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Katja Sirazitdinova & Roland Harwood · Jun 26th, 2026
Most computer vision models work in controlled environments. Very few work reliably across different cameras, locations, and real-world conditions.
In this first Hafnia Tech Talks – a new series by Milestone Systems – we heard from Katja Sirazitdinova, Senior Developer Advocate at NVIDIA, on vision-language models and video analytics AI agents — and how they’re helping developers move from development to deployment of computer vision solutions in complex city environments.
In this session, we covered:
The gap between what AI can do in the lab and what cities need in the field
The challenges of scaling across real environments (different cameras, data quality, conditions) – and how developers are solving them
A look at NVIDIA's agentic blueprints and models, via Hafnia, and how developers can use them to build for city-scale complexity
Where the real value lies – moving beyond detection to decisions that improve operations, safety, mobility, and services.
This was an interactive session moderated by our Community Lead, Roland Harwood.
# Ai
# Artificial intelligence
# Cities
# Computer Vision
# Cosmos
# Cross-city
# Hafnia
# Nvidia
# Smart citiy
# Transport
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Transport Innovation Alliance Chair Rikesh Shah reflects on recurring themes from Leadership Forums in Barcelona and Detroit (Net Zero, Vision Zero, and data) arguing these are global challenges that cities cannot solve alone, requiring joint strategies
# Ai
# Cities
# Mobility
# Transport
# Transit
# Netzero
# Visionzero
# Alliance
From frontier model to trusted real world video intelligence: Milestone Hafnia and NVIDIA Cosmos 3. The Hafnia Data Library aggregates millions of hours of real-world video through a compliant framework.
# Cosmos
# Hafnia
# Nvidia
# Milestone
# Smart citiy
# Artificial intelligence
Cities like Boston, Prague and Sunderland are moving AI from isolated pilots into operational infrastructure, is a governance and trust challenge as much as a technical one.
# Ai
# Artificial intelligence
# Challenge
# Cities
# Compliance
# Critical infrastructure
# Data
# Responsible ai
# Responsible technology
# Smart citiy
# Trust

Søren Raagard Jensen · May 7th, 2026
Søren Raagard Jensen outlines the importance of employing ethically sourced data to train AI for surveillance applications, explores how errors can emerge from poor data practices and explains what the industry can do to ensure high-quality datasets.
# Artificial intelligence
# Analytics
# Cities
# Hafnia
# Surveillance
# Responsible ai
# Responsible technology
# Trust
Comment
# Smart citiy
# Artificial intelligence
# Cities
# Customerstory
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Generating sustainable business value with AI demands critical thinking about the disparate philosophies determining AI development, training, deployment, and use.
# Artificial intelligence
# Responsible ai
# Responsible technology
# Trust
# EthicalAI
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The future of smart city technology isn't being shaped in Silicon Valley — it's taking root in Dubuque, Iowa. With a population of about 60,000, this mid-sized city has become a live testbed for AI-driven traffic management thanks to a unique public-private collaboration led by Milestone Systems. Project Hafnia demonstrates how cities can transform urban mobility and safety through Responsible Technology—without costly infrastructure overhauls.
# Analytics
# Artificial intelligence
# License plate recognition
# Responsible technology
# Cities
# Transportation
# Customerstory
# Smart citiy
# Hafnia
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