Machine learning (ML) has rapidly become one of the most influential technologies across industries, from healthcare and ...

The model training process is also evolving. RAG training and parameter-efficient fine-tuning are seen as evolutions of traditional model training that produce better quality output with lower ...

Research has shown that parameters pruned after training, a process that decreases the model size, could have been pruned before training without any effect on the network’s ability to learn.

They found that the process of building and testing a final paper-worthy model required training 4,789 models over a six-month period.

Underspecification means something different: even if a training process can produce a good model, it could still spit out a bad one because it won’t know the difference. Neither would we.