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There are new 3.6 and 3.5 models today, but Google is already training Gemini 4.
A new GA release for the Windows Cloudflare One Client is now available on the stable releases downloads page. This hotfix resolves a regression that caused a large increase in DNS-over-TCP queries to fallback and internal DNS servers. The client now sends fallback DNS queries over UDP first, falling back to TCP only when a response is truncated, instead of querying both protocols in parallel.
A new GA release for the macOS Cloudflare One Client is now available on the stable releases downloads page. This hotfix resolves a regression that caused a large increase in DNS-over-TCP queries to fallback and internal DNS servers. The client now sends fallback DNS queries over UDP first, falling back to TCP only when a response is truncated, instead of querying both protocols in parallel.
A federal judge has signed off on Anthropic's $1.5 billion class action settlement with authors who accused the company of training its AI models on copyrighted books, as reported earlier by Reuters. In an order on Monday, Judge Araceli Martínez-Olguín writes that the settlement will provide "meaningful relief," offering authors around $3,000 for each book allegedly pirated by Anthropic. The $1.5 billion settlement is the "largest known copyright recovery in history," according to the law firm r
A new GA release for the Linux Cloudflare One Client is now available on the stable releases downloads page. This hotfix resolves a regression that caused a large increase in DNS-over-TCP queries to fallback and internal DNS servers. The client now sends fallback DNS queries over UDP first, falling back to TCP only when a response is truncated, instead of querying both protocols in parallel.
Hackers are exploiting the "wp2shell" critical vulnerability suite (CVE-2026-63030 and CVE-2026-60137) affecting WordPress Core to deploy persistent webshells and install malicious plugins on affected servers. [...]
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In this post, we explore an idea for generating thinking tokens for datasets that lack reasoning traces in SFT customization. We first examine the reasoning suppression problem, then introduce Self-Distilled Reasoning (SDR), validate it across three benchmarks, and provide practical recommendations.
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