Skyscanner 如何利用 Databricks 大规模运行实时 AI.pdf

1、Forward-looking StatementThis presentation has been prepared for informational purposes only.The information set forth herein does not purport to be complete or contain all relevant information.Statements contained herein are made as of the date of this presentation unless stated otherwise.This pres

2、entation and the accompanying oral commentary may contain forward-looking statements.In some cases,forward-looking statements can be identified by terms such as“may”,“will”,“should”,“expects”,“plans”,“anticipates”,“could”,“intends”,“projects”,“believes”,“estimates”,“predicts”,or“continue”,or the neg

3、ative of these words or other similar terms or expressions that concern Databricks expectations,strategy,plans,or intentions.Forward-looking statements are based on information available at the time those statements are made and are inherently subject to risks and uncertainties that could cause actu

4、al results to differ materially from those expressed in or suggested by the forward-looking statements.Forward-looking statements should not be read as a guarantee of future performance or outcomes.Except as required by law,Databricks does not undertake any obligation to publicly update or revise an

5、y forward-looking statement,whether as a result of new information,future developments or otherwise.2How Skyscanner Runs Real-Time AI at Scale with Databricks?Michael Ewins,Ahmed BilalThis session is all about one thing:Getting AI into productionMosaic Model Serving:Turn any model into a production-

6、grade API5Low Latency(ms-level)inferenceAutoscaling to 100K+QPSIntegrate natively with data storesAgendaHow Mosaic AI Model Serving powers real-time systems at scale Learn from Skyscanners real-world deployment storyHow were evolving it for compound and agentic workloads Live demo to show this in ac