A visual representation of XAI. A clear white box model containing a digitized brain, with the letters X, A & I etched on the top of the box. According to the 2022 IBM Institute for Business Value ...
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Lowering barriers to explainable AI: Control technique for LLMs reduces resource demands by over 90%
Large language models (LLMs) such as GPT and Llama are driving exceptional innovations in AI, but research aimed at improving ...
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 ...
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 ...
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 ...
As the capabilities of artificial intelligence (AI) evolve, they push the boundaries of human understanding. Instead of transparent, explainable mechanisms, many AI applications are “black boxes,” ...
As artificial intelligence becomes an increasing part of our daily lives, from the image and facial recognition systems popping up in all manner of applications to machine learning-powered predictive ...
A team of researchers led by Integrated Biosciences and the Massachusetts Institute of Technology have used a new form of artificial intelligence to discover a class of antibiotics capable of killing ...
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 ...
National Institute of Standards and Technology scientists carefully crafted and proposed four fundamental tenets for determining precisely how explainable decisions made by artificial intelligence are ...
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