How are AI models trained?

25th June 2025

They’ve become a key element of our lives, particularly at work, but how exactly does an AI model know what answers to give – and why should you trust them?

AI is everywhere now, exploding in popularity in the past few years. Able to help workers to accomplish remedial tasks much quicker, but also with the potential to help compute on a much larger scale, AI is where the future of technology is heading.

But how does AI get to be AI? The answer is it is trained, developed to give the most useful and accurate answers possible. We explain exactly how that process works, so you understand the effort that goes into creating and refining the AI programs that you use:

AI models learn from data, so the first step is to collect data that it can use. For a typical AI this could include books, websites, articles, code repositories, or even some social media. If an AI is designed for a particular task, it will be trained on data relevant to it, but if it is a general assistant, it will be trained on a little of everything.

The data must then be broken down into smaller units so that it can be processed, removing harmful, poor quality or irrelevant content, and standardising the text so it is as simple as possible for the AI to absorb.

Next is a process called model architecture design: if data is the “what” of AI, this is the “how,” as this architecture determines how information is processed. Most AIs use transformers; powerful neural networks designed to handle data sequences.

The key components of this architecture include attention mechanisms, that help the model focus on relevant data, layers, that are stacked to increase learning capacity and parameters, that the model adjusts during training.

Pretraining comes after that, which is the core learning phases for the AI. The model is asked to predict the next word in a sentence. It is then measured as to how far off it was and the model then adjusts its parameters accordingly to get a more accurate result in future.

Following from that is a lot of fine-tuning and testing to ensure the AI is giving accurate and unbiased results to a high level of accuracy. Humans rank model outputs which helps the model to understand which answers are best.

Finally, the AI is deployed, though constantly tweaked and improved. We hope you found this explanation of how AI is trained useful: if you have any more questions, please contact Interfuture Systems.