We still have no idea why an AI model picks one phrase over another, Anthropic Chief Executive Dario Amodei said in an April ...

We still have no idea why an AI model picks one phrase over another, Anthropic Chief Executive Dario Amodei said in an April ...

The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications behind its ...

The work draws inspiration from neuroscience techniques used to study biological brains and represents a significant advance in AI interpretability. This approach could allow researchers to ...

In this perspective, the AI Grid explore why the concept of “interpretability”—the ability to understand how AI systems think—is not just a technical challenge but a societal imperative.

Amodei acknowledges the challenge ahead. In “The Urgency of Interpretability,” the CEO says Anthropic has made early breakthroughs in tracing how models arrive at their answers — but ...

Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh ...

A team at Google DeepMind that studies something called mechanistic interpretability has been working on new ways to let us peer under the hood. At the end of July, it released Gemma Scope ...

Being able to understand a model’s inner workings in bottom-up, forensic detail is called “mechanistic interpretability”. But it is a daunting task for networks with billions of internal ...

Some scientists study language models by observing how they respond to different prompts — an approach akin to behavioral psychology. Researchers in the burgeoning subfield of mechanistic ...