How Meta Uses Deep Learning
8 engineering articles about Deep Learning from Meta's engineering team
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The article introduces the Parameter Vulnerability Factor (PVF), a new metric designed to assess AI systems' vulnerability to silent data corruptions (SDCs) in model parameters.
Xun Jiao
7 min read
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The 2019 @Scale Conference brought together over 1,300 engineers to discuss challenges and innovations in building scalable applications and services.
The article announces the stable release of PyTorch 1. 0 at the NeurIPS conference, highlighting its new production-oriented features and extensive community growth.
Yangqing Jia
6 min read
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Oculus Connect 5 is an annual virtual reality developer conference where VR and augmented reality developers share insights and advancements.
5 min read
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Facebook announced significant advancements in AI development with the release of PyTorch 1. 0, emphasizing a more robust ecosystem of partners and production capabilities.
Joseph Spisak
6 min read
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The article announces the release of PyTorch 1. 0, an open-source AI framework that bridges the gap between research and production.
Bill Jia
6 min read
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The article introduces Big Basin, Facebook's next-generation AI hardware designed to enhance the performance of AI services.
Kevin Lee
5 min read
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The article discusses the pervasive role of artificial intelligence (AI) in everyday life and its implications for future technologies and job markets.
Joaquin Quiñonero Candela
12 min read
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