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daniyasiddiqui
daniyasiddiquiEditor’s Choice
Asked: 07/08/20252025-08-07T14:07:57+00:00 2025-08-07T14:07:57+00:00In: Communication, Technology

How are AI modes being localized for low-resource languages and regional markets?

My question is about AI

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    1. daniyasiddiqui
      daniyasiddiqui Editor’s Choice
      2025-08-07T14:28:19+00:00Added an answer on 07/08/2025 at 2:28 pm

      Picture conversing with a clever assistant — but it doesn't communicate your language very well, gets your culture wrong, or botches local names and sayings. That has been a genuine issue across much of the globe. But now, businesses are actually reversing that by localizing AI models for low-resourRead more

      Picture conversing with a clever assistant — but it doesn’t communicate your language very well, gets your culture wrong, or botches local names and sayings. That has been a genuine issue across much of the globe. But now, businesses are actually reversing that by localizing AI models for low-resource languages and markets in their region — and it’s a significant, meaningful change.

      From Global to Local: Why It Matters

      Most AI systems initially learned from English and a few large languages’ data, leaving billions of users with limited coverage.
      But local users demand more than translations — they demand AI that gets their context, talks their dialect, and honors their culture.
      For instance:

      • In India, users might switch mid-sentence between Hindi and English (Hinglish).

      • In Africa, diversity is so high. Some diversity is covered by languages that don’t even have much written text on the web.

      • In Southeast Asia, social nuance, tone, and honorifics count for a great deal.

      •  What Companies Are Doing About It

      Local Data Training
      Research laboratories and startups are gathering news stories, folk tales, radio interviews, and even WhatsApp conversations (with permission) to train AI in neglected languages.
      Community Driven Initiatives

      Local developers, linguists, and NGOs are assisting in the creation of open datasets, benchmarks, and testing models for bias or error.
      Smaller, More Efficient Models

      Rather than huge models requiring mountains of data, firms are creating smaller, optimized AI models that learn fast using less, ideal for low-resource settings.
      Voice and Text Together

      Where literacy is low, AI is being made to comprehend and converse in the local language, not merely read or write.

      •  Real-World Wins

      Africa: Technologies such as Masakhane and African NLP initiatives are enabling AI to comprehend Swahili, Yoruba, Amharic, and others.

      India: Voice and regional language AIs are now supporting Bengali & Tamil, Kannada & Bhojpuri — assisting farmers, students, and small business owners.

      Latin America & Southeast Asia: Voice chatbots are assisting rural communities in accessing health consultations and government services.

      It’s About Inclusion, Not Just Innovation

      Localizing AI isn’t simply a matter of technical difficulty — it’s an issue of inclusion and equity.
      It means more individuals can learn, work, and prosper with AI, regardless of their background or the language they speak.
      And that’s not only intelligent business — it’s the right thing to do.

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