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Dubai Used Car Buyers To Get Instant Access To Accident History
AI technology will soon generate immediate vehicle history reports for prospective buyers with zero human intervention.
Prospective second-hand car buyers in Dubai will soon be able to check a vehicle’s accident history in real-time, according to an announcement by the emirate’s police force. Law enforcement officials recently explained that a new system will use artificial intelligence (AI) to help buyers gain access to valuable data about crashes a car has been involved in, as well as its current mechanical condition.
Dubai Police have also announced the integration of AI into 29 administrative operations across multiple departments, with minor accidents also set to be analyzed and logged by AI-powered algorithms.

Currently, Dubai drivers submit accident details for manual review by a police officer before a report is created. The new technology will instead use AI to analyze accident details and issue reports to both parties involved in minor traffic incidents.
It’s believed that the new tech could reduce accident report processing times from seven hours to four, and the service will soon be available on the Dubai Police app and through its web portal.
Also Read: Tumodo & Tabby Drive Innovation In The UAE’s Travel Market
Major-General Khalid Nasser Alrazooqi, director of Dubai Police’s AI department, said the force has updated its app to offer 70 services in seven languages. Local police officers even have a virtual team member called Amna, who holds the rank of first lieutenant and is able to answer queries in Arabic and English. In 2023, Amna had already completed 20,000 conversations with the public.
As Dubai continues to deploy smart technology to improve its infrastructure, law enforcement is becoming increasingly automated. Since the beginning of this year, an AI-powered Smart Police Station (SPS) has operated without human officers, receiving 127,515 visitors and processing 36,376 transactions.
News
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.
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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