@datasciencefoundry: How does an LLM actually turn your prompt into a response? 🧠 Here's the big picture: 1️⃣ Your text is broken into tokens and converted into vectors that the model can process. 2️⃣ These vectors pass through many layers, where two key components repeatedly transform them: attention and feed-forward layers. 3️⃣ Attention lets the token representations interact with each other and incorporate information from the surrounding context. 4️⃣ The feed-forward layer then transforms each token representation independently. 5️⃣ After passing through all the layers, the model produces probabilities for what token should come next. 6️⃣ It selects a token, adds it to the sequence, and repeats the process until the response is complete. The key idea: An LLM doesn't generate an entire response at once. It repeatedly predicts the next token based on everything that came before it. #LLMs #GenerativeAI #Transformers #ArtificialIntelligence #MachineLearning
