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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.
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At I/O 2026, Sundar Pichai Concedes AI Must Deliver Real Value
Gemini 3.5, a personal agent called Spark, agentic shopping, and Android XR eyewear are all aimed at making AI feel useful, not just impressive.
Google’s annual I/O developer conference (I/O 2026) has recently become a status update on the same question: can the company turn its AI spending into products people use every day? This year, chief executive Sundar Pichai described Google as being in a phase of hyper progress, while conceding this is the part of the cycle where people want to see real value in the products they use on a day-to-day basis.
The strategy on display was to push agents — AI systems that act on a user’s behalf — into nearly every Google product at once. Search now has an “intelligent search box” that returns generated explainer videos alongside links. Gmail, Docs, YouTube and Maps are gaining their own agent layers, including a Docs Live feature that turns spoken instructions into drafted text with citations.
Two new models, Gemini 3.5 and a cheaper Gemini 3.5 Flash, arrived the same day. Google says 900 million people now use Gemini, and that more than 50 billion images have been generated with it. The pricing tier names are likely to confuse buyers: a new AI Ultra plan launches at $100 a month, while the older Gemini AI Ultra drops from $250 to $200.
The flashier announcements were Gemini Omni, a video generator pitched as a more realistic answer to OpenAI’s discontinued Sora 2, and Gemini Spark, a personal agent that handles recurring tasks across a user’s Google account. A new universal shopping cart lets agents complete purchases across multiple retailers from inside Google itself, placing the company between the merchant and the buyer, and also owning the checkout.
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Google also confirmed its Android XR eyewear, built with Samsung and frames from Warby Parker and Gentle Monster. Audio-only glasses ship this autumn; a display-equipped version, which would superimpose live translations into the wearer’s field of view, is still in development. Both sets translate, however only the display version shows you the result.
What Pichai did not resolve is the bargain underneath all this. An agent is only useful to the degree it knows your calendar, your inbox, your shopping history and your physical surroundings. Google has now confirmed that, in time, the same context may carry advertising.
