Beyond RGB: The Rise of Hyperspectral Rendering and Synthetic Data
Hyperspectral and multispectral imaging expose what RGB cannot: the continuous variation of light across wavelengths.
With What Accuracy Levels Can We Get Away in Computer Vision?
There’s no magic number. No single threshold that separates “good” from “bad.” 80%, 90%, 99% — these values mean nothing until you define the context: dataset complexity, operational risk, and task type.
7 pillars of trust: how to build AI you can truly trust?
Check out the major criteria every trustworthy AI system should meet, and why they matter for building reliable and responsible models.
Is Your Synthetic Data Trustworthy? Key Metrics and Tests
Learn how to assess synthetic-data quality with essential metrics, stress tests and validation tools, and discover how to build trusted datasets for real-world AI deployment.
Synthetic Data and GDPR
Learn how artificial data can help protect privacy in the age of AI.
