Revolution in language processing: language models without matrix multiplication

- Edge computing enhances NLP by reducing latency, improving privacy, and optimizing resources.

- NLP models can now run on peripheral devices, improving real-time applications like voice assistants and translation.

- Alternatives to matrix multiplication (MatMul) are emerging, such as AdderNet and binary networks, reducing computational cost.

- MatMul-free models improve memory efficiency and execution speed, making them suitable for large-scale language models.

- These models are ideal for resource-limited devices like smartphones and IoT sensors.

- Future research will focus on optimizing MatMul-free models for even better performance and scalability.

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