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Character.AI files for bankruptcy two years after Google’s $2.7 billion deal, now selling assets to Disney for $20 million

Character.AI, once one of Silicon Valley’s most promising generative AI startups, has filed for Chapter 11 bankruptcy protection in the United States and reached an agreement that would give Disney access to some of its technology for $20 million. The […] The post Character.AI files for bankruptcy two years after Google’s $2.7 billion deal, now…

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Cyber Security

Swann Communications SWIFI-SE2KIC

View CSAF Summary Successful exploitation of these vulnerabilities could allow an attacker to view video information without authentication. The following versions of Swann Communications SWIFI-SE2KIC are affected: SWIFI-SE2KIC firmware <=2.0.22 (CVE-2026-107605, CVE-2026-107606, CVE-2026-107607) CVSS Vendor Equipment v3 6.2 Swann Communications SWIFI-SE2KIC firmware 1 Vulnerability Missing Authentication for Critical Function Background Critical Infrastructure Sectors: Commercial Facilities…

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Apps

CISA Urges Patching Newly Exploited Vulnerability in Ivanti Connect Secure

CISA is aware of Ivanti’s disclosure of a newly exploited vulnerability, CVE-2026-104935, affecting Ivanti Connect Secure versions 25.1.1.1 and prior, 25.1.2.2 and prior, and 22.8R2.4 and prior. CISA is aware of cyber threat actors exploiting this zero-day authentication bypass vulnerability, which allows remote, unauthenticated execution of arbitrary commands, to conduct credential theft and data exfiltration.…

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Cyber Security

CISA Adds Two Known Exploited Vulnerabilities to Catalog

CISA has added two new vulnerabilities to its Known Exploited Vulnerabilities (KEV) Catalog, based on evidence of active exploitation. CVE-2026-96951 Microsoft Windows Command Injection Vulnerability CVE-2026-104935 Ivanti Connect Secure Authentication Bypass by Spoofing Vulnerability These types of vulnerabilities are a frequent attack vector for malicious cyber actors and pose significant risks to the federal enterprise. …

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Apps

Mix, Don't Tune: Bilingual Pre-Training Outperforms Hyperparameter Search in Data-Constrained Settings

For most languages of the world, language model pre-training operates in a data-constrained regime where models must repeat their training data many times, degrading generalization. Two remedies exist: aggressive hyperparameter tuning such as high weight decay, and mixing in data from a high-resource auxiliary language to directly aid the low-resource target. While hyperparameter tuning regularizes…

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