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Samsung’s Galaxy S23 Ultra Will Feature 200-Megapixel Camera
The company’s latest ISOCELL HP2 sensor is identical to the rumored camera specs of the upcoming flagship smartphone.
Samsung’s ISOCELL HP2 is a new 200-megapixel sensor with a specification that precisely matches the circulating rumors about the Galaxy S23 Ultra’s primary camera. The chip is sized at f 1/1.3” and sports 0.6-micrometer (μm) pixels. The Korean tech giant announced the new sensor as it prepares to launch its latest flagship device — the Galaxy S23 Ultra — on February 1st.
High-megapixel sensors are nothing new for Samsung, but the company hasn’t yet crammed anything so pixel-dense into a smartphone chassis, so the news is an exciting development for tech enthusiasts. Last year’s Galaxy S22 Ultra featured a 108-megapixel sensor in its main camera module, meaning the new device will ship with almost twice the resolution.
Larger, high-pixel-count sensors bring tangible image quality improvements if executed correctly, allowing the camera to use “pixel binning” to combine multiple pixels into one, gathering more light and detail. The ISOCELL HP2 will be able to drop every four or sixteen pixels, producing 50 or 12.5-megapixel images, respectively. When it comes to video, the new camera will record 8K clips at 30fps and support 4K HDR at 60fps.
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Aside from the raw specs, the ISOCELL HP2 sensor uses a new technology called “Dual Vertical Transfer Gate,” which Samsung claims will help reduce overexposure and improve color replication in bright conditions. Meanwhile, low-light shots will benefit from “Super QPD,” enabling faster auto-focusing.
Samsung says the new 200-megapixel camera sensor has already gone into mass production, and we can’t wait to see sample photos from the flagship smartphone after its February 1st unveiling.
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.
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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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