Machine learning has revolutionized various fields, but it also raises concerns for privacy due to the risk of overfitting. Researchers are exploring techniques to…
Browsing: Parameters
AI models are becoming increasingly large, with large language models (LLMs) composed of over 100 billion parameters. However, there are drawbacks to this growth,…
AI systems are becoming increasingly prevalent in our lives, but they are fundamentally unexplainable and unpredictable. This is because many of their inner workings…
This article discusses the differences between Interpretable Artificial Intelligence (IAI) and Explainable Artificial Intelligence (XAI) models. IAI models are easily understood by humans by…
A new proof from Los Alamos National Laboratory scientists shows that a technique called overparametrization enables quantum machine learning algorithms to find the highest…
A new paper by a Los Alamos team has established a theoretical framework for predicting the implications of overparametrization in quantum machine learning models.…
A new paper by a Los Alamos team has established a theoretical framework for predicting the critical number of parameters needed for quantum machine…
Artificial Intelligence (AI) is not quite what science fiction has portrayed it to be. AI is based on machine learning, which means the program…
This script is designed to calculate the theoretical amount of synaptic operations in spiking neural networks, including accumulated (AC) and multiply-accumulate (MAC) operations. It…
The Board of Appeal of the European Patent Office recently considered an invention directed to a sparsely connected neural network, which the applicant tried…