The Zeta AI Chip is a domestically produced AI computing chip focused on high energy efficiency, featuring compute-in-memory, RISC-V, and Chiplet-inspired architectures, primarily for edge computing and AI inference.
Its core advantages lie in the compute-in-memory architecture that dramatically reduces data movement, combined with the flexibility of RISC-V and Chiplet 3D stacking to achieve a balance of high performance and energy efficiency.
Primarily applicable to scenarios with high power and real-time requirements, such as IoT endpoints, mobile devices, edge servers, and AI training and inference in resource-constrained environments.
The Zeta chip uses a specialized architecture (such as compute-in-memory) with hardware-level optimizations for AI computing, achieving higher efficiency for specific inference tasks rather than pursuing universal graphics processing power.
Based on the open-source RISC-V instruction set architecture, with AI-focused custom instruction set extensions to achieve better performance and ecosystem autonomy.
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