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eCommerce Fashion Platform Namshi Acquired By Noon

The deal worth $335 million will consolidate the region’s eCommerce market by bringing together two of the largest online retailers.

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ecommerce fashion platform namshi acquired by noon
Noon

Emaar, Dubai’s premiere real estate developer, has revealed that it will be selling off ownership rights to the eCommerce fashion platform Namshi, which it has owned outright since 2019, after purchasing a 51% stake back in 2017.

Namshi is being acquired by rival company Noon, who will pay $335.2 million for the acquisition, a price set by an independent valuer and approved via Dubai’s Securities & Commodities Authority. The figure represents a hefty profit for Emaar, who paid $281 in total for full ownership of the company.

“The company would like to announce that its board of directors has, in principle, approved the sale of Namshi to Noon (subject to the approval of the Noon board of directors). Detailed information will be disclosed once the approval of Noon’s board is received formally,”  says Ahmad Thani Rashed Al Matrooshi, board member at Emaar.

Also Read: UAE Startup Dukkantek Raises $10 Million In Funding

The move will considerably consolidate the region’s eCommerce space, as Noon and Namshi are two of the biggest online retailers in the United Arab Emirates, with shopping giant Amazon taking the top spot.

Noon was founded in 2017 by Mohamed Alabbar, the founder of Emaar properties, along with help from Saudi Arabia’s Public Investment Fund. The sale is the second major investment switch for Emaar, who recently bought a stake in the Dubai Creek Harbour development for a massive $2 billion.

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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.

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eset bets on specialized security ai at 0.5% the training cost

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.

Also Read: Dubai Says Its Deepfake Detector Needs Just 7 Seconds Of Video

“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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