Built for breakthroughs

À mesure que l'IA générative gagne du terrain, il devient primordial de construire des solutions efficaces, tout en maitrisant leurs coûts. Cette session présente sept principes directeurs pour élaborer des applications d'IA générative efficaces et économiques. Ces principes peuvent aider les entreprises et les développeurs à exploiter le potentiel de l'IA générative tout en optimisant les ressources. Il est crucial d'établir des objectifs, de sélectionner des données de qualité, d'optimiser les architectures, de surveiller les performances, de respecter l'éthique et d’améliorer les performances par itérations successives. Grâce à ces principes, il est possible de développer des applications d'IA générative percutantes qui favorisent une innovation responsable. Enfin, vous allez découvrir le cas d’utilisation d’ASAPP, un leader des solutions pour centres de contact, et leur expérience avec l’IA générative qui a permis de réinventer leur logiciel grâce à Amazon Bedrock.

Mentre l'Intelligenza Artificiale generativa fa enormi passi avanti, diventa sempre più importante costruire soluzioni efficaci ed economicamente efficienti. Questa sessione illustra sette linee guida per sviluppare applicazioni di AI generativa che possono aiutare aziende e sviluppatori a sfruttarne al massimo il potenziale, ottimizzando le risorse. Stabilire obiettivi, curare dati di qualità, ottimizzare le architetture, monitorare le prestazioni, sostenere l'etica e iterare i miglioramenti sono aspetti cruciali. Con questi principi, le organizzazioni possono sviluppare applicazioni di IA generativa di grande impatto che guidano l'innovazione responsabile. Partecipa a questa sessione per scoprire come si possono utilizzare questi principi attraverso le nuove funzionalità di Amazon Bedrock.

A medida que la IA generativa gana terreno, el desarrollo de soluciones efectivas y costo eficientes es fundamental. Esta sesión describe siete principios para construir aplicaciones de IA generativa efectivas y costo eficientes. Estos principios pueden ayudar a las empresas y desarrolladores a aprovechar el potencial de la IA generativa mientras optimizan los recursos. Es crucial establecer objetivos, curar datos de calidad, optimizar arquitecturas, monitorizar el rendimiento, mantener la ética y realizar mejoras iterativas. Con estos principios, las organizaciones pueden desarrollar aplicaciones de IA generativa de gran impacto que impulsen la innovación responsable.

As gen AI gains traction, building effective and cost-efficient solutions is paramount. This session outlines seven guiding principles for building effective and cost-efficient gen AI applications. These principles can help businesses and developers harness gen AI’s potential while optimizing resources. Establishing objectives, curating quality data, optimizing architectures, monitoring performance, upholding ethics, and iterating improvements are crucial. With these principles, organizations can develop impactful gen AI applications that drive responsible innovation. Join this session to hear from ASAPP, a leading contact center solutions provider, as they discuss the principles they used to add gen AI–powered innovations to their software with Amazon Bedrock.

As interest in generative AI grows, building effective and cost-efficient solutions has become critical. This session highlights seven guiding principles for developing successful generative AI applications while managing costs. These principles help businesses and developers harness the potential of generative AI while optimizing resources. The principles include setting clear goals, organizing high-quality data, optimizing architectures, monitoring performance, adhering to ethical standards, and implementing process improvements. With these principles, organizations can build impactful generative AI applications that drive responsible innovation. Join this session to hear from Asapp, a leading contact center solutions provider, as they discuss the principles they've adopted to bring generative AI-powered innovation to their programs using Amazon Bedrock.

In this keynote, Jonathan Allen, Director of Enterprise Strategy at AWS, presents a comprehensive guide for leaders to harness the power of generative AI. Jonathan outlines a six-step framework for organizations to move from idea to value: Learn, Build, Establish Data Strategy, Lead People, Act Responsibly, and Get Started. He emphasizes the importance of scaling AI initiatives effectively, choosing the right models, and leveraging data as a differentiator. Jonathan also addresses the critical aspects of upskilling employees, fostering an AI-driven culture, and implementing responsible AI practices. The presentation provides practical advice for executives to navigate the challenges and opportunities presented by generative AI, urging leaders to embrace this transformative technology while managing associated risks

Experience the future of enterprise app development with App Studio—a generative AI-powered service that uses natural language to create enterprise-grade applications, empowers technical professionals like IT project managers, data engineers, and enterprise architects to build highly secure, scalable, and performant business applications solving critical problems in minutes, without professional developer skills.

In this session, gain the skills needed to deploy end-to-end generative AI applications using your most valuable data. While this session focuses on the Retrieval Augmented Generation (RAG) process, the concepts also apply to other methods of customizing generative AI applications. Discover best practice architectures using AWS database services like Amazon Aurora, Amazon OpenSearch Service, or Amazon MemoryDB along with data processing services like AWS Glue and streaming data services like Amazon Kinesis. Learn data lake, governance, and data quality concepts and how Amazon Bedrock Knowledge Bases, Amazon Bedrock Agents, and other features tie solution components together.

In the era of increasing cloud adoption, organizations face complex challenges in managing and optimizing their cloud spending. This session explores how Generative AI is revolutionizing cloud cost optimization, leveraging cutting-edge tools like Amazon Bedrock, Claude, and Amazon CodeWhisperer to transform traditional cost management approaches. Discover how AI-driven solutions can identify cost optimization opportunities that human analysts might miss, including: 1) Intelligent resource right-sizing recommendations using Amazon Bedrock's foundation models to analyze infrastructure patterns. 2) Predictive cost forecasting powered by Claude's advanced analytics capabilities. 3) Automated tagging and compliance monitoring using natural language processing through Amazon Bedrock. 4) Smart reservation and savings plan recommendations generated by AI models. 5) AI-powered waste detection enhanced by CodeWhisperer for automated remediation scripts. This session will also address common challenges and pitfalls in AI-driven cost optimization, providing practical solutions and implementation strategies. Learn how to balance automation with human oversight and maintain control while leveraging AI capabilities. Join us to explore how AI tools are transforming cloud cost optimization and learn practical strategies to implement these capabilities in your organization.