Future-proof AI systems

How reliable and aligned with their target audience AI systems are, says little about how well prepared for the future they are. We therefore need to look at the entire lifecycle of AI systems.

AI Systems Engineering & Lifecycle Management

TNO is looking for technical and organisational solutions to ensure that AI applications remain reliably deployable for longer.

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37 resultaten, getoond 1 t/m 5

System integration for robots in greenhouses

Informatietype:
Article

Good collaboration between humans and AI robots in greenhouses is essential. We are working on a semantic explanation and navigation system for improved communication.

AutoAdapt: Self-adaptive machine learning to propel us into the future

Informatietype:
Article

Self-adaptation in computing is a concept that might prove to be the missing link in making AI more transparent and accelerating innovation.

Developing moral models for AI systems

Informatietype:
Article

It is vital that values such as safety, trust and well-being are integrated in the decision-making process. How far are AI systems that we can trust them?

First overview of cyberattack techniques by AI against AI

Informatietype:
News
31 May 2023

All international trend reports view Artificial Intelligence as the most important disruptive technology of the coming years. Where a new technology develops, new vulnerabilities also arise. And AI is no exception.

‘Giant AI goes down the European road’

Informatietype:
Insight
31 March 2023

TNO supports the alarming call of the Future of Life Institute regarding AI. Regulation is urgent and cannot be left solely to the market. Read TNO's response.