Bringing AI Everywhere.pdf

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1、Bringing AI Everywhere Anurag HandaGenerative AIMachine LearningDeep LearningChallengesAI EverywhereThe rapid growth of AIThe AI landscape2Rapidly growing number of methods,capabilities,data types and sizes,and infrastructure requirements to run AI ComplexityIncreasing costs due to increased compute

2、 demand as AI becomes more widely adopted and consumedCostNeed for speed along with many steps and skill sets required to get AI from proof of concepts to production in a scalable,sustainable processOperationalizingActivating sensitive or regulated data globally while remaining secure and compliantD

3、ata security and privacy Ensuring AI technology advances responsibly,ethically and equitably with a comprehensive approach that lowers risks,improves lives and optimizes benefitsHuman impactBringing AI Everywhere 3Accelerate the WorkloadStreamline the AI WorkflowSimplify AI Infrastructure CloudClien

4、t AI SpecificGeneral PurposeAI SoftwareScalable Systems&SolutionsFoundational Silicon&Software Training&Fine-TuningInference&Deployment SmallModelsUnlock the AI Continuum Large ModelsNovel Applications4Comprehensive Portfolio that meets the needs of EveryoneAI ContinuumModel CreationTraining/Fine-Tu

5、ningDeploymentEdge InferenceLocalized Inference(Client)Data PrepCLOUD&ENTERPRISECLIENT&WORKSTATIONEDGEAI ModelsDirectMLHugging FaceML applicationsAI Accelerator Roadmap Intel Gaudi AI acceleratorIntel Gaudi 2 AI acceleratorIntel Gaudi 3AI acceleratorcodenamed Intel Gaudi 3AI acceleratorIntel Gaudi 2

6、 AI acceleratorAI Accelerator Advancements Available Now7nm 2x AI Compute 4x AI Compute 2xNetwork Bandwidth1.5xMemory Bandwidth20245nm Architected for Gen AIPerformance&ProductivityIncreased memory for LLM efficiency and cost effectivenessMassive,flexible on-chip networkingOpen standard vs.proprieta