Core42 Launches Arabic Large Language Model Jais 30B to push Demographic-Specific Models

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UAE technology company G42-owned Core42, that focuses on AI solutions and services, launched Arabian LLM Jais 30B which is the most advanced version of its open-source model. The 30 billion parameter model follows the release of the 13 billion parameter Jais model that was launched in August, further positioning UAE’s position in the AI LLM race. 

The model was trained on the powerful AI supercomputer, Condor Galaxy- 1 (CG-1), with four exaFLOPS of training compute, 54 million cores, and 64-nodes, which was built by G42 in partnership with Cerebras Systems. Jais 30B was trained on larger datasets of 126 billion Arabic tokens, 251 billion English tokens and 50 billion code tokens with an increased performance compared to its predecessor. It also offers 160% longer and detailed answers in Arabic and a 233% increase in English. The model also presents better performance in summarisation too. 

UAE’s constant endeavour to push themselves as a major player in the LLM race is ongoing. Recently, Abu Dhabi-based TIII released Falcon 180B, which is the largest open-source language model available.

Demographic Specific Model 

Jais is born from the collaboration between Core42, Mohamed bin Zayed University of Artificial Intelligence and Cerebras Systems. Interestingly, OpenAI recently partnered with G42, the parent of Core42, which will most likely benefit both the parties in the LLM race. With Jais 30B, UAE’s focus towards creating demographic-specific models, similar to the likes of Bhashini and Indus models for India, is gaining momentum. 

The post Core42 Launches Arabic Large Language Model Jais 30B to push Demographic-Specific Models appeared first on Analytics India Magazine.

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Core42 Launches Arabic Large Language Model Jais 30B to push Demographic-Specific Models

UAE technology company G42-owned Core42, that focuses on AI solutions and services, launched Arabian LLM Jais 30B which is the most advanced version of its open-source model. The 30 billion parameter model follows the release of the 13 billion parameter Jais model that was launched in August, further positioning UAE’s position in the AI LLM race. 

The model was trained on the powerful AI supercomputer, Condor Galaxy- 1 (CG-1), with four exaFLOPS of training compute, 54 million cores, and 64-nodes, which was built by G42 in partnership with Cerebras Systems. Jais 30B was trained on larger datasets of 126 billion Arabic tokens, 251 billion English tokens and 50 billion code tokens with an increased performance compared to its predecessor. It also offers 160% longer and detailed answers in Arabic and a 233% increase in English. The model also presents better performance in summarisation too. 

UAE’s constant endeavour to push themselves as a major player in the LLM race is ongoing. Recently, Abu Dhabi-based TIII released Falcon 180B, which is the largest open-source language model available.

Demographic Specific Model 

Jais is born from the collaboration between Core42, Mohamed bin Zayed University of Artificial Intelligence and Cerebras Systems. Interestingly, OpenAI recently partnered with G42, the parent of Core42, which will most likely benefit both the parties in the LLM race. With Jais 30B, UAE’s focus towards creating demographic-specific models, similar to the likes of Bhashini and Indus models for India, is gaining momentum. 

The post Core42 Launches Arabic Large Language Model Jais 30B to push Demographic-Specific Models appeared first on Analytics India Magazine.

Disclaimer

We strive to uphold the highest ethical standards in all of our reporting and coverage. We StartupNews.fyi want to be transparent with our readers about any potential conflicts of interest that may arise in our work. It’s possible that some of the investors we feature may have connections to other businesses, including competitors or companies we write about. However, we want to assure our readers that this will not have any impact on the integrity or impartiality of our reporting. We are committed to delivering accurate, unbiased news and information to our audience, and we will continue to uphold our ethics and principles in all of our work. Thank you for your trust and support.

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