SEA-LION: Singapore’s Initiative for More Inclusive AI

  • SaySay
  • Ai
  • June 14, 2024
  • 0 Comments

As the adoption of generative artificial intelligence (AI) expands across various industries, the lack of inclusivity and global representation becomes increasingly evident. This issue is particularly significant for large language models (LLMs), which often cater predominantly to Western markets, neglecting vast populations in Southeast Asia.

Southeast Asia is a region with over 692 million people speaking more than a dozen languages, including Filipino, Vietnamese, and Lao. Singapore alone has four official languages: Chinese, English, Tamil, and Malay. However, most existing LLMs do not adequately account for this diversity, leading to underrepresentation of the region’s languages and cultures.

Singapore aims to bridge this gap with the new SEA-LION model, developed by AI Singapore (AISG). SEA-LION is an open-source LLM designed to more accurately and effectively represent the languages and cultures of Southeast Asia. The model currently operates with two versions: one with three billion parameters and another with seven billion parameters.

SEA-LION has been trained on 981 billion language tokens, of which 128 billion pertain to Southeast Asian languages. In contrast, popular models like Meta’s Llama 2 include only 0.5% of their data focused on this region, whereas SEA-LION dedicates 13% of its data to these languages.

A new version of SEA-LION with seven billion parameters is set to be released in mid-2024. Future plans include models with 13 and 30 billion parameters, which will enhance the model’s understanding of regional nuances and context.

As the technology evolves and new tests emerge, SEA-LION will become a more powerful model, providing substantial support for multilingual environments and specific regional needs. Collaboration with other countries in the region, research institutions, and industry partners plays a crucial role in this development.

Singapore’s effort to create a more inclusive and culturally sensitive AI ecosystem is highlighted by Charlie Dai, Vice President and Principal Analyst at Forrester. A solution focused on regional characteristics will help overcome existing barriers and deliver more accurate and relevant data for various applications, from social welfare to healthcare and government administration.

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