This is a submission for DEV Computer Science Challenge v24.06.12: One Byte Explainer.

Explainer

Deep Learning is like teaching a kid to recognise cats. Start by showing them hundreds of cat pics. The kid eventually becomes so good at recognising cats they start finding cats in clouds, mud puddles, code comments, and even Stack Overflow posts.

Additional Context

We all know artificial intelligence (AI) has taken the world by storm, especially with generative AI. Deep Learning (DL) is one subset of Machine Learning (ML). This methods is based on multi-layered neural networks with representation learning. This process mimics the human brain and is best seen in childhood learning. The idea of teaching a child what something is so they eventually can recognise the object themselves. I decided to use cats, because the internet loves cats right?! ❤️

My cover heading is made using DreamShaper XL's on Night Cafe Studio. It's a Stable Diffusion model that's been fine tuned. Both this model and Dall-E are trained on millions or billions of text-image pairs, just like we'd teach a kid to recognise what a cat is 🐱.