How AI Systems Represent Concepts #ai #ailearning

How Neural Networks Define Concepts

Why do neural networks need to be deep? In this video we explore how neural networks transform perceptions into concepts. This video unravels the mystery behind how machines interpret input data, such as images or sounds, and categorize them into recognizable concepts. From the basic structure of neurons and layers to the intricate play of weights and activations, get a comprehensive understanding of the learning process. Explore real-world applications like handwriting recognition and how layered processing aids in effective data categorization. Whether it's distinguishing between summer and winter days based on temperature and humidity or recognizing handwritten digits, the magic lies in the layered architecture of neural networks. This video elucidates how these artificial networks mimic the human brain's ability to interpret, recognize, and reason, marking a significant stride in AI research towards creating machines capable of reasoning. Why layers matter.

Full Video:

[ColinTimmins]

Thank you for the visuals and explanation. Will check out the video. =]

[smetljesm]

Does not compute.
Please try again 😅😅

Will watch full video 😊

[apophenic_]

This is amazing. Thank you for putting it together.