Large language models (LLMs) such as GPT and Llama are driving exceptional innovations in AI, but research aimed at improving their explainability and reliability is constrained by massive resource ...

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...

The strong role of socioeconomic factors underscores the limits of purely spatial or technical solutions. While predictive models can identify where risk concentrates, addressing why it does so ...

Unlike traditional applications, agentic systems must monitor themselves in production, adapt to dynamic data and user ...

This article talks about how Large Language Models (LLMs) delve into their technical foundations, architectures, and uses in ...

In past roles, I’ve spent countless hours trying to understand why state-of-the-art models produced subpar outputs. The underlying issue here is that machine learning models don’t “think” like humans ...

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AI decisions are only defensible when the reasoning behind them is visible, traceable, and auditable. “Explainable AI” delivers that visibility, turning black-box outputs into documented logic that ...

As increasing use cases of AI in insurance add urgency to the need for explainability and transparency, experts are recommending "explainable AI" best practices to follow and key challenges to look ...