“Trust comes from being able to check the answer and the path that produced it,” said Daniel Escott, Chief Executive Officer at Formic AI. “Boreal gives teams a clear link back to source documents and ...

Companies are generating an increasing volume of data at a CAGR of 61%. As a result, enterprises have been transitioning toward a data-driven decision model to build a competitive advantage. The ...

Large language models (LLMs) such as GPT and Llama are driving exceptional innovations in AI, but research aimed at improving ...

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 ...

Machine learning and artificial intelligence are helping automate an ever-increasing array of tasks, with ever-increasing accuracy. They are supported by the growing volume of data used to feed them, ...

Explainable AI (XAI) is a field of AI that focusses on developing techniques to make AI models more understandable to humans. Explainable AI (XAI) is a field of AI that focusses on developing ...

Explainable AI helps companies identify the factors and criteria algorithms use to reach decisions. (Photo by Jens Büttner/picture alliance via Getty Images) Artificial intelligence is biased. Human ...

Johanna Pingel is product marketing manager, MathWorks. AI is transforming engineering in nearly every industry and application area. With that, comes requirements for highly accurate AI models.

While machine learning and deep learning models often produce good classifications and predictions, they are almost never perfect. Models almost always have some percentage of false positive and false ...

The first consideration when discussing transparency in AI should be data, the fuel that powers the algorithms. Companies should disclose where and how they got the data they used to fuel their AI ...