Google Designs a Gemini-Specific AI Chip Called Frozen v2
Google is designing Frozen v2, a chip that hardwires parts of its Gemini model into silicon and could serve six to ten times more tokens per watt, targeting deployment by 2028.
AI Accelerator
An AI accelerator is a processor or hardware system optimized for the highly parallel mathematical operations used by machine learning models. GPUs, tensor processing units, neural processing units, and purpose-built inference chips are common examples. Compared with general-purpose processors, accelerators can increase throughput, reduce latency, or lower the energy required to train and run models. Their design may emphasize matrix multiplication, low-precision arithmetic, fast memory access, or communication between many chips. Choosing an accelerator depends on the model architecture, batch size, software support, deployment environment, power budget, and whether the workload involves training, real-time inference, or both.
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