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NVIDIA Reveals Details Of Powerful DGX GH200 Supercomputer

The DGX GH200 architecture will enable hundreds of chips to act as a single GPU, and has been built with generative AI in mind.

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nvidia reveals details of powerful dgx gh200 supercomputer
NVIDIA

NVIDIA has revealed details about the company’s next supercomputer, the DGX GH200, which has been built to help companies develop generative AI models.

The machine uses a new NVLink Switch System to enable 256 chips to perform as if they were a single GPU. NVIDIA claims the system offers nearly 500 times as much memory as you’d find in previous DGX A100 computers, quite probably making it the most powerful supercomputer on the planet.

Several key players are interested in the DGX GH200. Google Cloud, Meta, and Microsoft will be some of the first to put the system through its paces as they test its capacity for generative AI workloads.

Also Read: Dubai Launches AI System To Reduce Traffic Congestion

NVIDIA says the new machine will be available by the end of 2023, by which time they should have already developed Helios, an even more powerful version combining four DGX GH200 systems.

Meanwhile, on the gaming front, NVIDIA’s Avatar Cloud Engine (ACE) has been revealed, allowing developers to create custom AI models for speech, conversation, and animation. NVIDIA claims that ACE for Games will “give non-playable characters conversational skills so they can respond to questions with lifelike personalities that evolve”.

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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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