𝗛𝗼𝘄 𝗔𝗜 𝗠𝗼𝗱𝗲𝗹𝘀 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗪𝗼𝗿𝗸
You use AI to write emails or fix code. Most people call it an algorithm. They do not know how it works. The process is simple to understand even if the math is complex.
The core idea is prediction.
If you type "The cat sat on the," the model predicts the next word. It chooses "mat" because that word has a high probability. It repeats this loop word by word to build a full sentence. To predict words well, the model learns grammar, facts, and logic.
Here are the four steps:
Tokens Models do not read words. They read numbers. They break text into small pieces called tokens. Every token becomes a list of numbers. Underneath every conversation, math happens at a massive scale.
Training Training is how a model learns. You show it billions of pages from books and websites. The model predicts a token and checks the answer. If it is wrong, the system adjusts its internal settings. It does this trillions of times. No human writes rules for it. The model finds patterns on its own.
Attention This helps the model understand context. In the sentence "The trophy did not fit in the suitcase because it was too big," the word "it" refers to the trophy. Attention tells the model which previous words matter most. This allows the model to track meaning across long paragraphs.
Fine-tuning Raw models are just prediction engines. Fine-tuning teaches them to be assistants. Humans rate the answers. The model learns to provide helpful and safe responses based on these ratings.
What happens when you press send?
Your text turns into numbers. Those numbers move through layers of math. The model calculates the probability for the next token. It picks a token and repeats the process until the reply is finished. This happens in seconds.
AI is not magic. It is prediction at a massive scale. Knowing this makes you a better user of the tool.
Source: https://dev.to/rameshkumarramu/ai-models-how-do-they-actually-work-2kmm
Optional learning community: https://t.me/GyaanSetuAi