Is it possible for an AI to be trained just on data generated by another AI? It might sound like a harebrained idea. But it’s one that’s been around for quite some time — and as new, real data is ...

Occasionally one may hear that a data model is “over-normalized,” but just what does that mean? Normalization is intended to analyze the functional dependencies across a set of data. The goal is to ...

Traditionally, AI progress was constrained by one thing above all else: access to data. Not enough volume. Not enough ...

Zehra Cataltepe is the CEO of TAZI.AI, an adaptive, explainable AI and GenAI platform for business users. She has 100+ AI papers & patents. In many industries, including banking, insurance and ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

AI promises a smarter, faster, more efficient future, but beneath that optimism lies a quiet problem that’s getting worse: the data itself. We talk a lot about algorithms, but not enough about the ...

AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology ...