Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...
In artificial intelligence research, scientists often describe parts of a model using simple algorithmic language. A small ...
Rob Futrick, Anaconda CTO, drives AI & data science innovation. 25+ years in tech, ex-Microsoft, passionate mentor for STEM diversity. As artificial intelligence (AI) models grow in complexity, ...
Progress in mechanistic interpretability could lead to major advances in making large AI models safe and bias-free. The Anthropic researchers, in other words, wanted to learn about the higher-order ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Two of the biggest questions associated with AI are “why does AI do what it does”? and “how does it do it?” Depending on the context in which the AI algorithm is used, those questions can be mere ...
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 ...
AI explainability remains an important preoccupation - enough so to earn the shiny acronym of XAI. There are notable developments in AI explainability and interpretability to assess. How much progress ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...
Ask a chatbot if it’s conscious, and it will likely say no—unless it’s Anthropic’s Claude 4. “I find myself genuinely uncertain about this,” it replied in a recent conversation. “When I process ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results