Update on the Future of “Open Source AI” with Key Trends and New Opportunity Predictions

”,co-hosted by SCB 10X, Sahara AI, and Sambanova, brought together AI experts to share their perspectives in topic emphasized by many AI gurus was “Open Source AI,” which was discussed by Kasima Tharnpipitchai: Head of AI Strategy at SCB 10X and Typhoon AI, Akshita Bakia: Senior Research Engineer at AllenNLP, Antoine Bosselut: Assistant Professor at EPFL, and Nicha Suebwonglee: Senior Venture Capital Business Development Manager at Amazon Web Services. Their discussion, “The Future of Open Source AI: Trends and Predictions,” is summarized in this article.

Open Source AI and the Future of AI

• Open Source AI is playing an increasingly important role by making advanced tools widely accessible and promoting collaboration. This enables researchers, developers, and organizations worldwide to participate in AI advancements.
  
  
• The exchange of views on this topic emphasized the crucial role of Open Source AI in driving the development of AI technology globally. It fosters collaboration and enables rapid innovation.
  
  
• Open Source AI also plays a significant role in developing local AI technologies, such as creating language models for specific regions and cultures, and addressing ethical issues like fairness and transparency.

Key Open Source AI Trends in the Future

• Importance of Developing Local AI Language Models: This emphasizes the need to create AI models suitable for different cultures and languages with varying contexts in each region. General models may not adequately meet the diverse cultural and linguistic needs. Developing AI models for specific languages and cultures will allow AI to better meet users' needs.
  
  
• Importance of High-Quality Open Source Data: Access to and management of high-quality data are crucial factors in developing effective AI models. Therefore, it's necessary to manage Open Source data carefully. By utilizing available Open Source data and improving data quality, researchers can develop more efficient and reliable AI models.
  
  
• Data Transparency: Disclosing the data used for training and the methods for developing AI models will become increasingly important to ensure transparency, trust, and guarantee ethical AI use. This also allows users to effectively examine and evaluate models.
  
  
• Composable Models or Agentic Workflows Trend: A significant trend in the future of AI, Composable Models involve combining different models or components for specific purposes. This enables greater flexibility and customization, giving developers an advantage in creating AI solutions that better meet specific needs.
  
  
• Promoting Collaboration: Collaboration between researchers, organizations, and governments to develop high-quality and fair AI will be a crucial factor in the continuous development of Open Source AI.
  
  
• Ethical Considerations: This point highlights the importance of addressing ethical issues in AI development, including ensuring fairness, transparency, and accountability in AI systems. Open Source AI development can play a vital role in promoting ethical practices and reducing AI bias.

Challenges and Opportunities

• Ethical Challenges: AI development must consider ethical issues such as fairness, transparency, data bias, inappropriate use, and privacy violations. Addressing these challenges will be crucial for responsible creation and use of Open Source AI.
  
  
• Data Challenges: Access to and management of quality data suitable for local contexts are essential, especially in regions with limited resources.
  
  
• Developing Language and Culture-Specific Models: Developing AI models that can meet the needs of users in different regions and cultures presents a significant opportunity to drive local AI development.
  
  
• Increased Opportunities for Creation: Open Source AI can provide opportunities for people worldwide to participate in creating and developing AI technology more easily.

Conclusion

Open Source AI will play a crucial role in driving AI technology development in the future. Developing culture and region specific language models, data transparency, and collaboration will be key trends. However, it's important to consider ethical challenges and be prepared to address various challenges effectively.

Watch this session Youtube: https://youtu.be/ZLuA3XTVKHc?si=gIj_cKxFSE9oHpqr