# AI Models

Today, there’s no news agency that hasn’t been coveting the AI hype. This hype gained momentum when ChatGPT was launched, powered by the GPT-3.5 model.

To understand the excitement, it’s important to first know what an AI model is.

**So, what’s an AI model?**

Well, an AI model is basically a computer program that can look at data, find patterns, and make decisions on its own.&#x20;

It uses rules (algorithms) to understand information and perform tasks like understanding speech or recognizing pictures, similar to how humans think.

But these model needs to be “trained” - teaching an AI model how to do specific jobs by showing it lots of examples.

**But how do you create an AI model?**&#x20;

<figure><img src="https://3620906879-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Ft1TLw2CAY3Yjr54moPYE%2Fuploads%2FbAWZsPcyOJsqJztYBCBy%2Fimage.png?alt=media&#x26;token=d1b2e2bd-81d0-4633-ab6c-c0f7a81851e9" alt=""><figcaption><p>How to Create an AI Model</p></figcaption></figure>

Creating an AI model involves a few key steps.

* Define the specific problem to be addressed, such as predicting trends or classifying data.
* Collect and prepare relevant data, including cleaning to remove inaccuracies and inconsistencies.
* Select an appropriate model type based on the nature of the problem, such as supervised learning for labelled data or deep learning for handling complex patterns. &#x20;
* Train the model using a subset of the data, enabling it to identify patterns and make predictions.
* Evaluate the model’s performance on a separate dataset to measure its accuracy and effectiveness. Apply optimization and fine-tuning to enhance its performance further.
* Deploy the validated model in real-world settings, with continuous monitoring to ensure it remains effective and adapts to new data or evolving conditions as needed.
