Remove BERT Remove Continuous Learning Remove Data Quality
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Training Improved Text Embeddings with Large Language Models

Unite.AI

More recent methods based on pre-trained language models like BERT obtain much better context-aware embeddings. The training data is also constrained in diversity and language coverage. Existing methods predominantly use smaller BERT-style architectures as the backbone model. Adding it provided negligible improvements.

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How AI facilitates more fair and accurate credit scoring

Snorkel AI

Lenders and credit bureaus can build AI models that uncover patterns from historical data and then apply those patterns to new data in order to predict future behavior. Instead of the rule-based decision-making of traditional credit scoring, AI can continually learn and adapt, improving accuracy and efficiency.

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How AI facilitates more fair and accurate credit scoring

Snorkel AI

Lenders and credit bureaus can build AI models that uncover patterns from historical data and then apply those patterns to new data in order to predict future behavior. Instead of the rule-based decision-making of traditional credit scoring, AI can continually learn and adapt, improving accuracy and efficiency.

article thumbnail

How AI facilitates more fair and accurate credit scoring

Snorkel AI

Lenders and credit bureaus can build AI models that uncover patterns from historical data and then apply those patterns to new data in order to predict future behavior. Instead of the rule-based decision-making of traditional credit scoring, AI can continually learn and adapt, improving accuracy and efficiency.