Nanowire ‘brain’ network learns and remembers ‘on the fly’
Like a collection of ‘Pick Up Sticks’, this neural network has passed a critical step for developing machine intelligence. For the first time, a physical neural network has successfully been shown to learn and remember ‘on the fly’, in a way inspired by and similar to how the brain’s neurons work. The result opens a pathway for developing efficient and low-energy machine intelligence for more complex, real-world learning and memory tasks.
Many machine learning models have been developed, each with strengths and weaknesses. This catalog is not complete without neural network models. In OpenCV, you can use a neural network model developed using another framework. In this post, you will learn about the workflow of applying a neural network in OpenCV.…
A team at Los Alamos National Laboratory has developed a novel approach for comparing neural networks that looks within the "black box" of artificial intelligence to help researchers understand neural network behavior. Neural networks recognize patterns in datasets; they are used everywhere in society, in applications such as virtual assistants,…