As Samsung continues to pioneer premium mobile AI experiences, we visit Samsung Research centres around the world to learn how Galaxy AI is enabling more users to maximize their potential.

Galaxy AI now supports 16 languages, so more people can expand their language capabilities, even when offline, thanks to on-device translation in features such as Live Translate, Interpreter, Note Assist and Browsing Assist.

But what does AI language development actually involve? Last time, we visited China to learn about the importance of partnering with other leaders in AI. This time, we’re in Brazil to explore how teams work across cultures and borders to bring Galaxy AI to more people.

A diverse country with more than 203 million people embodying a wide range of cultures and traditions, Brazil uses Brazilian Portuguese as its official language. Meanwhile, 22 neighbouring countries use Latin American Spanish.

Although Brazilian Portuguese and Latin American Spanish are widely spoken, intricate variations in both languages presented various challenges when teaching Galaxy AI to discern and distinguish regional differences.

That’s why Samsung R&D Institute Brazil (SRBR) collaborated with Samsung experts from Mexico — as well as third-party partners such as the science and technology institutes SiDi and Sidia — to assemble a multidisciplinary and highly skilled team that could tackle the task.

Lower Barriers, Higher Understanding

The team used thousands of sources and a combination of machine learning and language processing tools to improve the AI model’s recognition of speech, written texts, and regional variations.

But local jargon and names of famous figures — including sports teams, celebrities, and bands — vary widely between regions. Also, the same meaning can be expressed in many different words.

While language models need localized data to gain a comprehensive understanding of the different languages to be translated, such variations inevitably present obstacles.

For example, swimming pool is “alberca” in Mexico — but it is “pileta” in Argentina, Paraguay and Uruguay. Meanwhile, in Colombia, Bolivia and Venezuela, swimming pool is “piscina”, which is also used in Brazil but with a slight tonal difference. And while Colombians might say “chévere” to refer to something cool, Mexicans instead say “padre.”

These differences represent huge challenges for AI language understanding and learning, but the team overcame them by building larger language models, refining processing tools – and collaborating across borders and time zones.

“We had to consider local slang and different ways of speaking before adapting and testing the model accordingly, which required close collaboration between the SRBR quality assurance (QA) team and development teams,” says Mateus Pedroso, Senior Manager and Head of Software Quality Lab at SRBR.

“Since SRBR is located three hours ahead of the QA team in Mexico and 12 hours behind the management team in Korea, we had to create new communication channels and processes to align results and share progress.

This multicultural collaboration generated a fiesta of ideas and solutions for Galaxy AI.”


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