AICloudEdgeOpenLabRequirements

List of participants

Christoph Peylo - Global Head - Bosch Centre for AI	Bryan Che - Chief Strategy Officer Huawei
Loretta Tioiela - Strategy Advisor Huawei, Member EC European AI Alliance	Stefan Voget - Head of AI Infrastructure Laboratory - Continental
Florian Kisly - Technology Partner Management - Continental	Nathalie Hauk - Scientific expert - Fraunhofer-Institut FOKUS
Tom Ritter - Deputy Director - Fraunhofer-Institut FOKUS	Adam Gibson - CEO - Konduit
Filippo Formica - Direzione Tecnica, Innovazione e Ricerca - Engineering	Marco Alessi - Engineering R&D organizational unit - Engineering
Michele Gabusi - Data Science and Analytics Organizational Unit - Engineering	Carlos Cañado Moya - Head of Innovation & Software Development - Kairós Digital Solutions
Simon Butler - Associate Senior Lecturer in Informatics - University of Skövde	Alexander Karlsson - Senior Lecturer Computer Science - University of Skövde
Sebastian Scholze - Engineering manager - Institut für angewandte Systemtechnik Bremen GmbH	Andreas Riexinger - Automotive Expert - OpenADx
Njec Bat - Project Manager - XLab	Stratos Arampatzis - Director - Ortelio
Boris Baldassari - Director/founder - Castalia Solutions	Michael Plagge - Ecosystem Development Manager Eclipse Foundation - Eclipse Foundation
Gael Blondelle - VP Ecosystem Development Eclipse Foundation, MD EF Europe - Eclipse Foundation	Marc Vloemans - Head of AI Ecosystem Development - Eclipse Foundation

General goals

• Intention to collaborate in an ecosystem.
• The community effort will help towards coordination on topics eg trust, safety etc
• A central place to test, how to test, how to verify/qualify
• For now it's more informal initiative, but goal is to come up with production framework
• The OpenLab as a trust platform is an overall topic for everyone
• Work on horizontal applications for many sectors/verticals
• Share contributions

Potential Program themes

• Collaboration
  • Common ecosystem / MLOPS, sharing technology
  • Bring different initiative together, Federated Learning
  • IoT Ecosystems
  • Want to test with Hybrid cloud / Federated Services
  • Create distributions / synchronous releases
  • Streamlining processes for testing

• Trust
  • Trust in AI / IOT, in AI decisions
  • Need to see if we can have a collaboration or even better, implement the Digital Trust Forum, implement Digital Trust Forum in AI & IoT/in the OpenLab -> more trust in IoT devices, Trustworthy AI -> Trustworthy IoT
  • Work with partners to make the ecosystem more trustfully
  • Joint platform could be ideal for cooperation
  • Addition to trust discussion, implementation to "explain" AI, interest to share this in the initiative > share contributions, share test methods

• Ethics
  • Ethics of AI re hardware data collection

• Security & Safety & privacy
  • IT security and safety is still an issue
  • In automotive industry, definition of new safety strategy ongoing
  • Automotive Safety strategy and need to increase robustness
  • Privacy

• Integration
  • Continuous integration/DevOps
  • Good entry point for a couple of things, How to put together "everything"

• Projects
  • Brainstorming:
    • Infrastructure, sensor and wearables, health, Intelligence @ the Edge
    • Deploy & Embed AI in Enterprise architectures
    • Support for many languages
    • Project to manage AI APIs (competing with Acumos)
    • Integrate AI with workflows : Combining rules engine with machine learning. Falls back on human interaction when AI fails
    • Cloud for I4.0
    • Hybrid datastores
    • Project: IOT Testware (Eclipse project)
    • Application of research results
    • Develop test suits/test cases
    • Use Case : Deep Encode -> requires lots of compute power to adapt encoding on the fly thanks to AI
    • Toolchain for autonomous driving to test first solutions

• Technologies to be developed
  • Re limitation of cloud platform: can't use custom libraries
  • Requirements for applications, language support, support for continuous deployment
  • Embedded hardware requirements, DevOps, test methods
  • Rules engines with ML

• Data
  • Test data collection
  • Calibrated data sets needed/data reliability needed

• Other
  • Community efforts -> Frameworks that can be used for business
  • Verticals’ uses cases (Health/Hospital data-AI apps, project re Wearables/ with CEA)

Potential offers to bring to the OpenLab

• Capacity
  • Castalia; testing/reproducibility area of contribution
  • Huawei; Infrastucture, servers, open source cloud software, open source software in AI/ML, edge

• Data
  • Non mentioned

• Other resources (eg use cases)
  • Various attendees can bring use cases

• Miscellaneous items discussed
  • Interest in MLOPS platform
  • Custom libraries / OSS libraries -> Need to have continuous test / deployment
  • https://smartclide.eu/ (Note, EF; OpenLab LoS signed with them)
  • https://www.typhon-project.org/
  • Main constraints: missing of data availability
  • Develop cloud AI service for robots - https://noos.cloud from Ortelio is such a platform
  • Model uncertainty with "black box" methods (AI) and probabilistic methods
  • Combine Neural Network with statistical approaches

Next Steps/Action points

• Distribute meeting minutes via email w/ link to wiki
• Setup follow-up meeting to discuss the next steps
• Identify additional stakeholders for more detailed talks