Benchmarking HBM! SoftBank teams up with Intel to develop "ZAM": aiming to make AI memory cheaper and more energy-saving

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SoftBank and Intel are joining forces to bet on next-generation AI memory technology, seeking to carve out a new path in a market landscape dominated by high-bandwidth memory (HBM). Their jointly developed "Z-Angle Memory" (ZAM) project focuses on reducing power consumption and costs, directly targeting the current bottleneck of energy consumption and tight supply chain issues faced by AI.

Saimemory, a SoftBank subsidiary, announced on Tuesday that it has signed a cooperation agreement with Intel to jointly advance the commercialization of this next-generation memory technology for artificial intelligence and high-performance computing. The technology aims to improve the traditional Dynamic Random Access Memory (DRAM) architecture to meet the growing performance demands of AI applications.

According to a press release from SoftBank, a prototype product of the ZAM project is expected to be completed in the fiscal year ending March 31, 2028, with commercialization targeted for fiscal year 2029.

In a statement, Dr. Joshua Fryman, Intel Fellow and Chief Technology Officer of Intel's Government Technology division, said that standard memory architectures cannot meet AI demands, and that Intel's newly-developed architecture and assembly methods enhance DRAM performance while reducing power consumption and cost.

After the news was released, SoftBank’s share price rose 5.13% in Tokyo trading.

Intel’s stock rose 5%.

Technology Originates from U.S. Government Project

Saimemory was established in December 2024 and will leverage Intel’s expertise in memory technology, especially the results developed by Intel as a participant in the U.S. Department of Energy's advanced memory technology project.

This Department of Energy project focuses on developing core technologies for advanced memory, with Intel responsible for improving the performance and energy efficiency of new-generation DRAM used in computers and servers.

According to a report by Nikkei Asia last year, Japanese multinational IT equipment and services company Fujitsu also participated in the project.

AI Demand Triggers Supply Chain Strain

The industry backdrop to this collaboration is the surge in memory demand from AI-related applications, with demand growth far outpacing supply capacity and causing shortages across the entire memory supply chain.

Currently, AI chips widely use high-performance memory solutions such as HBM, but these products are difficult to produce, expensive, and have highly concentrated supply.

The ZAM project seeks to provide an alternative by improving traditional DRAM architecture, reducing manufacturing complexity and cost while ensuring performance, which could offer more options for the AI hardware supply chain.

Energy Efficiency Becomes a Core Consideration

The ZAM project’s emphasis on energy efficiency reflects the industry’s growing concern over the massive energy consumption of AI computing. Joshua Fryman stated that Intel’s newly developed memory architecture and assembly methods will enable broader applications over the next decade, positioning the technology to greatly reduce power consumption while enhancing performance.

As AI models continue to scale up, requirements for memory bandwidth and capacity during training and inference processes keep climbing, with corresponding energy consumption becoming one of the bottlenecks restricting AI development.

If more energy-efficient memory technology can be successfully commercialized, it will directly impact data center operating costs and the economic viability of AI applications.

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