Displaying 7 resources
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IMPACT STORIES - from the TAILOR Network of Excellence Centres in AI

The TAILOR Impact Stories is a powerful demonstration of the collective achievements and spirit of the TAILOR network.

Category
Best practices in deployment
Target audience
ADR Experts and Associations, Individual Citizens/Members of the Society, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks

STRATEGIC RESEARCH & INNOVATION ROADMAP OF TRUSTWORTHY AI

This document is the first version of the Strategic Research and Innovation Roadmap of the TAILOR project, focussed on Trustworthy Artificial Intelligence through Learning, Optimization and Reasoning.

Category
Cooperation with partners, Multistakeholder dialogue, Support guidance in the responsible implementation of ADR, Understanding of the fundamental rights and values, Best practices in deployment, Legal framework and regulation, Recommendations towards policy changes, Standards, Trustworthiness
Target audience
ADR Experts and Associations, Policy Makers, Private Sector, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks
Professional development resources for teachers/educators Professional development resources for teachers/educators

Handbook of Trustworthy AI

The main goal of the Handbook of Trustworthy AI (HTAI) is to provide to non-experts, researchers and students, an overview of the problem related to the developing of ethical and trustworthy AI systems.

Category
Multistakeholder dialogue, Support guidance in the responsible implementation of ADR, Understanding of the fundamental rights and values, Best practices in deployment, Legal framework and regulation, Trustworthiness
Target audience
ADR Experts and Associations, Policy Makers, Private Sector, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks

Comparing implementations of a Small CNN on Commodity Hardware

Presentation detailing our benchmarking of several low cost boards for AI inference on the Edge.
The NN is a small NN that performs 1 channel images classification over 58 categories targeting an industrial application.

Category
Edge-based AI
Target audience
ADR Experts and Associations, Individual Citizens/Members of the Society, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks

Edge AI trends and engineering principles applied to micro, meta, and end-to-end AI system verification, validation, and testing

Edge AI, which refers to the deployment of edge computing and artificial intelligence (AI) models and algorithms on edge devices like IoT devices and embedded systems, is rapidly evolving with several emerging trends and engineering principles app

Category
Edge-based AI
Target audience
Individual Citizens/Members of the Society, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e

EdgeAI

Develop new electronic components and systems, processing architectures, connectivity, software, algorithms, and middleware through the combination of microelectronics, AI, embedded systems, and edge computing.

Category
Edge-based AI
Target audience
Individual Citizens/Members of the Society, Policy Makers, Private Sector, professionals, Public Sector, Researchers and Academic
Source
Adra-e