AI without the jargon

What is an AI model?

An AI model is the part of an AI system that has learned patterns from data and can use those patterns to generate, classify, extract or interpret information.

Think of it like this

Application — what you interact with
Model — the intelligence doing the work
Infrastructure — where the model actually runs
Integration — how it connects to your business
ChatGPT, an AI model and an AI integration are not exactly the same thing — even though people often use the word AI for all three.

Why are there so many AI models?

Different models are built with different sizes, capabilities, costs and strengths.

General models

Designed to handle a broad range of language and reasoning tasks.

Specialised models

Designed or tuned for narrower types of work.

Open models

Models that can often be downloaded and operated in environments you control.

Bigger is not always better

The best model is the one that performs the job reliably at an acceptable cost and level of privacy.

Simple classification

May not need a huge model.

Complex reasoning

May benefit from a more capable model.

High-volume tasks

Speed and cost can matter as much as raw intelligence.

Start with the business problem.

Sometimes the answer is AI. Sometimes it is automation. Sometimes two existing systems simply need to communicate properly. And whenever business information is involved, privacy and data ownership should be part of the decision.

Common questions

Frequently asked questions

Is ChatGPT an AI model?

ChatGPT is a product that uses AI models. The application and the underlying model are related but not identical.

Can businesses choose different models?

Yes. Modern AI systems can often use different models for different tasks.

Can AI models run locally?

Some can.

Do I need to understand model specifications?

Usually not in depth. Businesses mainly need to understand capability, privacy, reliability and cost for the task involved.

Keep learning

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Your business first

You don't need to know which technology you need.

Tell us what is repetitive, slow or frustrating. The first job is understanding the problem. AI, automation and infrastructure come afterwards.

Tell us what's wasting your time