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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.

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abu dhabi-developed ai arabic language model unveiled

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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Nano Banana 2 Arrives In MENA For Google Gemini Users

Google brings its latest image model to Gemini and Search, adding 4K output and tighter text control for regional users.

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nano banana 2 arrives in mena for google gemini users
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Google has opened access to Nano Banana 2 across the Middle East and North Africa, pushing its newest image model into everyday tools rather than keeping it inside the exclusive (and expensive) Pro tier.

The rollout spans the Google Gemini desktop and mobile apps, and extends to Google Search through Lens and AI Mode. Developers can also test it in preview via AI Studio and the Gemini API.

Nano Banana 2 runs on Gemini Flash, Google’s fast inference layer. The focus is speed, but also control. Users can export visuals from 512px up to 4K, adjusting aspect ratios for everything from vertical social posts to widescreen displays.

The model maintains character likeness across up to five figures and preserves fidelity for as many as 14 objects within a single workflow. This enables visual continuity across scenes, iterations, or edits — supporting projects like short films, storyboards, and multi-scene narratives. Text rendering has also been improved, delivering legible typography in mockups and greeting cards, with built-in translation and localization directly within images.

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Under the hood, the system taps Gemini’s broader knowledge base and pulls in real-time information and imagery from web search to render specific subjects more accurately. Lighting and fine detail have been upgraded, without slowing output.

By embedding the model inside Gemini and Search, Google is normalizing advanced image generation for a mass audience. In MENA, where startups and marketing teams are leaning heavily on AI to scale content across languages and borders, that shift lands at a practical moment.

The move also folds creative tooling deeper into search itself, so that image generation is no longer a separate workflow. It now sits right next to the query box.

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