Model Training
Fine-Tuning
Taking a pre-trained AI model and teaching it your specific domain knowledge, like hiring a generalist and training them on your business.
Definition
The process of further training a pre-trained model on a smaller, domain-specific dataset to specialize it for a particular task. Adjusts the model's weights to perform better in a specific context.
Why it matters
The primary mechanism for making general-purpose AI models useful for specific business applications.
Related terms in Model Training
Adversarial Training
Teaching an AI to defend itself by constantly attacking it with tricky or malicious inputs during training.
Autoencoders
A neural network that learns to compress data into a small code and then unzip it back to the original.
Distillation (Model Distillation)
Teaching a small, fast AI model to mimic a large, expensive one, so you get similar results at a fraction of the cost.
Dropout
Randomly turning off some neurons during training so the AI doesn't over-memorize and can generalize better.
From vocabulary to outcomes
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Knowing the term is step one. Deploying it inside a revenue architecture that compounds is what Sophizo builds.
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