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Researchers develop new way to help machine-generated language systems reduce toxic language May 15, 2021 at 8:05 am (AI2 Photo) A young child’s ability to acquire language is nothing short of astonishing. But occasionally a toddler will pick up an inappropriate word, often with no comprehension of its meaning. Fortunately, with the right guidance, the child can be steered away from using the offensive term. A similar situation can occur with natural language generation (NLG) in machine learning, even though the process is very different from how people use words. NLG systems like OpenAI’s GPT-3 language model are neural networks that have been pre-trained on a corpus an enormous collection of writings. Using deep learning methods, the model is used to automatically create human-like text from a simple input prompt. The results can be incredibly realistic and at times difficult to discern from something written by an actual person.

Alisa liuAllen institute for artificial intelligenceUniversity of washingtonAllen instituteArtificial intelligenceOn the fly controlled text generationMaarten sapஆலன் நிறுவனம் க்கு செயற்கை உளவுத்துறைபல்கலைக்கழகம் ஆஃப் வாஷிங்டன்ஆலன் நிறுவனம்செயற்கை உளவுத்துறைமார்டன் சப்