0904-NVIDIA Launches NIM Microservices for Generative AI in Japan, Taiwan
Nations around the world are pursuing sovereign AI to produce artificial intelligence using their own computing infrastructure, data, workforce and business networks to ensure AI systems align with local values, laws and interests.
In support of these efforts, NVIDIA today announced the availability of four new NVIDIA NIM microservices that enable developers to more easily build and deploy high-performing generative AI applications.
The microservices support popular community models tailored to meet regional needs. They enhance user interactions through accurate understanding and improved responses based on local languages and cultural heritage.
In the Asia-Pacific region alone, generative AI software revenue is expected to reach $48 billion by 2030 — up from $5 billion this year, according to ABI Research.
Llama-3-Swallow-70B, trained on Japanese data, and Llama-3-Taiwan-70B, trained on Mandarin data, are regional language models that provide a deeper understanding of local laws, regulations and other customs.
The RakutenAI 7B family of models, built on Mistral-7B, were trained on English and Japanese datasets, and are available as two different NIM microservices for Chat and Instruct. Rakuten’s foundation and instruct models have achieved leading scores among open Japanese large language models, landing the top average score in the LM Evaluation Harness benchmark carried out from January to March 2024.
Training a large language model (LLM) on regional languages enhances the effectiveness of its outputs by ensuring more accurate and nuanced communication, as it better understands and reflects cultural and linguistic subtleties.
The models offer leading performance for Japanese and Mandarin language understanding, regional legal tasks, question-answering, and language translation and summarization compared with base LLMs like Llama 3.
Nations worldwide — from Singapore, the United Arab Emirates, South Korea and Sweden to France, Italy and India — are investing in sovereign AI infrastructure.
The new NIM microservices allow businesses, government agencies and universities to host native LLMs in their own environments, enabling developers to build advanced copilots, chatbots and AI assistants.https://blogs.nvidia.com/blog/nim-microservices-generative-ai/
Nations around the world are pursuing sovereign AI to produce artificial intelligence using their own computing infrastructure, data, workforce and business networks to ensure AI systems align with local values, laws and interests.
In support of these efforts, NVIDIA today announced the availability of four new NVIDIA NIM microservices that enable developers to more easily build and deploy high-performing generative AI applications.
The microservices support popular community models tailored to meet regional needs. They enhance user interactions through accurate understanding and improved responses based on local languages and cultural heritage.
In the Asia-Pacific region alone, generative AI software revenue is expected to reach $48 billion by 2030 — up from $5 billion this year, according to ABI Research.
Llama-3-Swallow-70B, trained on Japanese data, and Llama-3-Taiwan-70B, trained on Mandarin data, are regional language models that provide a deeper understanding of local laws, regulations and other customs.
The RakutenAI 7B family of models, built on Mistral-7B, were trained on English and Japanese datasets, and are available as two different NIM microservices for Chat and Instruct. Rakuten’s foundation and instruct models have achieved leading scores among open Japanese large language models, landing the top average score in the LM Evaluation Harness benchmark carried out from January to March 2024.
Training a large language model (LLM) on regional languages enhances the effectiveness of its outputs by ensuring more accurate and nuanced communication, as it better understands and reflects cultural and linguistic subtleties.
The models offer leading performance for Japanese and Mandarin language understanding, regional legal tasks, question-answering, and language translation and summarization compared with base LLMs like Llama 3.
Nations worldwide — from Singapore, the United Arab Emirates, South Korea and Sweden to France, Italy and India — are investing in sovereign AI infrastructure.
The new NIM microservices allow businesses, government agencies and universities to host native LLMs in their own environments, enabling developers to build advanced copilots, chatbots and AI assistants.https://blogs.nvidia.com/blog/nim-microservices-generative-ai/
NVIDIA Blog
NVIDIA Launches NIM Microservices for Generative AI in Japan, Taiwan
NVIDIA announced the availability of four new NVIDIA NIM microservices that enable developers to more easily build and deploy high-performing generative AI applications.