20:00 left to confirm your registration
Your reservation has expired. There may still be places available
AI Sweden invites you to the results event of the national project “Data-Driven Organizations – Best Practices for Operationalization of AI in Sweden.”
Over the past 20 months, leading Swedish organizations from industry, academia, and the public sector have joined forces to define how to move AI from experimentation to real-world implementation. Together, we have identified the organizational, technical, and governance models that enable responsible, scalable, and efficient AI operations.
At this event, we present the results — including practical frameworks, white papers, and demonstrations — that can help your organization shorten the time to operational AI significantly.
At this event, we present the results — including practical frameworks, white papers, and demonstrations — that can help your organization shorten the time to operational AI significantly.
Use Cases
The majority of the project’s efforts have been directed towards three very concrete use cases that the need owners represented in the project brought from their own organizations: How to use AI in a sustainable way, how to use shared infrastructure between different applications in a way that is regulatory compliant, and how to manage and administer a situation where you have thousand of models in production.
🗓️ Date and time: 25:th November, 13:00-17:00
📍 Where: Online, webinar
Agenda
13:00 Introduction
An introduction to the project. How can AI Sweden's partners benefit from the findings?
An introduction to the project. How can AI Sweden's partners benefit from the findings?
13:20 Use case 1: Sustainable AI Lifecycle
How can we make AI adoption economical and sustainable across its entire lifecycle, even with limited resources? Through a collaboration between Region Halland and Aixia, concrete tests were conducted, comparing hardware, models, and frameworks for both text and image analysis. What were the key findings?
How can we make AI adoption economical and sustainable across its entire lifecycle, even with limited resources? Through a collaboration between Region Halland and Aixia, concrete tests were conducted, comparing hardware, models, and frameworks for both text and image analysis. What were the key findings?
14:00 Use case 2: 1000 models in production
How do you scale ML operations from hundreds to thousands of models while maintaining efficiency and governance? Led by Volvo Parts and experts from Hopsworks and Red Hat, the project uncovered practical strategies to manage the life-cycle of countless models without proportional human resource growth. Discover strategies for scalable ML operations for success in complex business environments.
14:45 Short break (15 min)
Stretch your legs and fill up your coffee cup.
15:00 Use case 3: Soft infrastructure borders
Trafikverket needed to securely pool fragmented, specialized resources like GPUs while meeting MSB's stringent segregation requirements. This project developed a robust proposal, validated through multiple proofs-of-concept utilizing Stormgrid and Red Hat technologies. Discover a secure method to share IT resources that enhances capacity and modernizes practices for AI-based products.
Trafikverket needed to securely pool fragmented, specialized resources like GPUs while meeting MSB's stringent segregation requirements. This project developed a robust proposal, validated through multiple proofs-of-concept utilizing Stormgrid and Red Hat technologies. Discover a secure method to share IT resources that enhances capacity and modernizes practices for AI-based products.
15:40 Next-Generation MLOps?
AI Application Operations (AIAppOps) a new socio-technical framework developed at Linköping University that extends traditional MLOps to the full lifecycle of AI systems. See how it links data, model, and application processes with continuous monitoring to drive measurable business value.
16:10 How did we do on sustainability?
A critical review of the three presented use cases and papers from a sustainability perspective, performed by Santa Anna IT Research Institute. We will highlight the aspects connected to Corporate Sustainability Reporting Directive (CSRD) and outline how and where specific actions fit into an organisation's ongoing work with sustainability.
AI Application Operations (AIAppOps) a new socio-technical framework developed at Linköping University that extends traditional MLOps to the full lifecycle of AI systems. See how it links data, model, and application processes with continuous monitoring to drive measurable business value.
16:10 How did we do on sustainability?
A critical review of the three presented use cases and papers from a sustainability perspective, performed by Santa Anna IT Research Institute. We will highlight the aspects connected to Corporate Sustainability Reporting Directive (CSRD) and outline how and where specific actions fit into an organisation's ongoing work with sustainability.
16:35 White papers from the project
Rounding off the event, we will share a few shorter pitches for even more interesting papers produced by the project on Multi Agent System optimization, Building the AI-ready university and more.
Rounding off the event, we will share a few shorter pitches for even more interesting papers produced by the project on Multi Agent System optimization, Building the AI-ready university and more.
17:00 Session ends
Participants in the project
The organizations that participated in DDO were Aixia, Hewlett Packard Enterprise, Hopsworks, IBM, Linköping University, NetApp, Predli, Proact, RISE, RedHat, Region Halland, Sahlgrenska University Hospital, Statistics Sweden (Statistiska Centralbyrån), The Swedish Tax Agency (Skatteverket), Stormgrid, The Swedish Transport Administration (Trafikverket), Volvo Parts, Region Västra Götaland, Santa Anna, and AI Sweden.
