How transformers work and why model depth matters for AI products (Hindi)

Understanding how transformers work is essential for product managers building with AI. This architecture powers nearly every tool you use. The transformer relies on attention, where every word reads the entire context simultaneously. Instead of reading sequentially, the model processes all words at once. This happens in rounds called layers. Shallow layers catch basic relationships, while deeper layers uncover complex meaning. Stacking layers creates the depth that makes larger models feel smarter. Because layer count is fixed, a model cannot dynamically think harder on a difficult sentence. It applies the same depth to every input, so it only works with explicit context. If a task requires deeper reading, you must select a larger model rather than just expanding your prompt. In this lesson: - How attention helps AI read prompts at once - Why stacking layers creates depth for reasoning - Why models cannot allocate more compute to hard sentences - When to choose a larger model over a longer prompt U2xAI Academy - AI skills for product managers. यह लेसन हिंदी में है. This lesson is narrated in Hindi.