MWC Barcelona 2026 | Jorge Cardenas, City of Brownsville, TX & Shahid Ahmed, NTT DATA

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Jorge Cardenas

CIO

City of Brownsville, TX

Shahid Ahmed

Global Head Edge Services

NTT

play_circle_outline Tiny Purpose-Built Models: Economical Edge AI for IoT Physics Without Giant GPUs or LLMs

play_circle_outline Sovereignty and latency trade-offs at disaggregated edge nodes

play_circle_outline Brownsville's AI Factory: Private 5G, 100 Miles of Fiber, Edge Sensors Power Citywide Public Safety

play_circle_outline Multi-tenant Hyperconverged Edge and Private AI for License Plate Readers, Wrong-Way Detection, Illegal Dumping, and Routing

play_circle_outline Funding and business case built on outcomes, cost savings, ARPA investment

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Jorge Cardenas, City of Brownsville, TX & Shahid Ahmed, NTT DATA

Jorge Cardenas

CIO City of Brownsville, TX

Shahid Ahmed

Global Head Edge Services NTT

During MWC Barcelona 2026, Jorge Cardenas, chief information officer of the City of Brownsville, Texas, and Shahid Ahmed, global head of edge services at NTT DATA, join theCUBE’s John Furrier and Dave Vellante to discuss the convergence of AI, private 5G and hyper-converged edge computing. Ahmed breaks down the shifting economics of the edge, explaining why the future of the IoT value chain relies on small, purpose-built "math models" rather than massive language models to achieve low-latency, cost-effective results. Cardenas shares the remarkable transformat... Read more

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How can AI be implemented cost‑effectively on IoT edge devices (given very low sensor/connection costs) without relying on expensive GPUs, and what kinds of models and compute approaches are appropriate? add

What are your views on the trade-offs between data sovereignty and latency for edge (robotics/physical) AI deployments? add

How did Brownsville go from being the least connected city to deploying fiber, private 5G, and an AI factory, and what impact has that infrastructure had on public safety, city operations, and addressing resource constraints? add

How did you plan the wireless/network architecture — including backhaul — to support citywide camera-based AI inference (e.g., license plate readers, wrong‑way driving, speeding, illegal dumping), and why was a private 5G network chosen over relying solely on fiber or public 5G? add

How was the business case built to secure funding for this edge/physical AI project—what did it include (cost savings, community impact, roadmap, etc.) and how were decisions made about data retention (what and how much to persist)? add

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Jorge Cardenas, City of Brownsville, TX & Shahid Ahmed, NTT DATA

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