Categories: AI/ML News

Using the brain as a model inspires a more robust AI

Most artificially intelligent systems are based on neural networks, algorithms inspired by biological neurons found in the brain. These networks can consist of multiple layers, with inputs coming in one side and outputs going out of the other. The outputs can be used to make automatic decisions, for example, in driverless cars.

Building a Softmax Classifier for Images in PyTorch

Last Updated on January 9, 2023 Softmax classifier is a type of classifier in supervised learning. It is an important building block in deep learning networks and the most popular choice among deep learning practitioners. Softmax classifier is suitable for multiclass classification, which outputs the probability for each of the…

January 16, 2023

In "AI/ML Research"

Self-Taught AI May Have a Lot in Common With the Human Brain

Neural networks can use self-supervised learning to figure out what matters. This process might be what helps humans do the same.

October 3, 2022

In "AI/ML News"

Brain-inspired AI architecture could computing faster and far less power-hungry

Spiking neural networks (SNNs) are artificial intelligence (AI) models inspired by how biological neurons communicate with each other. While biological neurons exchange information in the form of electrical impulses, SNNs rely on brief signals known as spikes.

June 24, 2026

In "AI/ML News"

AI Generated Robotic Content