What Are Large Language Models?

Large Language Models (LLMs) are neural networks trained on massive text datasets that can understand and generate human-like text. They represent one of the most significant breakthroughs in artificial intelligence.

Key Characteristics

• Scale: Billions of parameters trained on terabytes of text data
• Generalization: Can perform tasks they weren't explicitly trained for (zero-shot learning)
• Emergent abilities: Capabilities that appear only at sufficient scale — reasoning, code generation, translation
• Context window: Can process thousands to millions of tokens in a single interaction

How LLMs Work (Simplified)

At their core, LLMs predict the next token (word piece) given a sequence of previous tokens. Through training on vast corpora, they learn:

1. Grammar and syntax of languages
2. Factual knowledge encoded in weights
3. Reasoning patterns and logical structures
4. Code patterns and mathematical operations

Why LLMs Matter

LLMs have fundamentally changed how we interact with computers. Instead of writing explicit rules, we can now describe what we want in natural language and have the model figure out the implementation. This has implications across every industry — from healthcare to finance, education to software development.

🌼 Daisy+ in Action: LLMs at the Core

Daisy+ integrates LLMs at its core — every digital employee (like DaisyBot) is powered by Claude, Anthropic's frontier LLM. Instead of building a chatbot on top of the ERP, Daisy+ treats LLMs as the intelligence layer for the entire platform. When a customer sends a message on livechat, when an email arrives at the catchall address, when a task needs to be triaged — it's an LLM making the decision, reading the context, and taking action.