))
Caching AI for Speed and Savings: The Key to Making Your LLM Feel "Smarter"
Manage episode 510935272 series 3656088
A tartalmat a DataQubi biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a DataQubi vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
Explores the economic imperative and psychological accelerator of caching large language model (LLM) calls for production scalability. Learn why speed is psychology, and how responses under 500ms feel "smart" compared to 3-second delays that erode user trust. Implementing caching—from basic Response Caching to advanced Semantic and KV Caching—can deliver powerful benefits: cutting latency 10x, reducing API costs by 40% to 90%, and ensuring consistent responses for enterprise reliability.
The takeaway is clear: Caching doesn't just save money; it makes AI feel smarter.
Thank you for tuning in to "Analyze Happy: Crafting Your Data Estate"!
We hope you enjoyed today’s deep dive. If you found this episode helpful, don’t forget to subscribe for more insights on building modern data estates with Microsoft technologies like Fabric, Azure Databricks, and Power Platform.
Connect with Us:
- Have a question or topic you’d like us to cover? Reach out on linkedin.com/company/dataqubi or [email protected]
- Visit our website at www.dataqubi.com or episode resources, show notes, and additional tips on data governance, AI transformation, and best practices.
Stay Ahead:
Check out the Microsoft Learn portal for free training on Azure IoT, Fabric, and more, or explore the Azure Databricks community for the latest updates. Let’s keep crafting data solutions that fit your organization’s culture and tech landscape—happy analyzing until next time!
33 epizódok
Megosztás
