Using Containers to deploy AI Models across our microscopy platform
How do you guarantee identical AI results from the cloud to a local desktop? Learn how containers solved this critical reproducibility challenge for scientific imaging.
#1about 4 minutes
AI-powered computer vision workflows in modern microscopy
Zeiss uses AI for various microscopy tasks like classification and instance segmentation to analyze biological samples.
#2about 2 minutes
The challenge of analyzing terabyte-scale microscopy data
Automated microscopy workflows can generate terabytes of data from a single experiment, requiring powerful AI for quantitative analysis like cell counting.
#3about 3 minutes
Key requirements for reproducible AI model deployment
Users need robust and reproducible AI models that deliver consistent results across different platforms without requiring IT expertise.
#4about 3 minutes
Moving from model artifacts to containerized deployments
The previous method of deploying only model files created synchronization issues, leading to the adoption of containers to package models with all their dependencies.
#5about 3 minutes
Why containers are the ideal solution for AI deployment
Containers solve key challenges by enabling GPU access on Windows via WSL2, decoupling dependencies for different AI tasks, and simplifying client software maintenance.
#6about 3 minutes
The new workflow for training and deploying models
The new process involves training models in the cloud, which produces a container as the final artifact that is then downloaded and run by the client software.
#7about 2 minutes
Demonstrating the business value of containerization
This container-based approach allows users to access new AI algorithms faster without client updates, convincing stakeholders and enabling independent development cycles.
#8about 4 minutes
Key learnings for adopting container technology
Adopting containers is successful when it solves a real business problem, starts with smaller prototype projects to de-risk, and leverages mature, standardized technology.
Related jobs
Jobs that call for the skills explored in this talk.
Stephan Gillich - Bringing AI EverywhereIn the ever-evolving world of technology, AI continues to be the frontier for innovation and transformation. Stephan Gillich, from the AI Center of Excellence at Intel, dove into the subject in a recent session titled "Bringing AI Everywhere," sheddi...
Building AI Solutions with Rust and DockerIn recent years, artificial intelligence has surged in popularity in the world of development. While Python remains a popular choice in the realm of AI, Rust - often known as Rust Lang - is quickly emerging as a formidable alternative.Rust programmin...
Chris Heilmann
With AIs wide open - WeAreDevelopers at All Things Open 2025Last week our VP of Developer Relations, Chris Heilmann, flew to Raleigh, North Carolina to present at All Things Open . An excellent event he had spoken at a few times in the past and this being the “Lucky 13” edition, he didn’t hesitate to come and...
From learning to earning
Jobs that call for the skills explored in this talk.