Nature

Optimizing machine learning for network inference through comparative analysis of model performance in synthetic and real-world networks

In an era marked by exponential data growth and pervasive digital connectivity, understanding the intricate structure of networks has become a critical challenge across various domains. Whether ...
Nature

High computational density nanophotonic media for machine learning inference

Efficient machine learning inference is essential for the rapid adoption of artificial intelligence (AI) across various domains. On-chip optical computing has emerged as a transformative solution due ...
PC Magazine

AI training vs. inference

The simplest definition is that training is about learning something, and inference is applying what has been learned to make predictions, generate answers and create original content. However, ...
CMS Wire

Artificial General Intelligence: Jumping to the New Inference Market S-Curve

Historically, we have used the Turing test as the measurement to determine if a system has reached artificial general intelligence. Created by Alan Turing in 1950 and originally called the “Imitation ...