News
Google Is Developing An AI Cancer-Spotting Microscope
The search giant has teamed up with the US Department of Defense to build the new detection tool.
Google has developed an “Augmented Reality Microscope” (ARM) in collaboration with the US Department of Defense. The prototype uses AI enhancements to add real-time visual indicators such as heat maps or object boundaries, making identifying the presence of known pathogens and cancer cells easier.
The ARM was first teased in 2018, and the latest prototype has still not been used to diagnose real patients. After further testing, Google hopes that the technology will be “retrofitted into existing light microscopes in hospitals and clinics”. Once installed, ARM-equipped microscopes will give clinicians a variety of visual feedback cues, including text, arrows, contours, animations and heat maps.

The US Department of Defense’s “Defense Innovation Unit” has already negotiated agreements with Google to enable Augmented Reality Microscope distribution through military channels. ARM is expected to cost $90,000 to $100,000 per unit — a figure well beyond many local health providers.
Also Read: Canadian University Dubai Students Create Smart Garbage Bin
This is not the first time Google Health has invested in AI-powered diagnostic tools. Parent company Alphabet already has a strong record of partnering with startups that invest in AI to “improve healthcare” and is projected to have spent over $200 billion on AI technology over the past decade — something that’s especially noteworthy at a time when the World Health Organization is predicting a worldwide deficit of 15 million health care workers by 2030.
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.
-
News3 weeks agoAbu Dhabi’s Robot Kitchen Is Serving Up Biryani, Not Burgers
-
Product Reviews3 weeks agoShokz OpenDots 2 Review: Clip-On Audio Gets A Bass-Heavy Makeover
-
News3 weeks agoSennheiser’s MOMENTUM 5 Series Bets On Batteries You Can Swap
-
News2 weeks agoCheckout.com Reports 20% Higher Payment Acceptance For PRYPCO
