Chopping vegetables = Tokenization? Cooking = Training? AI is born in the kitchen

It turns out that the profound and inscrutable training of large models is actually quite similar to cooking in the kitchen! 👩‍🍳 Imagine AI as a chef who is learning the craft; its "path to divinity" is actually very down-to-earth: 🔪 Step 1: Advanced Knife Skills (Tokenization) AI cannot digest entire paragraphs; it must chop the recipe (massive text) into smaller pieces. Just like handling a dragon fruit, when encountering unfamiliar and obscure words, it must use advanced techniques like "byte pair encoding" to cut even finer, ensuring all ingredients can absorb the flavors! 🏷️ Step 2: Labeling (Embedding) The chopped ingredients need to be transformed into numbers through a "nutritional information table." In the eyes of AI, the numerical labels for apples and pears are very close, but they are worlds apart from cars. This step helps it understand the subtle relationships between ingredients. 🔥 Step 3: Guessing Game (Pre-training) The core training method is simple and straightforward: guess what the next ingredient is! Show it "add two spoonfuls of sugar" and let it guess that the next step is "stir." After trillions of repetitions and corrections (backpropagation), it finally learns the culinary rules of language. 🎓 Step 4: Specialized Training (Fine-tuning) A versatile chef who wants to become a master of French pastries must undergo specialized training for specific recipes. This is why ChatGPT can accurately answer your questions; it not only knows how to cook but has also learned the specialized "art of hospitality."