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Summary
| Description | English: It shows the rapid increase in the computing used to train large language models. It also shows that the training cost of the best closed large language models seems much higher than the training cost of the best open-weight ones, leading to higher performance. The training cost of models like GPT-4 is not publicly known, so this is just an estimate. The data is from Epoch in 2023, and the chart is from Stanford University's 2024 AI index. Euskara: AA eredu batzuen prestakuntza-kostu zenbatetsia - AA indizea 2024 Hizkuntza eredu handiak entrenatzeko erabiltzen den konputazio-lanaren gorakada azkarra erakusten du. Halaber, erakusten du hizkuntza-eredu handi eta itxi onenen entrenamendu-kostuak eredu irekiko onenen entrenamendu-kostuak baino askoz ere handiagoak diruditela, eta horrek errendimendu handiagoa ekartzen duela. GPT-4 eta antzeko ereduen prestakuntza-kostua ez da publikoki ezagutzen; beraz, estimazio bat baino ez da. Datuak Epoch-enak dira 2023an, eta grafikoa Stanfordeko Unibertsitateko AI index-ekoa da 2024an. | ||
| Date | |||
| Source | https://aiindex.stanford.edu/report/#individual-chapters (chapter 1, image 3) | ||
| Author | Stanford Institute for Human-Centered Artificial Intelligence (permission obtained by email from the AI index research manager) | ||
| Permission (Reusing this file) |
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
|---|---|---|---|---|---|
| current | 20:52, 6 June 2024 | | 2,560 × 1,361 (147 KB) | Alenoach | Uploaded a work by Stanford Institute for Human-Centered Artificial Intelligence (permission obtained by email from the AI index research manager) from https://aiindex.stanford.edu/report/#individual-chapters with UploadWizard |
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