TeleGeography Explains the Internet

The TeleGeography Explains the Internet podcast welcomes Jezzibell Gilmore, General Manager, Service Provider at Kentik.

She discusses the profound impact of artificial intelligence on global network infrastructure, and how networks are evolving to handle new technological demands.

Key topics covered:

The Strain of AI workloads: The explosion of AI and GPU-heavy tasks is exposing the criticality of physical network infrastructure by demanding higher capacity, strict reliability, and ultra-low latency.

The rise of network intelligence: As global networks become increasingly complex, the industry is shifting from passive monitoring to "network intelligence," which uses AI to synthesize massive amounts of data and provide actionable insights for operators.

Shifting economic dynamics: The traditional expectation of constantly decreasing telecom prices is being upended, as the high demand and limited supply for AI-capable network capacity are actually driving prices up.

Physical limitations and the future: Overcoming unchangeable physical constraints—like the speed of light and the distance to new power generation sites—requires extreme network optimization, ultimately pointing toward a future goal of fully autonomous, self-healing networks.

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TeleGeography Resources: https://resources.telegeography.com/
Our Research: https://www2.telegeography.com/en/our-research

Host Greg Bryan welcomes Phill Lawson-Shanks, Chief Innovation Officer at Aligned Data Centers.

With several decades of experience in digital infrastructure, Phill has seen the industry evolve from mainframes and green screens to the massive hyperscale cloud platforms we rely on today.

In this episode, we explore:

The Shift in Data Center Geography: Why the "center of gravity" for networks is moving toward new power-rich zones and how the rise of AI is rewriting the rules of connectivity.

The Engineering Challenges of AI: From floor loading for 6,000-pound racks to the transition from air to liquid cooling, Phill explains the "fungible" design needed for modern AI factories.

The Infrastructure Bottleneck: Why AI is ultimately a network-dependent technology and how high-speed optical networking between buildings is pushing against the limits of physics.

Sustainability and Power: How the industry is chasing power availability and pioneering new ways to build modular, carbon-traceable infrastructure.

Podcast HQ: https://www2.telegeography.com/telegeography-explains-the-internet-podcast
TeleGeography Resources: https://resources.telegeography.com/
Our Research: https://www2.telegeography.com/en/our-research

This episode features Hunter Newby, a veteran of the telecom industry with experience spanning from LDDS WorldCom to building carrier hotels and neutral internet exchange points.

Newby discusses how AI inferencing is reshaping network infrastructure requirements and why geography still matters in the internet age.

Key topics covered:

Low-latency inferencing: Why AI applications require a fundamental shift from the old CDN model to distributed, proximity-based network architecture with deterministic routing in sub-millisecond "latency zones"

Internet exchange gaps: How many U.S. states lack even a single neutral internet exchange point, forcing local traffic to backhaul hundreds of miles and creating economic development barriers

Connected Nation Internet Exchange Points (CNIXP): Newby and Connected Nation are building purpose-built internet exchange points in underserved markets (125+ cities identified) to support enterprise needs and AI workloads, starting with aerospace companies like Airbus and Boeing.

Beyond the data center: Why the industry needs to shift focus from power-first mega data centers to network-first interconnection facilities that enable local traffic exchange and support emerging AI use cases

Premium routing opportunity: How carriers can move beyond commoditized transit pricing by offering guaranteed low-latency routing to specific zones—the "FedEx model" for data delivery

From this episode: Akamai Boosts Inference With ‘Thousands’ of Nvidia Blackwell GPUs

Podcast HQ: https://www2.telegeography.com/telegeography-explains-the-internet-podcast
TeleGeography Resources: https://resources.telegeography.com/
Our Research: https://www2.telegeography.com/en/our-research

What are the real bottlenecks in AI infrastructure development?

How is this infrastructure boom similar to the 90s internet boom? How do we overcome the pricing paradox in telecom transport where demand keeps rising and service prices keep falling?

Today on TeleGeography Explains the Internet, we welcome Luis Colasante, Head of Procurement Strategy for Energy & Infrastructure at Colt Technology Services.

Luis brings a perspective from the intersection of energy strategy, critical infrastructure, and capital markets. In this episode, we move beyond the "compute bubble" to discuss why physical infrastructure—from subsea cables to the power grid—has become the primary bottleneck for the AI revolution.

Luis explains:

The Energy-Connectivity Nexus: Why AI data centers require two to three times more power than traditional cloud facilities and how energy availability is now the ultimate gatekeeper for digital expansion.

Shifting Investment Cycles: A look at the parallels (and differences) between the late-90s telecom bubble and today’s hyperscaler-led boom.

Digital Sovereignty: Why governments are treating subsea cables as strategic national security assets, highlighted by the French government’s recent move with ASN.

The Death of the "Toll" Model: Why selling raw bandwidth has become a deflationary commodity business and how the industry is pivoting toward intelligent service layers and "Network as a Service" 2.0.

Podcast HQ: https://www2.telegeography.com/telegeography-explains-the-internet-podcast
TeleGeography Resources: https://resources.telegeography.com/
Our Research: https://www2.telegeography.com/en/our-research

Host Greg Bryan welcomes Jason Gintert back to the show. As the incoming President of the U.S. Networking User Association, Jason dives into the current state of AIOps in network management.

This includes:

Low Adoption and Key Challenges: Despite being a popular topic, AIOps adoption remains low due to concerns about trusting AI output (hallucinations) and the indeterminate nature of large language models.

Data Integration and Security: The importance of integrating private data using methods like the model context protocol to make AI answers more deterministic. For security, Jason strongly recommends starting with a read-only, zero-trust mindset when exposing data to AI tools.

Practical Use Cases: AI is most valuable for root cause analysis of common network problems (e.g., Wi-Fi authentication issues, circuit errors) and providing automated network summaries or predictive analysis.

The Human Element: AI is seen as a powerful tool to increase the productivity of network engineers by handling low-level tasks, but it will not replace humans. Engineers remain crucial for exercising judgment and taking responsibility for service-impacting changes.

Podcast HQ: https://www2.telegeography.com/telegeography-explains-the-internet-podcast
TeleGeography Resources: https://resources.telegeography.com/
Our Research: https://www2.telegeography.com/en/our-research