1、Edge AI Technology ReportGenerative AI at the Edge EditionA deep dive into the convergence of generative AI and edge computingIntroductionChapter I:Leveraging Edge Computing for Generative AIGenerative AI Across Edge DevicesAdvantages of Edge Computing in Real-world DeploymentsGenerative AI Integrat

2、ion with Edge Computing InfrastructureHow Particle is Transforming AI Deployment at the EdgeIndustry Perspectives on Edge DeploymentChapter II:Innovations and Advancements in Generative AI at the Edge Industry Trends,Market Analysis,and Innovation DriversHarnessing Generative AI for Edge Application

3、s with Edge ImpulseAI Workloads:From the Far Edge to the CloudKey Research Trends in Edge LLMsConclusionChapter III:Real-world Applications of Generative AI at the EdgeOverview of Current Generative AI Techniques and ImplementationsAccelerating Edge AI with Optimized Generative Models by SyntiantGen

4、erative AI Across Key IndustriesConclusionChapter IV:Challenges and Opportunities in Edge-based Generative AI Key Challenges to Deploying Generative AI at the EdgeStrategies and Solution GuidelinesFuture Opportunities and Growth AreasConclusion:Inspiring Action and InnovationAbout the ReportAbout th

5、e SponsorsEdge ImpulseParticleSyntiantAuthorsAbout WevolverAbout tinyML FoundationReferences and Additional Resources567891113161719222325262729313940414244464748485052545556575IntroductionWe once believed the cloud was the final frontier for artificial intelligence(AI),but the real magic happens mu

6、ch closer to homeat the edge,where devices can now think,generate,and respond in real time.The rapid evolution of AI,particularly generative AI,is fundamentally reshaping industries and challenging the existing computing infrastructure.Many AI models,especially resource-intensive ones like Large Lan