RAG can make your AI analytics way smarter — but only if your data’s clean, your prompts sharp and your setup solid.

While organizations may be ready to unlock the full potential of their data for analytics and AI, challenges such as data silos, inefficient workflows, slow analytics, governance risks, scalability ...

Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your ...

Many organizations are sitting on valuable proprietary data but lack a clear plan for commercializing it. As interest in ...

A new twist on a classic material could advance quantum computing and make modern data centers more energy efficient, ...

MetaGraph compresses vast data archives into a search engine for scientists, opening up new frontiers of biological discovery ...

Chicago-based Introl hit No. 14 on the Inc. 5000 this year, buoyed by an AI boom that some warn has started to look like a ...

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech ...

In this interview, Alf Franklin, discusses the firm’s core mission to help everyone transform data into actionable answers ...

Google said on Tuesday it would invest $15 billion over five years to set up an artificial intelligence data centre in India's southern state of Andhra Pradesh, its biggest ever investment in the ...

AI-generated data is known as synthetic data. Such data can be used for amazing purposes. I explore a study at Stanford ...