Chain of Thought Will AI Erase All Language Barriers? | Smartling's Olga Beregovaya
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Apr 23, 2025 Olga Beregovaya, VP of AI at Smartling, dives into the captivating world of AI and translation. She discusses how AI has evolved from rule-based systems to sophisticated models that tackle language barriers. Key challenges like English-centric biases and the unpredictability of AI outputs are explored. Olga highlights opportunities in specialized language models and innovative workflows that enhance translator productivity. The potential for multilingual multimodality raises exciting possibilities for the future of global communication and more nuanced translations.
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NLP Evolution and Limits
- The shift from rule-based to transformer-based NLP enables processing natural language at unprecedented scale and speed.
- Despite advances, humans still outperform AI in nuanced language tasks, keeping the Turing test relevant.
Core AI Translation Challenges
- AI translation faces challenges in lexical and domain coverage, especially for long-tail and under-resourced languages.
- Biases and hallucinations remain significant hurdles for reliable, high-quality translation.
English-Centric AI Limits
- English-centric training limits translation accuracy in other languages and cultures.
- Prompts in English often yield better results; fine-tuning on language- and domain-specific data improves coverage.