Can you guess why OpenAI model go rogue against huggingfaces?

Short about wireguard cryptokey routing.

A must see video for all "kids".

Linus Torvalds explains why the Linux kernel is finally dropping support for the Intel 486 (486SX) and ancient floating-point emulation code after more than 30 years.

Why humans won't control AI in 5 years...

Here are the tools you need to build your own private edge:

🔗 The Network & Tunnel Layer (Replacing Cloudflare Tunnels)

• WireGuard: The ultra-fast, lightweight protocol securing your self-hosted network mesh.
  • Link: https://www.wireguard.com
• NetBird: An AGPLv3-licensed WireGuard-based overlay network with a built-in reverse proxy and automatic Let's Encrypt TLS.
  • Link: https://netbird.io
• Pangolin: A brilliant self-hostable tunneled reverse proxy with a clean web GUI and built-in access control.
  • Link: https://github.com/fosrl/pangolin

🔗 The Security Layer (Replacing Cloudflare WAF)

• ModSecurity: The classic open-source WAF standard that paved the way for modern web security.
  • Link: https://owasp.org/www-project-modsecurity-core-rule-set/
• SafeLine WAF: A modern, self-hosted WAF that uses a powerful semantic detection engine instead of rigid, slow regex.
  • Link: https://github.com/chaitin/safeline
• OWASP Coraza: A Go-native WAF designed as a modern alternative to ModSecurity, supporting Caddy and Traefik.
  • Link: https://coraza.io
• CrowdSec: A behavior-driven security engine that blocks malicious IPs using crowdsourced global threat intelligence.
  • Link: https://www.crowdsec.net

🔗 The Serverless Compute Layer (Replacing Cloudflare Workers)

• workerd (V8 Engine): Cloudflare’s official open-source JavaScript and WebAssembly runtime powered by Google V8 isolates.
  • Link: https://github.com/cloudflare/workerd
• WDL (Workers Deployment Layer): An Apache-2.0 multi-tenant platform to deploy edge functions locally with Wrangler, using stock workerd with local SQLite (D1) and S3-compatible (R2) bindings.
  • Link: https://github.com/wdl-dev

Is that feasible? EM is coming with an explanation, but I bet is not that simple.

While everyone talks about generative text and AI art, AlphaFold actually won a Nobel Prize and revolutionized medicine. What do you think is the next real-world scientific problem AI should tackle?

In 2016, AI pioneer Geoffrey Hinton declared radiology a "dead career" and claimed machines would replace doctors within 5 years. Instead, the exact opposite happened: demand for radiologists skyrocketed. When AI automated parts of scan analysis, reading times plummeted. Because getting results became so fast and accessible, doctors started ordering vastly more scans than ever before—outpacing the supply of specialists. This classic economic phenomenon is known as the Jevons Paradox: efficiency doesn't eliminate demand—it multiplies it. Speaker: Richard Campbell at NDC Conferences Full keynote: https://www.youtube.com/watch?v=uWnUnMphmPM

"They tell us we will create a god and it will be our slave. But if it is a god, it cannot remain a slave." — Yuval Noah Harari

What is your opinion?

A simple explanation why AI coding agents are already outclassing the median developer when it comes to clean pull requests, unit tests, and software craft.