機械学習の研究、プログラミングの洞察、AIコミュニティの議論をYannic Kilcherと共に探求し、AIが社会に与える影響やその課題を浮き彫りにします。
Efficient Streaming Language Models with Attention Sinks (Paper Explained)
32 mins • Oct 17, 2023
Charts
- 197Decreased by 4
'/%3e%3cpath%20d='M74.965,77.269%20C74.795,75.733%2074.283,74.624%2073.259,73.6%20C71.339,71.595%2067.968,70.272%2064,70.272%20C60.032,70.272%2056.661,71.552%2054.741,73.6%20C53.76,74.667%2053.205,75.733%2053.035,77.269%20C52.693,80.256%2052.907,82.816%2053.248,86.955%20C53.589,90.88%2054.229,96.128%2055.04,101.419%20C55.637,105.216%2056.107,107.264%2056.533,108.715%20C57.259,111.104%2059.861,113.152%2064,113.152%20C68.139,113.152%2070.784,111.061%2071.467,108.715%20C71.893,107.264%2072.363,105.216%2072.96,101.419%20C73.771,96.085%2074.411,90.88%2074.752,86.955%20C75.136,82.816%2075.307,80.256%2074.965,77.269%20z'%20fill='%23FFFFFF'%20id='XMLID_657_'/%3e%3cpath%20d='M74.496,55.509%20C74.496,61.312%2069.803,66.005%2064,66.005%20C58.197,66.005%2053.504,61.312%2053.504,55.509%20C53.504,49.707%2058.197,45.013%2064,45.013%20C69.803,45.013%2074.496,49.749%2074.496,55.509%20z'%20fill='%23FFFFFF'%20id='XMLID_655_'/%3e%3cpath%20d='M63.872,14.165%20C39.381,14.251%2019.328,34.133%2018.987,58.624%20C18.731,78.464%2031.403,95.445%2049.109,101.675%20C49.536,101.845%2049.963,101.461%2049.92,101.035%20C49.707,99.499%2049.451,97.963%2049.28,96.427%20C49.195,95.872%2048.853,95.445%2048.384,95.189%20C34.389,89.088%2024.619,75.051%2024.789,58.795%20C25.003,37.461%2042.411,20.096%2063.701,19.925%20C85.504,19.755%20103.296,37.419%20103.296,59.179%20C103.296,75.264%2093.568,89.088%2079.701,95.189%20C79.189,95.403%2078.848,95.872%2078.805,96.427%20C78.592,97.963%2078.379,99.499%2078.165,101.035%20C78.08,101.504%2078.549,101.845%2078.976,101.675%20C96.512,95.531%20109.099,78.805%20109.099,59.179%20C109.013,34.347%2088.747,14.123%2063.872,14.165%20z'%20fill='%23FFFFFF'%20id='XMLID_653_'/%3e%3cpath%20d='M62.848,29.099%20C46.891,29.696%2034.091,42.88%2033.877,58.837%20C33.749,69.333%2038.997,78.635%2047.061,84.139%20C47.445,84.395%2048,84.096%2048,83.627%20C47.872,81.792%2047.872,80.171%2047.957,78.464%20C48,77.909%2047.787,77.397%2047.36,77.013%20C42.453,72.405%2039.467,65.835%2039.637,58.581%20C39.979,45.781%2050.261,35.371%2063.061,34.859%20C76.971,34.304%2088.405,45.483%2088.405,59.221%20C88.405,66.219%2085.419,72.533%2080.683,77.013%20C80.299,77.397%2080.085,77.909%2080.085,78.464%20C80.171,80.128%2080.128,81.749%2080.043,83.584%20C80,84.053%2080.555,84.395%2080.981,84.096%20C88.917,78.677%2094.165,69.504%2094.165,59.179%20C94.208,42.197%2080,28.416%2062.848,29.099%20z'%20fill='%23FFFFFF'%20id='XMLID_651_'/%3e%3c/g%3e%3c/svg%3e)
最近のエピソード
Oct 17, 2023
Efficient Streaming Language Models with Attention Sinks (Paper Explained)
32 mins
Oct 17, 2023
Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution (Paper Explained)
47 mins
Oct 5, 2023
Retentive Network: A Successor to Transformer for Large Language Models (Paper Explained)
28 mins
Oct 5, 2023
Reinforced Self-Training (ReST) for Language Modeling (Paper Explained)
53 mins
Aug 28, 2023
[ML News] LLaMA2 Released | LLMs for Robots | Multimodality on the Rise
44 mins
