artificial intelligence

New research led by the University of Glasgow’s School of Psychology and Neuroscience presents an approach to understand whether the human brain and deep neural networks recognize things in the same way.

Peter Bernard, CEO of Datagration, discusses how oil and gas industry predictive maintenance doesn’t just provide an economic value, it also boosts safety by anticipating unpredicted failures among aging infrastructure.

Geolog and Petro.ai announced a strategic partnership to deliver data science products and services to the global energy industry.

With so much volatility in the sector, acutely felt by many western consumers, how are intelligent work flows enabling the shift toward alternatives?

Incorporating domain knowledge into your architecture and your model can make it a lot easier to explain the results, both to yourself and to an outside viewer. Every bit of domain knowledge can serve as a stepping stone through the black box of a machine learning model.

The AIoT has the potential to transform industries and society, and it is already starting to have an impact. This article will explore the principles of AIoT, its benefits, and its current use.

Supervised learning has many commercial applications; however, such learning lacks the capability to generate new insights and knowledge. In contrast, unsupervised learning discovers the inherent structures in unlabeled data, thereby helping generate new insights and actionable knowledge from large volumes of data.

Researchers from Skoltech have trained a neural network to recognize rock samples in core box images efficiently. The process has sped up analysis by up to 20 times and made it possible to automate the description of rock samples.

The collaboration is planned to explore artificial intelligence in an effort to get more value from oil and gas operations and create a sustainable and carbon-efficient future for the energy industry.