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News FAUN.dev() Team
@kala shared an update, 1 month, 3 weeks ago
FAUN.dev()

Anthropic Launches Petri: Open-Source Tool for AI Safety Audits

Anthropic introduces Petri, an open-source tool for automating AI safety audits, revealing risky behaviors in leading language models.

News FAUN.dev() Team
@devopslinks shared an update, 1 month, 3 weeks ago
FAUN.dev()

Qovery Secures $13M Series A to Boost DevOps Automation Platform

Kubernetes

Qovery raises $13M Series A to enhance its DevOps automation platform, addressing the DevOps engineer shortage and supporting regional expansion and AI-driven development.

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@laura_garcia shared a post, 1 month, 3 weeks ago
Software Developer, RELIANOID

Japan’s new Active Cyberdefence Law

Japan’s new Active Cyberdefence Law (ACD) is redefining how the nation tackles cyber threats — shifting from a defensive stance to a proactive cybersecurity strategy. Key measures include: ⚙️ Authority to neutralize hostile servers 🤝 Closer public–private collaboration 📢 Mandatory breach reporting A..

Japan's Active Cyberdefence Law
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@laura_garcia shared a post, 1 month, 3 weeks ago
Software Developer, RELIANOID

Asia Hits 50% IPv6 Capability — A Global Milestone

- Asia has reached a major internet milestone: 50% of its systems are now IPv6 capable, positioning the region as a global leader in IPv6 user adoption. - Why this matters: - India (78.1%) and China (810M users) are driving this growth. - Historical IPv4 scarcity in Asia helped fuel early IPv6 inves..

Blog Asia reaches 50 percent IPv6 capability
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@laura_garcia shared a post, 1 month, 3 weeks ago
Software Developer, RELIANOID

🚀 RELIANOID is heading to it-sa Expo&Congress 2025!

📍 Nuremberg, Germany | October 7–9, 2025 🔒 Europe’s largest IT security event with 900+ exhibitors, expert talks & global networking. We’ll be there to showcase how RELIANOID helps businesses stay ahead of evolving cyber threats. 👉 See you in Nuremberg! Send us a DM to make an appointment. #itSa2025..

itsa nuremberg
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@faun shared a link, 1 month, 3 weeks ago
FAUN.dev()

Organize your Slack channels by “How Often”, not “What” - Aggressively Paraphrasing Me

One dev rewired their Slack setup by **engagement frequency**—not subject. Channels got sorted into tiers like “Read Now” and “Read Hourly,” cutting through noise and saving brainpower. It riffs off the **Eisenhower Matrix**, letting priorities shift with projects, not burn people out... read more  

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@faun shared a link, 1 month, 3 weeks ago
FAUN.dev()

Privacy for subdomains: the solution

A two-container setup using **acme.sh** gets Let's Encrypt certs running on a Synology NAS—thanks, Docker. No built-in Certbot support? No problem. Cloudflare DNS API token handles auth. Scheduled tasks handle renewal... read more  

Privacy for subdomains: the solution
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@faun shared a link, 1 month, 3 weeks ago
FAUN.dev()

Users Only Care About 20% of Your Application

Modern apps burst with features most people never touch. Users stick to their favorite 20%. The rest? Frustration, bloat, ignored edge cases. Tools like **VS Code**, **Slack**, and **Notion** nail it by staying lean at the core and letting users stack what they need. Extensions, plug-ins, integrati.. read more  

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@faun shared a link, 1 month, 3 weeks ago
FAUN.dev()

Authentication Explained: When to Use Basic, Bearer, OAuth2, JWT & SSO

Modern apps don’t just check passwords—they rely on **API tokens**, **OAuth**, and **Single Sign-On (SSO)** to know who’s knocking before they open the door... read more  

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@faun shared a link, 1 month, 3 weeks ago
FAUN.dev()

Uncommon Uses of Common Python Standard Library Functions

A fresh guide gives old Python friends a second look—turns out, tools like **itertools.groupby**, **zip**, **bisect**, and **heapq** aren’t just standard; they’re slick solutions to real problems. Think run-length encoding, matrix transposes, or fast, sorted inserts without bringing in another depen.. read more  

INTELLECT-3 is a frontier-class 100B+ Mixture-of-Experts language model developed by Prime Intellect and trained end-to-end using their large-scale asynchronous RL framework, PRIME-RL. Built on the GLM-4.5-Air base model, INTELLECT-3 combines supervised fine-tuning with long-horizon reinforcement learning across hundreds of verifier-backed environments spanning math, code, science, logic, and agentic tasks.

The model was trained on a high-performance cluster of 512 NVIDIA H200 GPUs across 64 nodes, supported by Prime Intellect’s Sandboxes execution engine, deterministic compute orchestration, and Lustre-backed distributed storage. The result is a model that surpasses many larger systems in reasoning benchmarks while remaining fully open-source.

Prime Intellect released not only the model weights but also the full training recipe: PRIME-RL, Verifiers, the Environments Hub, datasets, and evaluation suites. INTELLECT-3 is positioned as a foundation for organizations seeking to post-train or customize their own frontier-grade models without relying on proprietary AI labs.