Sebastian Rhode
Using Containers to deploy AI Models across our microscopy platform
#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.
Matching moments
30:09 MIN
Deploying the machine learning model with Docker
Leverage Cloud Computing Benefits with Serverless Multi-Cloud ML
00:05 MIN
Understanding the scale and diversity of development at Zeiss
Empowering Thousands of Developers: Our Journey to an Internal Developer Platform
15:53 MIN
Reusing containerized tools across platforms and CI/CD pipelines
Reusing apps between teams and environments through Containers
04:50 MIN
Building the Zeiss medical ecosystem in the cloud
ZEISS & Microsoft - Building the Next Generation Medical Ecosystem in the Cloud
13:22 MIN
Using containerized environments for multiple AI agents
10 commandments for vibe coding
14:16 MIN
Building specialized platforms for GenAI, data, and web
Empowering Thousands of Developers: Our Journey to an Internal Developer Platform
23:35 MIN
Empowering engineers with accessible machine learning tools
Solving the puzzle: Leveraging machine learning for effective root cause analysis
15:54 MIN
Deploying enterprise AI applications with NVIDIA NIM
WWC24 - Ankit Patel - Unlocking the Future Breakthrough Application Performance and Capabilities with NVIDIA
Featured Partners
Related Videos
Empowering Thousands of Developers: Our Journey to an Internal Developer Platform
Bastian Heilemann & Bruno Margula
Compose the Future: Building Agentic Applications, Made Simple with Docker
Mark Cavage, Tushar Jain, Jim Clark & Yunong Xiao
Supercharge your cloud-native applications with Generative AI
Cedric Clyburn
Containers and Kubernetes made easy: Deep dive into Podman Desktop and new AI capabilities
Stevan Le Meur
ZEISS & Microsoft - Building the Next Generation Medical Ecosystem in the Cloud
Leo Lindhorst
Bootable AI Containers with Podman Desktop
Kevin Dubois & Cedric Clyburn
Bringing AI Everywhere
Stephan Gillich
Industrializing your Data Science capabilities
Dubravko Dolic & Hüdaverdi Cakir
From learning to earning
Jobs that call for the skills explored in this talk.

DevOps Engineer – Kubernetes & Cloud (m/w/d)
epostbox epb GmbH
Berlin, Germany
Intermediate
Senior
DevOps
Kubernetes
Cloud (AWS/Google/Azure)

Lead Fullstack Engineer AI
Hubert Burda Media
München, Germany
€80-95K
Intermediate
React
Python
Vue.js
Langchain
+1

Senior Systems/DevOps Developer (f/m/d)
Bonial International GmbH
Berlin, Germany
Senior
Python
Terraform
Kubernetes
Elasticsearch
Amazon Web Services (AWS)

Cloud Solution Architect - Container on Cloud
SVA System Vertrieb Alexander GmbH
Azure
Openshift
Kubernetes
Google Cloud Platform
Amazon Web Services (AWS)


DevOps AWS für AI Solutions
IQ Buddy GmbH
Remote
DevOps
Docker
Continuous Integration
Amazon Web Services (AWS)


Cloud & AI Platform Specialist - German Enterprise
Microsoft Deutschland GmbH
