降低人工智能安全风险的最佳实践.pdf

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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.2Best Practices to mitigate AI Security RisksData+AI Summit 2025Arun PamulapatiSamrat Ray2025 Databricks Inc.All rights reserved90%of enterprises notconfident goingto productionChallenge:Building and

6、deploying production-quality Gen AI solutions2025 Databricks Inc.All rights reservedTrain and deploy LLMs are cost effective at scaleCost-effective to build and deploy your own LLMsStandardized operations to scale to production across use casesGovernance and monitoring built-inMove GenAI models into