CHATGPT福岡 CHATGPTサムアルトマンのインタビュー GPT4
CHATGPT福岡 CHATGPTサムアルトマンのインタビュー
Pathways Language Model (PaLM): Scaling to 540 Billion Parameters for Breakthrough Performance
MONDAY, APRIL 04, 2022
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 on many tasks by scaling model size, using sparsely activated modules, and training on larger datasets from more diverse sources. Yet much work remains in understanding the capabilities that emerge with few-shot learning as we push the limits of model scale.
Last year Google Research announced our vision for Pathways, a single model that could generalize across domains and tasks while being highly efficient. An important milestone toward realizing this vision was to develop the new Pathways system to orchestrate distributed computation for accelerators. In “PaLM: Scaling Language Modeling with Pathways”, we introduce the Pathways Language Model (PaLM), a 540-billion parameter, dense decoder-only Transformer model trained with the Pathways system, which enabled us to efficiently train a single model across multiple TPU v4 Pods. We evaluated PaLM on hundreds of language understanding and generation tasks, and found that it achieves state-of-the-art few-shot performance across most tasks, by significant margins in many cases.
ChatGPTはOpenAIのWebサイトからアクセスすることができる人工知能ツールで、自然言語テキスト入力に対して回答を生成することができます。ビジネス現場でのタスク自動化やサポートツールとして利用することができ、FAQの自動回答やマーケティングキャンペーンのテキスト生成など多様なタスクに対応することができます。ChatGPTは高い精度を有し、複数のタスクに対応することができ、使いやすい回答を生成するように学習することが期待されます。
CHATGPTを利用した仕事の変革 これからの仕事の仕方のヒントについて 研究しています。
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