{"id":6894,"date":"2025-09-17T04:02:23","date_gmt":"2025-09-17T04:02:23","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/09\/17\/ai-scaling-laws-universal-guide-estimates-how-llms-will-perform-based-on-smaller-models-in-same-family\/"},"modified":"2025-09-17T04:02:23","modified_gmt":"2025-09-17T04:02:23","slug":"ai-scaling-laws-universal-guide-estimates-how-llms-will-perform-based-on-smaller-models-in-same-family","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/09\/17\/ai-scaling-laws-universal-guide-estimates-how-llms-will-perform-based-on-smaller-models-in-same-family\/","title":{"rendered":"AI scaling laws: Universal guide estimates how LLMs will perform based on smaller models in same family"},"content":{"rendered":"<p>    AI scaling laws: Universal guide estimates how LLMs will perform based on smaller models in same family<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>When researchers are building large language models (LLMs), they aim to maximize performance under a particular computational and financial budget. Since training a model can amount to millions of dollars, developers need to be judicious with cost-impacting decisions about, for instance, the model architecture, optimizers, and training datasets before committing to a model.<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><\/p>\n<p> \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/techxplore.com\/news\/2025-09-ai-scaling-laws-universal-llms.html\">Go to techxplore<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI scaling laws: Universal guide estimates how LLMs will perform based on smaller models in same family When researchers are building large language models (LLMs), they aim to maximize performance under a particular computational and financial budget. Since training a model can amount to millions of dollars, developers need to be judicious with cost-impacting decisions [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[54,45],"tags":[50],"class_list":["post-6894","post","type-post","status-publish","format-standard","hentry","category-computer-sciences","category-techxplore","tag-techxplore"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/6894"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=6894"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/6894\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=6894"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=6894"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=6894"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}