Billions of parameters. Trillions of parameters. Everyone throws these numbers around like they mean something. Here’s what they actually are. 🎛️ A Parameter is Just a Dial Imagine a million tiny dials inside the model. During training, each dial gets turned slightly — up or down — until the model gets better at predicting the right answer. When training is done? The dials are frozen. That’s your model. 🚲 Think of it Like Learning to Ride a Bike ...
What is a Large Language Model? A Large Language Model (LLM) is a type of AI system trained on massive amounts of text data to understand and generate human language. Think of it as a very sophisticated autocomplete — but one that can write essays, answer questions, summarize documents, write code, and hold conversations. Examples you’ve probably already used: ChatGPT (OpenAI) Claude (Anthropic) Gemini (Google) LLaMA (Meta) These are all LLMs — each with different architectures, training data, and capabilities, but all built on the same core idea. ...
Not all AI is created equal. Some feel instant. Some feel like watching paint dry. Here’s what’s actually going on under the hood. ⏱️ TTFT — Time To First Token How fast does the first word appear? You: "Explain quantum computing" Bad TTFT: [........] ← 3 seconds of silence 😬 Good TTFT: [█ ] ← first word appears fast 😊 This is what makes a model feel responsive. Even if the full answer takes time, a fast TTFT makes it feel alive. ...