Why AI doesn't speak every language
Vox・2 minutes read
Large language models like GPT-3 and GPT-4 struggle with processing diverse global languages, leading to a focus on natural language processing applications like ChatGPT. Research reveals a lack of attention to many languages, with initiatives such as Big Science's BLOOM working towards creating multilingual models that include low-resource languages.
Insights
- The development of large language models like GPT-3 and GPT-4 is hindered by challenges in handling diverse languages globally, leading to a focus on high-resource languages like English.
- Efforts by researchers such as Ruth-Ann Armstrong and initiatives like Big Science’s BLOOM highlight a growing emphasis on creating datasets and developing multilingual models to address the disparity in natural language processing attention towards low-resource languages like Jamaican patois and Catalan.
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Recent questions
What challenges do large language models face?
Large language models like GPT-3 and GPT-4 encounter difficulties in processing diverse languages globally due to their focus on high-resource languages and lack of attention to low-resource languages.
What is ChatGPT focused on?
ChatGPT, an application built on GPT, concentrates on natural language processing for various applications, emphasizing communication and interaction through text-based conversations.
What does Common Crawl index globally?
Common Crawl indexes websites globally, revealing a dominance of English and other high-resource languages, showcasing the disparity in language representation on the internet.
What disparity exists in NLP focus?
Research highlights a disparity in NLP focus, with only a few languages receiving attention, leading to a lack of resources and tools for low-resource languages.
What is the goal of initiatives like Big Science’s BLOOM?
Initiatives like Big Science’s BLOOM aim to develop multilingual models with open-source collaboration, emphasizing inclusivity of low-resource languages and promoting diversity in language processing technologies.
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Summary
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Global Language Models Face Multilingual Challenges
- Large language models like GPT-3 and GPT-4 face challenges in processing diverse languages globally.
- ChatGPT, an app built on GPT, focuses on natural language processing for various applications.
- Common Crawl indexes websites globally, revealing a dominance of English and other high-resource languages.
- Research highlights a disparity in NLP focus, with only a few languages receiving attention.
- Researchers like Ruth-Ann Armstrong work on creating datasets for low-resource languages like Jamaican patois.
- Evaluation of big language models like GPT-3 on languages like Catalan shows promising results despite minimal training data.
- Initiatives like Big Science’s BLOOM aim to develop multilingual models with open-source collaboration, emphasizing inclusivity of low-resource languages.
