TL:DR
- AI evolution extends beyond generative AI to include agentic AI & physical AI technologies that complement each other to unlock new enterprise capabilities.
- Distributed AI infrastructure enables multicloud, multi-model agentic AI deployments while supporting edge-based physical AI applications like autonomous vehicles.
- Enterprises implementing distributed AI infrastructure at the edge position themselves to capitalize on transformative physical AI applications and economic impact.
Many people think of AI as a monolith. But what we call AI is actually a series of related technologies, each of which is evolving alongside the others. Generative AI has been in the public consciousness for several years now, but it’s merely one example of a transformative AI technology. Other emerging technologies will not replace generative AI; instead, they will build upon each other to unlock new capabilities.
Upcoming enterprise AI use cases will rely on a mix of different AI technologies. In a recent interview with Savannah Peterson from The Cube, Equinix Chief Digital and Innovation Officer Harmeen Mehta described how C-suite leadership can leverage AI in their innovation cycles, using technologies like predictive and prescriptive AI in addition to generative AI:
Agentic AI is another example of a technology that’s already having an impact, and that impact will only continue to grow. We can safely assume that agents will evolve quickly and take on increasingly complex tasks in the years to come. This will enable better performance and flexibility across AI use cases. Enterprises that implement distributed AI infrastructure to enable multicloud, multi-model agentic AI will be in the best position to capitalize on this trend.
Looking forward, physical AI—such as self-driving cars that help reduce traffic fatalities and robots that offload dangerous or repetitive tasks from human workers—has the potential to transform the economy in ways we’re only beginning to understand. Capitalizing on physical AI will require more AI infrastructure in more places. In particular, distributed AI inference infrastructure at the edge will become increasingly important.
To learn more about the different forms that AI will take next, watch the video clip below. In the clip, industry experts give their take on how AI will evolve in the future, with a focus on agentic and physical AI.
Also, read the solution brief to learn how Equinix Distributed AI™ is helping our customers adapt to a rapidly changing AI landscape.
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