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Orca AI To Save Lives With Its Collision Avoidance System For Ships

Orca AI combines data from sensors with artificial intelligence to provide real-time insights that reflect the changing conditions at sea.

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orca ai wants to save lives with its ai collision avoidance system for ships
Orca AI

The recent Suez Canal blockage, which lasted for six days after a 400-metre-long (1,300 ft) container ship ended up wedged across the waterway due to the combination of strong winds and human errors, showed the whole world just how easily can major shipping accidents happen and how severe and long-lasting their impact can be. Unfortunately, the Suez Canal blockage was just one of several thousand marine incidents that occur annually. Now, one Tel Aviv-based company has successfully raised €10.8 million in a Series A round to work on its ship navigation and collision avoidance system, Orca AI.

“The maritime industry has come leaps and bounds in recent years, but is still far behind aviation with technological innovations. Ships deal with increasingly congested waterways, severe weather and low-visibility conditions creating difficult navigation experiences with often expensive cargo,” says Orca AI CEO and co-founder Yarden Gross.

Orca AI combines data from sensors with artificial intelligence to provide real-time insights that reflect the changing conditions at sea. The system can be used for individual ships to deliver predictions and alerts on hazards, but it can also supply fleet managers with insights on the risk behavior and patterns of the entire fleet.

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“Utilizing onboard navigation sensors and high-resolution cameras with proprietary AI algorithms, the technology is able to provide valuable insight such as alerting the crew on dangerous targets, prioritize risk in real-time and sort out complex navigation situations,” explains Dor Raviv, Co-Founder & CTO of Orca AI.

Other tech companies are also trying to make the shipping industry safer and less prone to costly accidents. For example, the Saudi Arabian Oil Company is using AI technology to monitor its maritime fleet, while Stockholm-based X Shore is exploring an auto-docking solution that could greatly streamline what’s arguably the most dangerous part of getting a massive cargo ship from point A to point B.

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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.

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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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