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Dubai Municipality To Test Construction Materials Using AI Robots

The technology shortens testing from 4 days to 8 minutes, according to experts.

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dubai municipality to test construction materials using ai robots
Dubai Media Office

The Central Laboratory of Dubai Municipality is now using robots employing X-Rays and AI technology to conduct the automated chemical analysis of various construction materials, including cement.

Testing is linked to a smart laboratory platform, allowing engineers to receive inspection reports through smartphones and other mobile devices. The new system will improve the quality of the Municipality’s testing services to meet top international construction standards.

Hind Mahmoud Ahmed, Acting Director of the Dubai Central Laboratory Department at Dubai Municipality, explained, “The robots utilize X-rays to precisely carry out chemical analysis of construction materials and cement products used, which allows for effectively meeting the requirements of the construction sector. The technology shortens the duration of the tests from 4 days to 8 minutes, with a record daily increase in the ratio of samples examined to 650 percent, compared to the previous pre-application situation”.

Also Read: StarzPlay Launches Free-To-Play Fantasy Sports Game In MENA

As well as helping to meet stringent safety standards, cement testing also impacts sustainability. Inspection of various mixtures can quickly ascertain their lifespan, helping city planners make better choices when commissioning new buildings. What do you think of the new AI robots?

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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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