First, institutions must ensure that synthetic datasets are continuously recalibrated against fresh, real-world evidence. The ...
Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...
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.
Translational modelling has emerged as a critical approach in environmental health and pharmacology, offering new pathways to predict human health risks ...
To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...
Not to get too lofty, but if you think about it, one could argue that our entire world is powered by data. Statistics here, IP addresses there. Ones, zeroes, and many other numbers coasting down the ...
New research from the Data Provenance Initiative has found a dramatic drop in content made available to the collections used to build artificial intelligence. By Kevin Roose Reporting from San ...
Artists and writers are up in arms about generative artificial-intelligence systems—understandably so. These machine-learning models are capable of pumping out only images and text because they’ve ...
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