What are the main challenges in training AI models?

What are the main challenges in training AI models?

Some key challenges include data quality, overfitting, computational resources, and bias in training data.

How does data quality affect AI model training?

Data quality is crucial; poor quality data can lead to inaccurate models and unreliable predictions.

What is overfitting and how can it be avoided?

Overfitting occurs when a model learns noise instead of the signal. It can be avoided by using techniques like cross-validation and regularization.

Can you explain bias in training data?

Bias in training data can lead to unfair or skewed outcomes. It's important to ensure diverse and representative datasets.

What resources are needed for training large AI models?

Training large AI models requires significant computational power, often utilizing GPUs or TPUs, and large amounts of memory.