A few months ago, my company, CrowdFlower, ran a machine learning competition on Kaggle. It perfectly highlighted the biggest opportunity (and challenge) with machine learning: What do you do with an ...

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...

Datasets fuel AI models like gasoline (or electricity, as the case may be) fuels cars. Whether they're tasked with generating text, recognizing objects, or predicting a company's stock price, AI ...

Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use ...

Krishna, Satyapriya, Tessa Han, Alex Gu, Steven Wu, Shahin Jabbari, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective." Transactions on ...

Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of payments. We live in a world where machines can understand speech, recognize faces, and even generate ...