Decentralized AI: The Future of Edge Computing - Seguridad Mania.com - España y América Latina

As breakthrough technologies like AI mature, they inevitably evolve from centralized to decentralized architectures. With global edge computing spending projected to reach $378 billion by 2028, organizations that continue relying solely on centralized AI risk falling behind in both efficiency and performance. The pervasive waste and expense of centralized generative AI models have underscored the urgent need for intelligence at the edge. While edge computing concepts have existed since the 1990s with content delivery networks, today's businesses face the complex challenge of transforming their architectures to process data closer to its source. This session explores how leading organizations are navigating this transition, reducing latency and costs while competing with decades of established centralized cloud infrastructure. Join Alan Morrison (Advanced Data Technologies Consultant and Writer) to discover how decentralized AI and edge computing are revolutionizing data processing across industries. Key Takeaways: - Understand why centralized AI approaches are becoming unsustainable and how edge computing addresses these limitations - Learn practical strategies for implementing edge intelligence from organizations already succeeding with this approach - Discover the economic benefits of processing data at the edge versus transmitting everything to centralized systems - Gain insights into market growth projections and how to position your infrastructure investments accordingly - Identify the architectural transformation challenges of edge computing and how to overcome them