[00:03] a transformer model starts working behind the scenes in just a fraction of a second. Unlike older AI systems that read one word at a time, a transformer looks at the entire sentence together to understand the complete context. Its
[00:17] attention, which helps the model decide which words are most important when predicting the next word. Each word is first converted into numbers called embeddings, allowing the computer to understand relationships between
[00:31] embeddings pass through multiple transformer layers where the model repeatedly compares words, finds patterns, and builds a deeper understanding of the sentence. Using everything it has learned during
[00:44] training, the model predicts the single most likely next word. It repeats this prediction thousands of times every second until the complete response is generated. This ability to understand context and generate text one word at a
[00:59] time is what makes modern AI models like chat GPT feel surprisingly intelligent. Subscribe to this channel for more such information.