5 min read
UK Quantum Computing: Leading the Revolution
Of all the technologies being explored today, Quantum technologies are some of the most exciting and potentially most revolutionary, and the UK is at...
AI GLOSSARY
Interpretability
Interpretability refers to the ability to understand and explain how an AI or machine learning model makes its decisions. By providing insights into the relationship between inputs and outputs, an interpretable model openly shows its internal workings and provides information that makes it easier for users to trust, verify, and act on the model’s predictions. Interpretability is especially important in high-stakes applications where transparency is required to ensure accountability and fairness.
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4 min read
Industrial AI in 2026: Turning Uncertainty into Opportunity
Alistair Garfoot:
With pilot project failure rates as high as 80%, industries like manufacturing, utilities, and logistics have struggled to capitalise on AI’s...
4 min read
Digital Custodianship: The Future of Civil Infrastructure
Tom Bartley:
Our civil infrastructure is entering an accelerated phase of deterioration, and numerous challenges are hindering effective infrastructure...
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News, announcements, and blogs about AI in high-stakes applications.