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Google Chrome Now Lets You Copy Video Stills For Easy Sharing
The “Copy Video Frame” feature will create better-quality images.
Google Chrome now makes capturing video stills easier than ever after a new feature was added to the popular web browser.
The company acknowledged the struggle users previously faced when trying to capture video stills, noting that screenshots often produced low-quality images with the video progress bar shown at the bottom.
Today, those issues are gone, and for users of any Chromium-based browser (Such as Chrome, Microsoft Edge, or Brave), capturing high-quality stills is as simple as hitting pause, right-clicking, and selecting the “Copy Video Frame” option from the menu.
After trying the new feature ourselves, we noticed that it does have a few issues. For example, you’ll need to right-click twice on YouTube to access the menu: One click will bring up YouTube’s own menu, while the second click reveals the correct Chrome menu with the “Copy Video Frame” option.
Once a user copies a video still, they can paste it directly into another app, such as Google Docs or Apple Notes, for example.
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Right now, there’s no option to save a copied video frame directly to your desktop as a standalone file. The feature is also limited when used on videos from streaming services, with many sites restricting the ability to capture their content. So far, we’ve had the best luck using “Copy Video Frame” on YouTube, which is no surprise given that Google’s parent company, Alphabet, owns the video-streaming giant.
The “Copy Video Frame” feature is available now on all desktop platforms that can run Google Chrome, including MacOS, Windows, Linux, and ChromeOS.
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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