Traditionally, drug discovery relied heavily on trial and error, with long timelines and high costs. The introduction of ...

Modern behavioral data science approaches treat every user interaction as a signal. Micro-interactions like hover time, pause ...

In the race to develop AI that understands complex images like financial forecasts, medical diagrams and nutrition labels—essential for AI to operate independently in everyday settings—closed-source ...

As Data Science Central Community Editor Kurt Cagle writes, there is talk of a looming AI winter, harkening back to the period in the 1970s when funding for AI ventures dried up altogether.

Companies such as Scale AI, Turing and Toloka are hiring top experts in fields such as biology and finance to help AI groups ...

The spectrum of data science practitioners who have the experience and skills necessary to develop AI applications has been quite narrow. In 2022, amid a hiring crunch, we’ll see that aperture of ...

As AI continues to pervade across domains and workloads, and new frontiers emerge, the need for end-to-end data science and AI pipelines that work well with external workflows and components is ...

The relentless advance of data science and AI highlights the need for constant learning. According to a 2021 O’Reilly survey, 91% of the data and AI professionals pursued training for new skills ...

International Conference on Data Science, AI and Applications (ICDSAIA 2025) commenced at the EATL Innovation Hub, located in ...