AI Explained: A Mental Model of Neural Networks
Blog post from Deepgram
Neural networks (NNs) have become a ubiquitous part of modern technology, underpinning systems like Google Translate and TikTok by functioning as the "brains" of machines, enabling artificial intelligence. The concept can be understood through a simplified model of a speech recognition application, where NNs process input waveforms and convert them into strings by breaking down the audio into chunks and using a layered structure to recognize increasingly complex audio features. Each layer in the NN builds upon the previous one, moving from frequency chunks to letter sounds, then to syllables, and finally to words, with the output layer providing a probability distribution for the possible words. While this model offers a mental image of NN functionality, the detailed mathematical operations and training processes involved in real NNs are more complex and will be explored in future discussions.
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