What Is a Small Language Model (SLM)? How It Differs From an LLM
What is a small language model (SLM), how does it differ from a large model, and when should you use it? Get the concept, a comparison table, and a selection checklist.
Artificial Intelligence
AI tools, marketing with ChatGPT and Gemini, GEO and visibility in AI search.
118 posts
What Is the A2A Protocol? How AI Agents Talk to Each Other
The A2A (Agent2Agent) protocol lets AI agents from different providers discover each other and share tasks. Learn the core concepts, the MCP difference, security, and when you need it.
What Is an Open-Weight AI Model? How It Differs From Open Source
An open-weight model has downloadable weights, but its training data, code or license may not be fully open. We explain the difference from open source AI, license limits and risks.
What Is a Knowledge Graph? Entities and Relationships Explained
A knowledge graph stores entities and their relationships as nodes and edges. Learn how it works, how it differs from a vector database, and how it connects to knowledge panels.
What Is a Diffusion Model? How AI Generates Images
A diffusion model creates images by removing noise step by step. Learn how it works, how it differs from GANs, where it helps your business, and which copyright risks to watch.
What Is Model Quantization? Shrinking AI Models Explained
Quantization stores a model's weights at lower bit precision to save memory and often speed. We explain how it works, where it can hurt quality, and how to test it before you ship.
What Is Federated Learning? Training Models Without Sharing Data
Federated learning trains a shared model while raw data stays on each device or inside each organization. Only model updates travel. Here is how it works, where it helps and where it falls short.
What Is Inference in AI? How It Differs from Training
Inference is when a trained model answers a new input. We explain how it differs from training, how latency and throughput trade off, what drives cost, and where to run it.
What Is the Transformer Architecture? Attention Explained Simply
The transformer architecture is a neural network design that scores how every word relates to every other word at once. See self-attention, the RNN difference and the limits in plain language.
What Is Function Calling? How AI Models Use Tools Step by Step
Function calling lets an AI model decide which of your functions to call and with what arguments. Learn the flow, the risks, the differences from MCP and a practical checklist.