CSEM advances gemstone analysis using artificial intelligence

Gübelin Gem Lab has teamed up with CSEM to develop a powerful machine learning platform that advances current methods used to determine gemstone authenticity and origin. A key aspect of the jewelry industry is the correct determining of a gemstone’s country of origin and authenticity, a process which relies heavily on expert human judgment and […]

Gübelin Gem Lab has teamed up with CSEM to develop a powerful machine learning platform that advances current methods used to determine gemstone authenticity and origin.

A key aspect of the jewelry industry is the correct determining of a gemstone’s country of origin and authenticity, a process which relies heavily on expert human judgment and analysis. As a pioneer in this field, Gübelin Gem Lab has teamed with CSEM to automate these processes using machine learning, a key area of artificial intelligence (AI).

The Gübelin Gem Lab ventured into the discipline of multivariate and automated data evaluation technologies some ten years ago, namely for the evaluation of large sets of chemical data, and to harmonize gemstone interpretations through all its entities. This new AI approach aims to increase the consistency and reliability of data interpretation, reduce potential human errors and save time.

Deep learning on a new level

By partnering up with Neuchâtel-based CSEM, Gübelin Gem Lab aims to bring gemmology to a new level by developing and transfering world-class data handling technologies based on artificial intelligence and deep learning using neural networks. This joint project named “Gemtelligence – Software development for the automated analysis of gemstones’ was submitted to Innosuisse and has recently been approved for funding.

CSEM’s expertise to handle complex and heterogeneous data is crucial for this project. “We are dealing with data with different degree of structuring, ranging from spectra, chemical element concentrations, to microscopy images, handwritten descriptions and subjective reflections by various experts,” says Philipp Schmid, Head of Industry 4.0 and Machine Learning at CSEM. “The goal is to create a kind of super-expert, working hand-in-hand with the human experts,” concludes Schmid.