Amazon Web Services (AWS) CEO Matt Garmin unveiled an ambitious vision for the future of cloud computing during his keynote at the company’s Re:Invent conference in Las Vegas. He projected a world where agentic artificial intelligence (AI) transforms customer interactions, claiming that the true business value of AI will be realized through widespread deployment of AI agents. This vision reflects AWS’s long-standing ethos, which has emphasized customer freedom to innovate since its inception two decades ago.
Garmin stated that AWS has been making significant advancements at “all levels of the technology stack” over the past three years, envisioning a future with “billions of agents” generating tangible business value. He was accompanied onstage by executives from key AWS customers, including Sony and Adobe.
John Kodera, Chief Digital Officer at Sony, highlighted the Japanese concept of “Kando,” which signifies deep emotional engagement and awe as a core business objective. He introduced Sony’s “data ocean,” developed using AWS’s Bedrock machine learning platform, which serves as the foundation for its generative AI applications. Kodera also mentioned that Sony utilizes AWS Nova Forge, a service enabling customers to build large-scale “frontier models” from the supplier’s cluster of foundation models, Nova. These frontier models are defined as AI systems that process a variety of data forms, including images, video, audio, and text.
Similarly, Shantanu Narayen, Chair and CEO of Adobe, discussed the intersection of creativity and AI, emphasizing how Adobe’s software—such as Acrobat, Firefly, and Studio—leverages AWS technologies like Amazon SageMaker and Bedrock to enhance creative workflows.
Garmin noted that AI startups are increasingly gravitating towards AWS, citing AudioShake—a company specializing in sound separation technology aimed at assisting individuals with hearing challenges—as an example of this trend.
AWS also announced several product advancements aimed at addressing technical debt among customers. Key among these is the introduction of agentic capabilities in AWS Transform, designed to facilitate rapid modernization of existing codes and applications. The service enables “full-stack Windows modernization,” allowing organizations to efficiently identify and modernize application and database dependencies through a centralized interface.
Major organizations such as Air Canada, Experian, QAD, Teamfront, Thomson Reuters, and Verisk are currently employing AWS Transform as part of their strategies to eliminate technical debt.
Another notable introduction is the AWS AI Factories, which aim to transform existing infrastructures into high-performance AI environments. These factories involve deploying dedicated AWS AI infrastructure within customers’ datacenters, combining Nvidia accelerated computing platforms with AWS Trainium chips and AWS AI services. This allows customers to utilize their existing datacenter space and network while AWS takes care of the deployment and management of the integrated infrastructure, meeting data sovereignty and regulatory requirements with expedited timelines.
According to Neil Ward Dutton, an IDC analyst focused on AI and automation, three announcements from the conference stood out. First was the AWS AI Factories, which are designed for the largest customers facing stringent security and sovereignty challenges. Second was Amazon Nova Forge, allowing clients to bring their own training data to enhance part-trained Nova models. Finally, he mentioned the introduction of policy specification and evaluation tools in Bedrock AgentCore, which constrict AI agents’ access to tools, resources, and data.
Ward Dutton cautioned that while the initial phase of enterprise generative AI is centered on remote accessibility, achieving substantial value will require a shift towards integrating AI technologies into essential business processes, workflows, and systems of engagement. He emphasized that for enterprises to derive true value at scale, they must adapt their security, privacy approaches, and regulatory responses to the evolving landscape of AI technology.
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