Last year, when Google first shared details about its language-based models, it revealed that it had trained LaMDA with 137 billion parameters. In contrast, PaLM was trained with around 540 billion parameters, making it a more comprehensive dataset with more diverse answers. While both models may have evolved and grown since early 2022, the transition to PaLM should provide Bard with the much-needed boost to better compete with its rivals.
