What Is a Large Language Model (LLM)?
LLMs are the AI technology behind ChatGPT, Claude, and tools like AskBiz. Here's how they work and why they matter for business.
Key Takeaways
- LLMs are AI models trained on vast amounts of text to understand and generate language.
- They can answer questions, summarise documents, generate reports, and reason about data.
- When connected to your business data, LLMs become powerful business intelligence tools.
What an LLM is
A large language model is an AI system trained on enormous quantities of text — books, websites, code, articles — to develop a deep understanding of language: how words relate, how sentences are structured, how questions are answered, and how reasoning works. This training enables them to generate coherent, contextual, and often accurate responses to questions asked in natural language.
How they work (simply)
LLMs predict the most likely next word in a sequence, given everything that came before. Trained on enough data, this next-word prediction produces responses that are coherent, factual, and contextually appropriate. The 'large' in LLM refers to both the quantity of training data (hundreds of billions of words) and the number of model parameters (the internal settings adjusted during training).
LLMs and business data
An LLM trained on general internet data can answer general questions. An LLM connected to your business data can answer questions about your business. 'What were our top-selling products last quarter?' 'Which customer segment has the highest churn risk?' 'How does our gross margin compare to our target?' AskBiz connects LLM capability to your business data to enable exactly these queries.
Limitations to understand
LLMs can generate plausible-sounding but incorrect information (hallucination). They don't automatically know your specific business context unless it's been connected. They don't replace domain expertise — they augment it. Used well, an LLM is an extraordinarily capable research assistant and analyst. Used uncritically, it can produce confidently wrong answers that mislead decisions.