What would it take for AI evaluations to truly support our global experiences? 🌍 Our cross-institutional paper introduces INCLUDE, a multilingual LLM evaluation benchmark of local exams capturing in-language nuances & cultural context for truly localized AI evaluation. https://t.co/o2lNc2LmlT
🗣️ LLM multilenguaje sota que se preocupa de los matices culturales 👇 #ai4all #ai4good https://t.co/BkGY3XOIhY
Let's make AI more inclusive by training open LLMs in many languages Language carries culture, knowledge, and unique perspectives Transparency, openness, and data provenance are key to making AI fair and accessible for all. Become a lead for your lang https://t.co/ekqEvqRLDS https://t.co/qDWJh9aNkD
Recent discussions highlight the importance of cultural diversity in the development of large language models (LLMs). A new initiative, CultureSPA, aims to align AI with pluralistic values while maintaining its effectiveness. Comparisons have been drawn between LLMs and Raspberry Pi, emphasizing how both democratize technology and foster innovation. Advocates are calling for the training of open LLMs in multiple languages to enhance inclusivity, as language is a carrier of culture and knowledge. Transparency and data provenance are deemed essential for ensuring that AI remains fair and accessible. Additionally, a cross-institutional paper has introduced INCLUDE, a multilingual LLM evaluation benchmark designed to capture local nuances and cultural contexts in AI assessments.