The focus of artificial-intelligence spending has gone from training models to using them. Here’s how to understand the ...

Graphical models provide a robust framework for representing the conditional independence structure between variables through networks, enabling nuanced insight into complex high-dimensional data.

Probabilistic graphical models are a powerful technique for handling uncertainty in machine learning. The course will cover how probability distributions can be represented in graphical models, how ...

We know that correlation does not imply causation, but careful analyses of correlations are often our only way to quantify cause and effect in domains ranging from healthcare to education. This ...

The AI industry stands at an inflection point. While the previous era pursued larger models—GPT-3's 175 billion parameters to PaLM's 540 billion—focus has shifted toward efficiency and economic ...

CISOs know precisely where their AI nightmare unfolds fastest. It's inference, the vulnerable stage where live models meet real-world data, leaving enterprises exposed to prompt injection, data leaks, ...

This post details the beginning of Bloomberg’s journey to build a machine learning inference platform. For those readers who are less familiar with the technical concepts involved in machine learning ...

Cerebras Systems Inc., an ambitious artificial intelligence computing startup and rival chipmaker to Nvidia Corp., said today that its cloud-based AI large language model inference service can run ...