8 Proven Strategies to Scale Your AI Systems Like OpenAI! 🚀 (Ep. 274)

Data Science at Home - En podcast av Francesco Gadaleta

Kategorier:

In this episode of Data Science at Home, we’re diving deep into the powerful strategies that top AI companies, like OpenAI, use to scale their systems to handle millions of requests every minute! From stateless services and caching to the secrets of async processing, discover 8 essential strategies to make your AI and machine learning systems unstoppable. Whether you're working with traditional ML models or large LLMs, these techniques will transform your infrastructure. Hit play to learn how the pros do it and apply it to your own projects!   LISTEN / SUBSCRIBE TO THE PODCAST YouTube: https://www.youtube.com/@DataScienceatHome Apple Podcasts: https://podcasts.apple.com/us/podcast/data-science-at-home/id1069871378 Podbean Podcasts: https://datascienceathome.podbean.com/ Player Fm: https://player.fm/series/data-science-at-home-2600992   Chapters 00:00 Intro 00:34 Scalability Strategies 01:08 Stateless Services 02:47 Horizontal Scaling 04:51 Load Balancing 06:14 Auto Scaling 07:41 Caching 09:27 Database Replication 11:07 Database Sharding 12:54 Async Processing 14:50 Infographics   RESOURCES & LINKS Data Science at home: https://datascienceathome.com Amethix Technologies: https://amethix.com   CONNECT WITH US! Instagram: https://www.instagram.com/datascienceathome/ Twitter: @datascienceathome Facebook: https://www.facebook.com/datascienceAH LinkedIn: https://www.linkedin.com/company/data-science-at-home-podcast Discord Channel: https://discord.gg/4UNKGf3 NEW TO DATA SCIENCE AT HOME? Welcome! Data Science at Home explores the latest in AI, data science, and machine learning. Whether you’re a data professional, tech enthusiast, or just curious about the field, our podcast delivers insights, interviews, and discussions. Learn more at https://datascienceathome.com   SEND US MAIL! We love hearing from you! Send us mail at:  [email protected]

Visit the podcast's native language site