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Lebanon Postpones Daylight Saving Time Shift By 1 Month

The decision has left Lebanon waking up in two different time zones this morning.

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lebanon postpones daylight saving time shift by 1 month
AFP

In a last-minute decision, Lebanon’s government announced that the shift away from daylight saving time would be postponed by a month, extending DST until the end of Ramadan. As a result, while most Northern Hemisphere countries automatically advanced their times by an hour yesterday, the people of Lebanon were left confused about the exact time they should set their alarms on Sunday morning.

In an alleged video leak shown by news outlet Megaphone, Lebanon’s prime minister, Najib Mikati, and parliament speaker Nabih Berri discussed the postponement, with Berri insisting on delaying the switch away from DST.

Most digital devices with network access, such as smartphones and computers, switch in and out of daylight saving time automatically, so Lebanese citizens were asked to adjust their clocks back an hour manually.

Also Read: A Line-Up Of Over 100 Shows Comes To Snapchat This Ramadan

Although public institutions are forced to abide by the government’s decision, many private businesses ignored the request and continued to follow the existing schedule. The confusion has left Lebanon — a small country that can be transversed east to west in less than two hours — with two separate time zones.

The chaos has resulted in missed appointments, TV channels displaying different times, and even Google searches with the wrong timestamps.

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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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