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  "full_text": "Addition is All You Need for Energy-efficient Language Models\n\nProposes an algorithm that approximates floating point multiplication with one integer addition operations.\n\nIt is less computationally intensive than 8-bit floating point but achieves higher precision.\n\n\"Since multiplying floating point numbers requires substantially higher energy compared to integer addition operations, applying the L-Mul operation in tensor processing hardware can potentially reduce 95% energy cost by elementwise floating point tensor multiplications and 80% energy cost of dot products.\"\n\nRefreshing to see more research around efficient ML algorithms. It's one of my favorite research areas, so I just wanted to highlight this recent paper. Lots of interesting insights and results in the paper.",
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