Transformer models are efficient for training on large data sets without human supervision
Transformer models are taking advantage of GPU compute. Transformer-based models have shown to be very efficient in training on GPUs by parallelizing the ingestion of large amounts of data. Attention mechanisms allow the model to focus on specific parts of the input sequence while processing it, thereby improving its ability to understand and generate complex patterns.
"Looking at previous words only”
Luke,
I
am
your
worst mother
"Looking at all words at once"
Luke,
I
am
your
father worst death
Self Attention 10 Heartcore Capital – AI & Productivity Report
best
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