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Orchid Plans To Find Out What’s Wrong With You Before You’re Born
According to CEO Noor Siddiqui, the company isn’t on a mission to make designer babies, but aims to beat genetic odds and relieve suffering.
Each day, around 400,000 babies are welcomed into the world. However, among those, a growing number will experience some kind of birth defect or inherited disease.
Noor Siddiqui, CEO of Orchid, hopes to “mitigate” unpleasant genetic surprises using genome sequencing technology to reveal a wealth of genetic information on which newborns will grow into healthy adults.
Until 2019, IVF specialists had access to under 1% of the human genome. The tests, called PGT-A and PGT-M, scanned a mere 1,000 data points in a genome comprising around 3 billion bases, offering a very limited dataset compared to the technology used by Orchid.
“Our chromosomes are like chapters in a book that make up the table of contents.” Explained Siddiqui. “[PGT-A and PGT-M tests] only examine the table of contents, whereas what Orchid is doing is like a spellcheck on the entire book.” Orchid’s genome sampling technology assesses “100 times the data, covering many more conditions.” In essence, an Orchid report covers three categories of common genetic issues: monogenic disorders, polygenic conditions, and de-novo mutations.
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Orchid’s technology raises many questions. Aside from the obvious ethical concerns, data privacy is the most obvious potential issue with the tests. Noor Siddiqui is keen to alleviate any concerns: “No data at Orchid is ever sold to any third parties. Parents are in complete control of their data. If they want to delete the data, we’re happy to delete it off of our servers. If they want to export the data, they can export the data. And if they want us to re-analyze the data, we can re-analyze the data”.
Compared to a lifetime of medical bills, gene therapy, and suffering, Orchid’s genome screening report has the potential to change the future lives of thousands of newborns worldwide.
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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