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Abu Dhabi-Developed AI Arabic Language Model Unveiled
The open-source bilingual model is called Jais and is more accurate than existing Arabic implementations, developers say.
A new AI Arabic language model has been unveiled by Abu Dhabi-based Inception, a subsidiary of G42. The project aims to bring one of the world’s most widely used languages into the AI mainstream.
Jais — named after Jebel Jais, the highest mountain peak in the UAE — was developed for government use and financial, energy, climate, and healthcare applications. The open-source bilingual Arabic-English model was built with additional input from the Mohammed bin Zayed University of Artificial Intelligence and Cerebras Systems, based in Silicon Valley.
Jais developers claim the new AI language model is more accurate than previous Arabic LLMs. The software also represents a further step towards encouraging scientific and computing communities to work in languages other than English.
“We see Jais becoming very useful in generative use cases, such as generating responses to questions, generating documents, translations, emails, and even providing advice and recommendations,” said Andrew Jackson, CEO of Inception.
As well as understanding context and cultural references, Jais can also capture linguistic nuances across various Arabic dialects, “making it more accurate and contextually relevant than other models,” the developers said.
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Jais was trained using Condor Galaxy, the “world’s largest AI supercomputer”, launched by parent company G42 and Cerebras in July. The software is continuously expanding as more Arabic content is curated, according to the companies involved.
WorldData ranks Arabic as one of the world’s most widespread languages, with over 400 million speakers. It is the official language of 22 countries and is partly spoken in 11 more. However, despite a dramatic rise in Arabic content, the language still only represents around 1% of the online space, according to data presented by G42 and Cerberus.
Jais software is available to download on the machine learning platform Hugging Face.