Localized AI Language Models Surged in 2023: Will the Trend Persist in 2024?
In Brief
The last few months of 2023 saw a surge in the number of localized AI large language models (LLMs) releases.
The last few months of 2023 has seen a surge in the number of localized AI large language model (LLM) releases. Localized language models refer to natural language processing (NLP) AI models that are specifically tailored or adapted to a particular region, language or culture.
China-based DeepSeek launched DeepSeek LLM, a 67 billion parameter model trained from scratch on a massive 2 trillion token dataset, with availability in English and Chinese. Former DeepMind engineer and founder of young startup Runa AI, Aleksa Gordic introduced YugoGPT – a generative language model for Serbian, Croatian, Bosnian and Montenegrin languages of Southern Europe, intending to emulate ChatGPT’s functionality for English.
Likewise, Indian startup Sarvam AI introduced OpenHathi – the country’s first Hindi LLM. Then there are Tamil Llama, Telugu Llama, and OdiaGenAI for Tamil, Telugu and Odia languages (local languages spoken in India) respectively.
All these developments indicate that there is a growing trend across continents to move towards the development of localized language models. The term “localized” emphasizes the customization of the language model to make it more relevant and effective for users in a specific geographic or cultural setting.
This localization process involves training the model on datasets that are representative of the target language or region, ensuring that the model can comprehend and generate text that aligns with the linguistic and cultural characteristics of that area.
The Cultural Significance of Localized Language Models
There will be little opposition when stating that localized language models pave the way for more inclusive and effective AI. These models, designed to cater to specific regions and cultures, are proving to be essential for a variety of reasons. One key aspect is the focus on cultural sensitivity. These models undergo training to comprehend and respect cultural differences, encompassing idioms, colloquialisms, and context-specific language usage.
In November, Russian President Vladimir Putin mentioned that the current AI models “cancel Russian culture”, and the president announced that Russia will increase investment in AI development, across all sectors.
“Our innovations should rest on our traditional values, the wealth and beauty of the Russian language and languages of other peoples in Russia,” he stated.
While acknowledging the diversity within a region, these models adapt to various dialects, accents and language variations. This adaptability ensures a more accurate representation of the linguistic nuances present in different areas. Additionally, the versatility of localized language models shines in their application. From customer support to content creation, these models are tailored to serve specific regions, fostering more meaningful interactions in users’ native language.
Perhaps most importantly, users interacting with systems powered by localized language models enjoy a personalized and natural interaction. The model’s understanding and responses align with users’ linguistic and cultural backgrounds, resulting in a more seamless and engaging experience.
In breaking down language barriers, improving communication and aligning AI applications with diverse linguistic and cultural needs, localized language models are proving indispensable. This shift towards tailored AI solutions reflects a commitment to inclusivity and responsiveness in the ever-evolving landscape of artificial intelligence.
A Trend to Watch Out for in 2024?
The recent surge in localized language models observed in late 2023 is expected to persist throughout 2024, fueled by escalating demand, technological advancements and ongoing research.
The increasing need for AI applications tailored to specific linguistic and cultural contexts is a driving force, with businesses recognizing the importance of enhancing user experiences through these models. Anticipate more refined models as technology evolves, incorporating sophisticated algorithms and improved computing power.
Looking forward, 2024 holds the promise of enhanced multilingual models, improved cultural adaptation, and potentially, the emergence of industry-specific language models.
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About The Author
Kumar is an experienced Tech Journalist with a specialization in the dynamic intersections of AI/ML, marketing technology, and emerging fields such as crypto, blockchain, and NFTs. With over 3 years of experience in the industry, Kumar has established a proven track record in crafting compelling narratives, conducting insightful interviews, and delivering comprehensive insights. Kumar's expertise lies in producing high-impact content, including articles, reports, and research publications for prominent industry platforms. With a unique skill set that combines technical knowledge and storytelling, Kumar excels at communicating complex technological concepts to diverse audiences in a clear and engaging manner.
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Kumar is an experienced Tech Journalist with a specialization in the dynamic intersections of AI/ML, marketing technology, and emerging fields such as crypto, blockchain, and NFTs. With over 3 years of experience in the industry, Kumar has established a proven track record in crafting compelling narratives, conducting insightful interviews, and delivering comprehensive insights. Kumar's expertise lies in producing high-impact content, including articles, reports, and research publications for prominent industry platforms. With a unique skill set that combines technical knowledge and storytelling, Kumar excels at communicating complex technological concepts to diverse audiences in a clear and engaging manner.
