AI Model Terms You Actually Need to Understand

If you’ve ever tried to self-host a model and been hit with “CUDA out of memory” or seen someone mention INT4 quantization without understanding what was sacrificed, this is the breakdown you were missing. Every term maps back to one question: can I actually run this thing on my hardware? Here’s the answer — visualized. Parameters — The Size Question Parameters are the core weights of a model. The “8B” in Llama-3 8B means approximately 8 billion trainable numbers — each storing learned knowledge from training. But parameter count alone doesn’t tell you what it takes to run. You also need to know the precision those parameters are stored at. ...

August 28, 2026 · 3 min · 559 words · Sanket

Model Parameters: The Billion Dials Inside AI

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 ...

July 5, 2026 · 1 min · 206 words · Sanket

AI Series Part 1: What is a Large Language Model (LLM)?

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. ...

July 5, 2026 · 4 min · 686 words · Sanket

LLM Performance Primer: What Actually Makes AI Fast

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. ...

July 5, 2026 · 2 min · 250 words · Sanket