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TechRadar
Wayne Williams

Samsung is going after Nvidia's billions with new AI chip — Mach-1 accelerator will combine CPU, GPU and memory to tackle inference tasks but not training

A person holding out their hand with a digital AI symbol.

Samsung is reportedly planning to launch its own AI accelerator chip, the 'Mach-1', in a bid to challenge Nvidia's dominance in the AI semiconductor market. 

The new chip, which will likely target edge applications with low power consumption requirements, will go into production by the end of this year and make its debut in early 2025, according to the Seoul Economic Daily.

The announcement was made during the company's 55th regular shareholders' meeting. Kye Hyun Kyung, CEO of Samsung Semiconductor, said the chip design had passed technological validation on FPGAs and that finalization of SoC was in progress.

Entirely new type of AGI semiconductor

The Mach-1 accelerator is designed to tackle AI inference tasks and will reportedly overcome the bottleneck issues that arise in existing AI accelerators when transferring data between the GPU and memory. This often results in slower data transmission speeds and reduced power efficiency.

The Mach-1 is reportedly a 'lightweight' AI chip, utilizing low-power (LP) memory instead of the costly HBM typically used in AI semiconductors.

The move is widely seen as Samsung's attempt to regain its position as the world's largest semiconductor company, fighting back against Nvidia which completely dominates the AI chip market and has seen its stock soar in recent months, making it the third most valuable company in the world behind Microsoft and Apple.

While the South Korean tech behemoth currently has no plans to challenge Nvidia's H100, B100, and B200 AI powerhouses, Seoul Economic Daily reports that Samsung has established an AGI computing lab in Silicon Valley to expedite the development of AI semiconductors. Kyung stated that the specialized lab is “working to create an entirely new type of semiconductor designed to meet the processing requirements of future AGI systems.’

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