Enterprises racing to deploy generative AI often focus on models. In practice, outcomes depend on how well organizations ...

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, ...

So-called “unlearning” techniques are used to make a generative AI model forget specific and undesirable info it picked up from training data, like sensitive private data or copyrighted material. But ...

Once, the world’s richest men competed over yachts, jets and private islands. Now, the size-measuring contest of choice is clusters. Just 18 months ago, OpenAI trained GPT-4, its then state-of-the-art ...

Machine learning models are becoming increasingly important in the prediction of economic crises. The models, however, use datasets comprising a large number of predictors (features) which impairs ...

Mozilla Data Collective is betting that the future of AI will require more than bigger models and larger datasets. It will ...

The world is changing rapidly, and if businesses want to keep up, there is no alternative but to change with it. Customer behavior, market conditions, and the technological landscape are in a constant ...