Tag: large language models
How Think-Tokens Change Generation: Reasoning Traces in Modern Large Language Models
Think-tokens are the hidden reasoning steps modern AI models generate before answering complex questions. They boost accuracy by 37% but add latency and verbosity. Here's how they work, why they matter, and where they're headed.
Read more
How to Use Large Language Models for Literature Review and Research Synthesis
Learn how large language models can cut literature review time by up to 92%, what tools to use, where they fall short, and how to combine AI with human judgment for better research outcomes.
Read more
Key Components of Large Language Models: Embeddings, Attention, and Feedforward Networks Explained
Understand the three core parts of large language models: embeddings that turn words into numbers, attention that connects them, and feedforward networks that turn connections into understanding. No jargon, just clarity.
Read more
Tool Use with Large Language Models: Function Calling and External APIs
Function calling lets large language models interact with real-time data and external tools using structured JSON requests. Learn how it works, how major models differ, where it shines, and what pitfalls to avoid.
Read more