Why 'Responsible AI' Starts With 'Boring' Data Engineering

Silent schema drift is a common source of failure. When fields change meaning without traceability, explanations become ...
InfoWorld

AI-augmented data quality engineering

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

Every AI Initiative Begins With Data

Without high-quality, well-governed data, every downstream AI initiative becomes fragile, expensive, inaccurate or downright ...

Fundamental emerges from stealth with first major foundation model trained for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...

Beyond the lakehouse: Fundamental's NEXUS bypasses manual ETL with a native foundation model for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a simple sequence of words, but as a complex web of non-linear relationships.

Is your AI model secretly poisoned? 3 warning signs

Is your AI model secretly poisoned? 3 warning signs ...

Mistral's New Ultra-Fast Translation Model Gives Big AI Labs a Run for Their Money

Too many GPUs makes you lazy,” says the French startup’s vice president of science operations, as the company carves out a ...
Communications of the ACMOpinion

When AI Tools Train on AI Output: Model Collapse in Daily Workflows

The degradation is subtle but cumulative. Tools that release frequent updates while training on datasets polluted with ...

OpenAI launches its first model partially built by itself: GPT-5.3-Codex

OpenAI launches GPT-5.3-Codex with faster coding, stronger reasoning, and higher benchmark accuracy—plus API access soon.