🔍 Key Developments in Data‑Centric AI

 Sweeping shift away from "sweatshop data"

A new essay featured in Time argues that as AI matures, demand is rising for higher-quality, expert-labeled datasets, reducing reliance on low-paid global labor. However, some researchers contend that content moderation and similar tasks still depend on traditional data workers

Enterprise shift: Fixing data is now the business imperative

According to the Financial Times, businesses are prioritizing data quality to support AI agents. While perfect data isn't practical, balanced curation is seen as essential before rolling out models

 Explosive AI infrastructure investment race

A Guardian report highlights massive capital deployment—Google plans to invest ~$85B, Amazon $100B, and Meta $64–72B in AI infrastructure during 2025—to support an era where high-quality data is as vital as compute power


New tooling to support high-quality data pipelines

Cleanlab recently raised $25 M to commercialize automated data cleaning and labeling tools for enterprise applications

Snorkel released platform improvements for building data-centric AI agents using expert labeling workflows tailored to agentic systems

Computer Science Engineering Awards


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