How natural language processing and AI can help policymakers address global food insecurity

NLP offers powerful opportunities to support the UN Sustainable Development Goals (SDGs)—including SDG2 (Zero Hunger). In the ...

What Data Leaders Must Fix Before AI Can Scale In 2026

In 2026, data leaders must focus on enhancing data foundations rather than feature expansion. That means prioritizing data ...

The 'last-mile' data problem is stalling enterprise agentic AI — 'golden pipelines' aim to fix it

Empromptu's "golden pipeline" approach tackles the last-mile data problem in agentic AI by integrating normalization directly into the application workflow — replacing weeks of manual data prep with ...

Data Processing: The Achilles Heel Of AI

As you explore how to create new opportunities with AI, it’s crucial to first take a close look at your data architecture.
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Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

Mastering generative engine optimization in 2026: Full guide

That’s the job of generative engine optimization (GEO) — and in 2026, it’s no longer optional. This guide shows you how to build, execute, and measure a GEO strategy that actually works. What is GEO — ...