamics.
A Platform for Collaboration
The summit commenced with remarks from Rixin Sun, President of the SMIA, who highlighted the significant growth of GMIF since its inception in 2019. Over five years, the event has evolved in scale and influence, consistently keeping pace with storage sector advancements. President Sun emphasized GMIF's future direction, aiming for a more specialized focus, fostering collaboration and technical exchange between storage companies and adjacent sectors, including AI computation.
AI-Driven Infrastructure Needs
A key discussion led by Daniel Yen from Morgan Stanley examined the impact of agentic AI on infrastructure requirements. With the complexity of AI workloads increasing, particularly in areas such as model loading and data management, Yen noted that investments in memory and storage technologies are seeing a corresponding rise, stressing the importance of overcoming the "memory wall" challenge.
Peking University's Yimao Cai further elaborated on the architectural shifts needed for AI inference, highlighting the necessity for high-bandwidth storage solutions to meet the escalating demands of large-scale models. He proposed that future architectures should integrate various technologies like HBM, NAND, and RRAM to optimize performance and cost-effectiveness.
Global Innovation in Memory Solutions
The discussions continued with insights from Samsung's Kevin Yoon, who outlined advancements in memory architecture motivated by the rise of agentic AI. Yoon detailed Samsung's innovations, including Z-NAND and PCIe Gen6 SSD technologies designed to efficiently support the increasing demands for capacity and energy efficiency.
Likewise, Maya Zhang from Sandisk discussed the central role of NAND flash technology as AI infrastructures evolve, while Benny Ni from Solidigm addressed how data tiering strategies can enhance memory utilization in AI applications.
Emerging Trends in AI Deployment
Topics of multi-device coordination in AI inference were explored by John Xavier Lionel from Arm, who emphasized the need for systemic optimization across cloud, edge, and device levels. The trend of integrating local storage for AI applications points to broader architectural shifts necessary to support the shifting landscapes of data processing.
AI's Impact on Storage Requirements
Discussion shifted towards how AI influences storage demands in various environments, led by Silicon Motion's Stanley Huang, who shared insights on custom quality of service (QoS) needs in multi-agent settings.
BIWIN’s Sam Sun discussed how diverse storage requirements from data centers, edge computing, and endpoint devices demonstrate the industry's adaptability, showcasing innovations like Mini SSDs and compact embedded storage tailored for resource-constrained environments.
From AI Concepts to Reality
As the event moved toward its conclusion, speakers highlighted the convergence of memory and storage ecosystems with AI applications across sectors, particularly automotive, showcasing innovations aimed at embedding AI deeper into workflows and enhancing operational efficiencies.
Looking Ahead
The GMIF2026 Summit successfully underscored the crucial role that memory and storage play in the AI era, both in current technologies and emerging applications. The event has solidified its reputation as a leading platform for discussions on advancements across the global memory and storage industry. With a shared goal of enhancing collaboration across supply chains and encouraging continued innovation, GMIF looks ahead to a future rich with opportunity in the AI memory sector.
This fifth installment of the GMIF has tracked the evolution of memory and storage technologies as they adapt to the increasing demands of artificial intelligence (AI). The summit spotlighted critical trends in inference efficiency, enterprise storage, and cloud-edge-device coordination, exploring the implications of the burgeoning token economy on industry dynamics.
A Platform for Collaboration
The summit commenced with remarks from Rixin Sun, President of the SMIA, who highlighted the significant growth of GMIF since its inception in 2019. Over five years, the event has evolved in scale and influence, consistently keeping pace with storage sector advancements. President Sun emphasized GMIF's future direction, aiming for a more specialized focus, fostering collaboration and technical exchange between storage companies and adjacent sectors, including AI computation.
AI-Driven Infrastructure Needs
A key discussion led by Daniel Yen from Morgan Stanley examined the impact of agentic AI on infrastructure requirements. With the complexity of AI workloads increasing, particularly in areas such as model loading and data management, Yen noted that investments in memory and storage technologies are seeing a corresponding rise, stressing the importance of overcoming the "memory wall" challenge.
Peking University's Yimao Cai further elaborated on the architectural shifts needed for AI inference, highlighting the necessity for high-bandwidth storage solutions to meet the escalating demands of large-scale models. He proposed that future architectures should integrate various technologies like HBM, NAND, and RRAM to optimize performance and cost-effectiveness.
Global Innovation in Memory Solutions
The discussions continued with insights from Samsung's Kevin Yoon, who outlined advancements in memory architecture motivated by the rise of agentic AI. Yoon detailed Samsung's innovations, including Z-NAND and PCIe Gen6 SSD technologies designed to efficiently support the increasing demands for capacity and energy efficiency.
Likewise, Maya Zhang from Sandisk discussed the central role of NAND flash technology as AI infrastructures evolve, while Benny Ni from Solidigm addressed how data tiering strategies can enhance memory utilization in AI applications.
Emerging Trends in AI Deployment
Topics of multi-device coordination in AI inference were explored by John Xavier Lionel from Arm, who emphasized the need for systemic optimization across cloud, edge, and device levels. The trend of integrating local storage for AI applications points to broader architectural shifts necessary to support the shifting landscapes of data processing.
AI's Impact on Storage Requirements
Discussion shifted towards how AI influences storage demands in various environments, led by Silicon Motion's Stanley Huang, who shared insights on custom quality of service (QoS) needs in multi-agent settings.
BIWIN’s Sam Sun discussed how diverse storage requirements from data centers, edge computing, and endpoint devices demonstrate the industry's adaptability, showcasing innovations like Mini SSDs and compact embedded storage tailored for resource-constrained environments.
From AI Concepts to Reality
As the event moved toward its conclusion, speakers highlighted the convergence of memory and storage ecosystems with AI applications across sectors, particularly automotive, showcasing innovations aimed at embedding AI deeper into workflows and enhancing operational efficiencies.
Looking Ahead
The GMIF2026 Summit successfully underscored the crucial role that memory and storage play in the AI era, both in current technologies and emerging applications. The event has solidified its reputation as a leading platform for discussions on advancements across the global memory and storage industry. With a shared goal of enhancing collaboration across supply chains and encouraging continued innovation, GMIF looks ahead to a future rich with opportunity in the AI memory sector.
Topics Consumer Technology）
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