LLMs Explained: How They Process Data and Differ from AI Agents

This article explains the fundamentals of Large Language Models (LLMs), defining them as models trained to process sequences of tokens and generate responses. It details the training process, including pre-training and fine-tuning, and highlights that LLMs can answer questions, summarize, translate, and generate code based on learned patterns. However, LLMs cannot independently search the internet, edit files, or provide real-time data post-training. The piece differentiates LLMs from AI agents, explaining that agents combine LLMs with workflows and tools to perform tasks and maintain conversational context, unlike LLMs which solely process given input. AI

IMPACT Clarifies the core functionality and limitations of LLMs, distinguishing them from more capable AI agents.

RANK_REASON The item is an explanatory article about LLMs and AI agents, not a release or significant industry event.

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