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Twitter Will Default To A For You Page, Just Like TikTok
Twitter is making the algorithmic feed the default option, and the star icon that lets you swap feeds is going too.
Twitter is rolling out changes to how users move between the algorithmically-driven timeline and the reverse chronological feed, making the former the new default.
iOS users will see the changes first, and the company has also removed the star button at the top right for switching between feeds. Instead, in place of the old controls, two tabs labeled “For You” and “Following” allow users to switch between timelines.
TikTok users will instantly notice that the “For You” naming convention follows the popular video platform’s lead. The new default view will show tweets from people that you follow out of order, interspersed with tweets from profiles the algorithm thinks you may like.
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While the changes make it easier to switch between the two feeds, unfortunately, you’re shown the default “For You” timeline every time you relaunch the app. The changes come after controversial new CEO Elon Musk tweeted that the “main timeline should allow for an easy sideways swipe between top, latest, trending, and topics that you follow” and said that Twitter would be “making this change soon”.
So far, there isn’t an option to swipe to trending and followed topics, though the trending page is only a few taps away in the search menu.
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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