News
Meta’s Twitter Rival, Instagram Threads, Launches July 6
If you’ve been considering ditching Twitter, the new competitor might be just what you’ve been waiting for.
Meta’s hotly anticipated Twitter competitor, Instagram Threads, is expected to launch on July 6th, after tech sleuths noticed an Apple App Store listing for the new app, as well as an Android equivalent on Google’s Play Store.
As well as the new apps, Meta has now added a launch date ticker to their Instagram app, which can be activated by typing “threads” into the search box (plus several related keywords), causing a ticker icon to appear in the search bar, along with a link to what is expected to be the platform’s homepage The countdown ticker confirms the July 6th launch date, ending at 10 AM ET.

The App Store and Google Play Store descriptions of the new Instagram Threads app show screenshots of how users can log in using their Instagram handles and views of an interface similar to Mastodon, Bluesky, and of course, Twitter. Like those platforms, Threads will allow users to follow and connect with their favorite creators and other users who love the same things or share similar opinions.
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Last month, Meta explained that Instagram Threads would integrate with the decentralized social media protocol ActivityPub, with one of the executives noting, somewhat controversially: “We’ve been hearing from creators and public figures who are interested in having a platform that is sanely run,” which sparked a humorous exchange that led to a potential cage match fight between Mark Zuckerberg and Elon Musk.
In response to the news of the launch of Instagram Threads, Elon Musk issued a handful of tweets concerning the amount of user data that Meta’s apps would collect. However, it should be noted that Instagram’s existing app already has access to the same dataset.
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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