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How Microsoft’s next-gen BitNet architecture is turbocharging LLM efficiency
A smart combination of quantization and sparsity allows BitNet LLMs to become even faster and more compute/memory efficient
One-bit large language models (LLMs) have emerged as a promising approach to making generative AI more accessible and affordable. By representing model weights with a very limited number of bits, 1-bit LLMs dramatically reduce the memory and computational resources required to run them. BitNet introduces a new computation paradigm that minimizes the need for matrix multiplication, a primary focus in current hardware design optimization.”
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