AI puts skill development at risk for data scientists by minimizing hands-on practice and repetition.

Data science is everywhere, a driving force behind modern decisions. When a streaming service suggests a movie, a bank sends a warning about unusual activity on an account, or a weather app predicts ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Recent advancements in technology, data availability and changing consumer preferences have opened new opportunities for insurers to leverage data and insights. This allows them to enhance operations, ...

Large language models (LLMs) can generate impressive data visualizations from simple requests, yet their accuracy remains underexplored. Here we present a benchmark of 293 coding tasks derived from 39 ...

In social science, formal and quantitative models, ranging from ones that describe economic growth to collective action, are used to formulate mechanistic explanations of the observed phenomena, ...

In today’s customer-centric market, addressing customer churn is no less than a battle. It requires in-depth data-led customer insights for proactive identification of churn risks, driving timely ...

Time data is primal. It has always been thus for modern computing, mathematics and, now, artificial intelligence. From the founding grandparents of modern computing and AI – Ada Lovelace’s “analytical ...

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 ...