Poor data governance can lead to a myriad of issues that include data interpretation inconsistencies, security ...

Seabed-origin oil spills pose distinct challenges in marine pollution management due to their complex transport dynamics and ...

In Part 1, we explored the challenges of implementing machine learning and real-time analytics in semiconductor ...

A novel approach from the Allen Institute for AI enables data to be removed from an artificial intelligence model even after ...

Snowflake Inc. (NYSE: SNOW) is experiencing strong growth due to financial success, product innovations, and strategic ...

Teradata remains a deep value play after disappointing earnings, but recent cash flow strength and favorable valuation ...

With GenAI and agentic AI projects increasingly moving from proof of concept to enterprise deployment, the business case for ...

Linear power flow model is advantageous for the fast operational analysis and the efficient optimization of the power systems. In this letter, we propose a hybrid physical model-driven and data-driven ...

The linearized power flow (PF) model is mainly used to make the optimal power flow (OPF) problem convex. However, existing data-driven linear PF models are not applicable for OPF calculation since the ...

Algorithms are not innocent codes based on machine learning and artificial intelligence, but ideological devices that shape ...

Cloudflare's evolution into a 'connectivity cloud' creates a unique, programmable global edge network, driving durable growth ...

Veeam Data Cloud for Salesforce isn't a bolt-on or an afterthought. It's engineered specifically to meet the challenges of ...