Machine Learning Times
EXCLUSIVE HIGHLIGHTS
A Brief History of Why Machine Learning Projects Stall
  EDITOR’S NOTE: This is the preface to The...
Hybrid AI Emerges To Tame LLMs – And Not A Moment Too Soon
 Originally published in Forbes The great potential of LLMs is...
AGI Is Infeasible. Instead, Pursue Superhuman Adaptable Intelligence
  Originally published in Forbes On a recent episode of the...
Artifact-Driven Development: Making It Possible to Query Large Analytics and AI Projects
 A practical introduction to making complex project structure explicit...

Big data architecture

Tag management: Emerging areas for predictive analytics

 An exponential increase in data volume only supports an improvement in business practices when the right analytical processes are deployed. Today, even managing real-time data and having a firm grasp on current trends isn’t enough. Without predictive analytics, businesses are still stuck in reactive mode. Organizations don’t just need to know what users are doing