Imagine trying to teach a computer to recognize a cat in a picture. You could try to program specific rules – it has whiskers, pointy ears, a tail, etc. But what about a cat curled up in a ball? Or a blurry photo? Rule-based systems struggle with such variations. Artificial Neural Networks (ANNs) offer a Read More …
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GAN – Generative Adversarial Network
Imagine you have two artists: a forger and an art critic. The forger tries to create fake paintings that look just like the real ones, while the critic tries to distinguish the fakes from the authentic pieces. As they both get better at their jobs, the forger becomes more skilled at creating convincing fakes, and Read More …
RAG: Giving AI a Better Memory
Imagine you’re trying to answer a tough question, but your brain doesn’t have the specific information. What do you do? You probably look it up – maybe on the internet or in a book. Retrieval-Augmented Generation, or RAG, is a way to give AI models a similar ability. Think of a powerful AI language model as Read More …