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 ...

For years, enterprises tolerated opaque automation because outcomes were predictable. Early systems followed fixed rules, handled narrow tasks, and operated within clearly defined boundaries. If ...

Many organizations implementing AI agents tend to focus too narrowly on a single decision-making model, falling into the trap of assuming a one-size-fits-all decision-making framework, one that ...

AI labs like OpenAI claim that their so-called “reasoning” AI models, which can “think” through problems step by step, are more capable than their non-reasoning counterparts in specific domains, such ...

They could offer a more nuanced way to measure AI’s bias and its understanding of the world. New AI benchmarks could help developers reduce bias in AI models, potentially making them fairer and less ...