Agentic AI: The Future of Intelligent Systems15 Aug

Episode 97: The AI Data Center Problem — What Does Intelligence Take?

AI is becoming more intelligent, autonomous, and agentic — but that intelligence has a very physical footprint.

In this episode of Agentic AI — the future of intelligent systems, Navveen Balani explores the infrastructure behind the AI revolution: massive data centers, electricity demand, water consumption, cooling, land, and the impact on the communities that host them.

The question isn't whether we should build AI infrastructure. We need to. The question is whether we understand what these facilities will take from the places where they are built — before construction begins.

The episode introduces the idea of an AI Siting Ledger, built around eight shared questions every major AI infrastructure project should answer:

How much water? How much electricity? Can you turn down? Whose land? What's next door? What does the community get? Who checks? And what happens when it ends?

These questions could form a common contract between AI operators, governments, utilities, and communities — creating accountability before the shovel goes into the ground, rather than sustainability reporting after the facility is already operating.

Because the future of agentic AI won't be determined only by how intelligent our systems become.

It will also depend on whether the physical world is willing and able to host that intelligence.

And by 2030, perhaps the hardest resource for AI won't be chips, power, or water.

It may simply be a yes.

Denne episoden er hentet fra en åpen RSS-feed og er ikke publisert av Podme. Den kan derfor inneholde annonser.

Episoder(102)

Episode 100: The Next Era of AI — From Agents to Enterprise Intelligence

Episode 100 marks an important milestone for Agentic AI: The Future of Intelligent Systems.But rather than look back, this episode looks ahead.AI is moving beyond models, copilots and individual agent...

6 Sep 6min

Episode 99: Why Agentic AI Design Needs a Reset — From Repeated Reasoning to Executable Intelligence

Agentic AI is becoming more capable, but the way we design it may be fundamentally inefficient.Today, the default assumption is simple: if AI can reason about a task, let it reason about that task eve...

29 Aug 7min

Episode 98: From Tokens to Outcomes to Value — Rethinking Agentic AI Economics

The AI industry has become obsessed with tokens. How many tokens did we consume? Which model is cheaper? How much does a million tokens cost?But tokens measure what AI consumes. They don't measure wha...

22 Aug 13min

Episode 96: Why the Token Economy Has an Expiration Date

Artificial Intelligence is changing—but so is its economic model.Today, organizations measure AI in tokens. Every prompt has a cost, every response is metered, and AI success is often judged by infere...

9 Aug 12min

Episode 95: Google Gemini Enterprise Agent Platform and Lean Agentic AI— Building Lean Agentic AI That Cuts Cost, Energy & Carbon

Discover Google's latest Gemini Enterprise Agent Platform—and learn how to build AI agents that are efficient by design.In this episode, I explore Google's Gemini Enterprise Agent Platform, announced ...

28 Jul 25min

Episode 94: Agentic AI ROI — Why Most Organizations Aren't Seeing Business Value Yet

Organizations around the world are investing billions in Agentic AI. New foundation models are released almost every month, intelligent agents are becoming more capable, and the pace of innovation has...

19 Jul 8min

Episode 93: Physical AI — The Next Frontier for Agentic Systems

For decades, AI has lived behind screens—answering questions, generating content, and assisting human decision-making. But a new frontier is emerging.Physical AI is taking agentic intelligence beyond ...

28 Jun 7min