News
Twitter Plans To Charge $19.99 Per Month For Verification
After acquiring the social media platform for $44 billion, Elon Musk has issued a deadline to introduce a paid verification scheme.
In one of his first directives since the takeover, Elon Musk aims to change Twitter Blue, the optional $4.99 per month subscription service, into a more expensive add-on that verifies users with the familiar blue check mark.
If the current plan goes ahead, users will have 90 days to upgrade to the new monthly fee or lose their existing verification completely. Musk has made plenty of noise about revamping Twitter over the last few months and is rumored to have issued a November 7th deadline for this particular change, with employees facing being fired if the feature isn’t in place by that date.
Twitter’s new owner has been in charge for less than a week so far, but has already changed the site’s homepage. When logged-out users visit the root domain, they are redirected to the Explore page that shows trending tweets and the latest news stories. The outspoken Tesla founder is planning mass layoffs of Twitter middle managers and engineers who haven’t recently contributed to the site’s codebase, with cuts expected to begin happening this week.
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The original Twitter Blue subscription launched almost a year ago as a way to view articles without ads, as well as giving subscribers an undo function for Tweets. The service hasn’t been particularly popular, and ad revenue still constitutes the vast majority of the platform’s revenue.
Musk is keen to grow the subscription model to the point where it accounts for half of Twitter’s revenue — let’s see how the controversial Tesla CEO fares over the coming months.
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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