Ever wondered how AI tools like ChatGPT or Microsoft Copilot can answer questions like, “Where is the Statue of Liberty located?” It’s more than just searching for facts - it's a sophisticated process built on modern machine learning.
Here’s a concise walkthrough of what happens behind the scenes:𝟭. 𝗧𝗼𝗸𝗲𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻: 𝗕𝗿𝗲𝗮𝗸𝗶𝗻𝗴 𝗗𝗼𝘄𝗻 𝗬𝗼𝘂𝗿 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻
When you submit your question, the AI first divides your input into smaller pieces called tokens - typically words or word segments. So, “Where is the Statue of Liberty located?” becomes [“Where”, “is”, “the”, “Statue”, “of”, “Liberty”, “located”, “?”]. This helps the AI process and analyze each part of your question.
𝟮. 𝗘𝗺𝗯𝗲𝗱𝗱𝗶𝗻𝗴𝘀: 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗖𝗼𝗻𝘁𝗲𝘅𝘁
Each token is then turned into an embedding - a mathematical representation that captures its meaning and context. For example, the model recognizes that “Statue of Liberty” refers to the famous monument, not just three separate words.
𝟯. 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀 𝗮𝗻𝗱 𝗦𝗲𝗹𝗳-𝗔𝘁𝘁𝗲𝗻𝘁𝗶𝗼𝗻: 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗠𝗲𝗮𝗻𝗶𝗻𝗴
The embeddings are passed through multiple layers of a neural network (specifically, a transformer), which uses a mechanism called self-attention. This advanced process allows the AI to evaluate each token in the context of the entire question, ensuring that phrases and their meanings are kept intact (for instance, not confusing “Liberty” as just an abstract concept).
𝟰. 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗳𝗿𝗼𝗺 𝗩𝗮𝘀𝘁 𝗗𝗮𝘁𝗮
These AI models are trained on massive datasets comprising books, articles, and websites. Drawing on this prior knowledge, the AI predicts the most likely correct answer to your question.
𝟱. 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝘁𝗵𝗲 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲
Based on its deep understanding, the model generates an answer, one word (token) at a time. For your question, it outputs:
“The Statue of Liberty is located in New York City.”
This entire process - from breaking up your question to analyzing context, recalling knowledge, and wording the response - demonstrates how generative AI blends language understanding with statistical prediction. The result is a coherent, context-aware answer delivered in moments.