These are not “nice-to-haves”; they are prerequisites for distributed cognition, operating at machine speed. As Tatipamula and Cerf point out, the network can no longer simply host intelligence. It ...
This study found that certain characteristics in linked electronic health record data across episodes of care can help identify patients with Alzheimer disease and related dementias at high risk of 30 ...
Learn about model risk, its causes, management strategies, and real-world examples from financial industry pitfalls. Unlock ...
Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
Garbage in, garbage out. That is a motto insurers are focused on as AI adoption accelerates. No matter how sophisticated an ...
Organisations collect and store more data than ever, often with the belief that more data automatically leads to a ...
New Semantic Compiler modernizes BI, accelerates AI readiness, and eliminates metric sprawl across databases, analytics platforms, and AI agentsMOUNTAIN ...
The Power Grid Model DS project extends the capabilities of the power-grid-model calculation core with a modelling and simulation interface. This is aimed at building data science software ...
Microsoft is moving more of the data governance workload to users, but says that this will lead to greater accountability and transparency. Microsoft Fabric users will soon face more work to set up ...
A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback