{"id":852,"date":"2024-04-11T16:30:58","date_gmt":"2024-04-11T16:30:58","guid":{"rendered":"https:\/\/fde.cat\/index.php\/2024\/04\/11\/building-new-custom-silicon-for-metas-ai-workloads\/"},"modified":"2024-04-11T16:30:58","modified_gmt":"2024-04-11T16:30:58","slug":"building-new-custom-silicon-for-metas-ai-workloads","status":"publish","type":"post","link":"https:\/\/fde.cat\/index.php\/2024\/04\/11\/building-new-custom-silicon-for-metas-ai-workloads\/","title":{"rendered":"Building new custom silicon for Meta\u2019s AI workloads"},"content":{"rendered":"<p>The post <a href=\"https:\/\/engineering.fb.com\/2024\/04\/11\/ai-research\/building-new-custom-silicon-for-metas-ai-workloads\/\">Building new custom silicon for Meta\u2019s AI workloads<\/a> appeared first on <a href=\"https:\/\/engineering.fb.com\/\">Engineering at Meta<\/a>.<\/p>\n<p>Engineering at Meta<\/p>","protected":false},"excerpt":{"rendered":"<p>The post Building new custom silicon for Meta\u2019s AI workloads appeared first on Engineering at Meta. Engineering at Meta<\/p>\n","protected":false},"author":0,"featured_media":0,"comment_status":"","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spay_email":"","footnotes":""},"categories":[7],"tags":[],"class_list":["post-852","post","type-post","status-publish","format-standard","hentry","category-technology","entry"],"jetpack_featured_media_url":"","jetpack-related-posts":[{"id":787,"url":"https:\/\/fde.cat\/index.php\/2023\/11\/15\/watch-metas-engineers-on-building-network-infrastructure-for-ai\/","url_meta":{"origin":852,"position":0},"title":"Watch: Meta\u2019s engineers on building network infrastructure for AI","date":"November 15, 2023","format":false,"excerpt":"Meta is building for the future of AI at every level \u2013 from hardware like MTIA v1, Meta\u2019s first-generation AI inference accelerator to publicly released models like Llama 2, Meta\u2019s next-generation large language model, as well as new generative AI (GenAI) tools like Code Llama. Delivering next-generation AI products and\u2026","rel":"","context":"In &quot;Technology&quot;","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":773,"url":"https:\/\/fde.cat\/index.php\/2023\/10\/18\/how-meta-is-creating-custom-silicon-for-ai\/","url_meta":{"origin":852,"position":1},"title":"How Meta is creating custom silicon for AI","date":"October 18, 2023","format":false,"excerpt":"With the recent launches of MTIA v1,\u00a0 Meta\u2019s first-generation AI inference accelerator, and Llama 2,\u00a0 the next generation of Meta\u2019s publicly available large language model, it\u2019s clear that Meta is focused on advancing AI for a more connected world. Fueling the success of these products are world-class infrastructure teams, including\u2026","rel":"","context":"In &quot;Technology&quot;","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":629,"url":"https:\/\/fde.cat\/index.php\/2022\/09\/07\/open-sourcing-taobench-an-end-to-end-social-network-benchmark\/","url_meta":{"origin":852,"position":2},"title":"Open-sourcing TAOBench: An end-to-end social network benchmark","date":"September 7, 2022","format":false,"excerpt":"What the research is: The continued emergence of large social network applications has introduced a scale of data and query volume that challenges the limits of existing data stores. However, few benchmarks accurately simulate these request patterns, leaving researchers in short supply of tools to evaluate and improve upon these\u2026","rel":"","context":"In &quot;Technology&quot;","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":670,"url":"https:\/\/fde.cat\/index.php\/2023\/01\/27\/watch-metas-engineers-discuss-optimizing-large-scale-networks\/","url_meta":{"origin":852,"position":3},"title":"Watch Meta\u2019s engineers discuss optimizing large-scale networks","date":"January 27, 2023","format":false,"excerpt":"Managing network solutions amidst a growing scale inherently brings challenges around performance, deployment, and operational complexities.\u00a0 At Meta, we\u2019ve found that these challenges broadly fall into three themes: 1.) \u00a0 Data center networking: Over the past decade, on the physical front, we have seen a rise in vendor-specific hardware that\u2026","rel":"","context":"In &quot;Technology&quot;","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":875,"url":"https:\/\/fde.cat\/index.php\/2024\/06\/10\/serverless-jupyter-notebooks-at-meta\/","url_meta":{"origin":852,"position":4},"title":"Serverless Jupyter Notebooks at Meta","date":"June 10, 2024","format":false,"excerpt":"At Meta, Bento, our internal Jupyter notebooks platform, is a popular tool that allows our engineers to mix code, text, and multimedia in a single document. Use cases run the entire spectrum from what we call \u201clite\u201d workloads that involve simple prototyping to heavier and more complex machine learning workflows.\u2026","rel":"","context":"In &quot;Technology&quot;","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":680,"url":"https:\/\/fde.cat\/index.php\/2023\/02\/16\/inside-metas-first-smart-glasses\/","url_meta":{"origin":852,"position":5},"title":"Inside Meta\u2019s first smart glasses","date":"February 16, 2023","format":false,"excerpt":"What\u2019s new: Meta is sharing the inside story of how it developed the Ray-Ban Stories smart glasses. Why it matters: Creating Ray-Ban Stories meant Meta\u2019s engineers had to take on new challenges to build smart glasses that married complex engineering dynamics. How do you make something that features cameras, microphones,\u2026","rel":"","context":"In &quot;Technology&quot;","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"_links":{"self":[{"href":"https:\/\/fde.cat\/index.php\/wp-json\/wp\/v2\/posts\/852","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/fde.cat\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/fde.cat\/index.php\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/fde.cat\/index.php\/wp-json\/wp\/v2\/comments?post=852"}],"version-history":[{"count":0,"href":"https:\/\/fde.cat\/index.php\/wp-json\/wp\/v2\/posts\/852\/revisions"}],"wp:attachment":[{"href":"https:\/\/fde.cat\/index.php\/wp-json\/wp\/v2\/media?parent=852"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/fde.cat\/index.php\/wp-json\/wp\/v2\/categories?post=852"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/fde.cat\/index.php\/wp-json\/wp\/v2\/tags?post=852"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}