April 4, 2022, 4:01 p.m. | Google AI (noreply@blogger.com)

Google AI Blog ai.googleblog.com

Posted by Sharan Narang and Aakanksha Chowdhery, Software Engineers, Google Research

In recent years, large neural networks trained for language understanding and generation have achieved impressive results across a wide range of tasks. GPT-3 first showed that large language models (LLMs) can be used for few-shot learning and can achieve impressive results without large-scale task-specific data collection or model parameter updating. More recent LLMs, such as GLaM, LaMDA, Gopher, and Megatron-Turing NLG, achieved state-of-the-art few-shot results …

language language model machine learning natural language processing pathways language model performance scaling self-supervised learning

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