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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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ESET Bets On Specialized Security AI At 0.5% The Training Cost
ESET says NeoCortex can estimate an attacker’s next move, with a kill switch and human oversight built in to keep it from going rogue.
A sign-in anomaly, a suspicious process launch and an unusual connection may look harmless alone. Together, they can describe an intrusion that is hard for security to teams to piece together.
To solve that problem, ESET announced ESET NeoCortex on November 4, 2026: a specialized foundational AI model for cybersecurity. It powers ESET LiveCortex, available within the ESET PROTECT Platform, which connects fragmented security signals and turns them into actionable incidents.
Filtering is the main selling point, with LiveCortex processing billions of raw telemetry events daily, and just 0.00111% of them contributing to incidents presented to customers. The aim is less alert fatigue and more analyst time spent on threats that matter.
NeoCortex is built on world-model architecture, learning how digital environments behave and how events relate. ESET says that lets it reconstruct missing incident context, recognize similar past cases and estimate an attacker’s likely next step – what the company calls “minus-one-day defense,” a chance to intervene before the next stage unfolds. ESET points to Black October, the week leading up to October 25, 2026, when critical security issues affecting PHP, Linux, GitLab and other key systems demanded rapid, prioritized responses, as the kind of moment where that context matters.
ESET’s internal research also suggests a specialized model like NeoCortex can be trained at up to 200 times lower cost than a large general reasoning model, while delivering more accurate, defense-focused results. The company credits optimized training, a focus on cybersecurity vocabulary, lower computing requirements and privately owned hardware.
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“AI is accelerating both cyberattacks and cyberdefenses. With ESET NeoCortex, we are applying our AI investment to develop specialized foundational cybersecurity intelligence that remains under our control and strengthens, rather than replaces, human expertise,” said Juraj Malcho, Chief Technology Officer at ESET.
As part of the design, NeoCortex forms part of a layered architecture combining specialized models, deterministic controls, correlation logic, validation, auditability and expert human oversight. Safeguards include restricted sandboxes, read-only tools, continuous monitoring, defined usage and token limits, a kill switch and human oversight of critical response decisions. The model is also developed and self-hosted on ESET’s own infrastructure, which the company says reduces exposure to shifts among third-party AI providers, including commercial and geopolitical ones.
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