INTELLECT-3

INTELLECT-3 is a 100B+ parameter Mixture-of-Experts model trained with large-scale asynchronous reinforcement learning, achieving state-of-the-art performance in math, code, science, and reasoning. Released fully open-source, it provides model weights, datasets, environments, and training frameworks for reproducible frontier-level AI research.

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@viktoriiagolovtseva shared a post, 2 weeks, 4 days ago

Your Guide to Cloning in JIRA: How to Clone Issues in Different Ways

While cloning in Jira can be done in just a few clicks, it becomes less straightforward when you have special requirements. What if you need to clone an issue to a different project, clone tasks in bulk, or do this automatically on a schedule? In this article, we explore all these scenarios and provide you with examples and step-by-step instructions.

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@ilobe added a new tool Weights & Biases , 2 weeks, 4 days ago.

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@ek121268 shared a link, 2 weeks, 4 days ago

VP of Product Marketing, http://checkmarx.com

Securing the Museum of Software in an AI Coding Tsunami

In Securing the Museum of Software in an AI Coding Tsunami, Eran Kinsbruner argues that software now consists of legacy, modern, and rapidly AI-generated code, creating unprecedented complexity and risk. Traditional AppSec can’t keep up with machine-speed development. He calls for a unified, developer-first, agentic AppSec platform that embeds security into coding workflows to prevent, fix, and secure all code eras before vulnerabilities reach repositories.

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@eon01 shared a post, 2 weeks, 5 days ago

Founder, FAUN.dev

100 GitHub Projects That Defined 2025: A Community-Driven Ranking

#2025 #top 100 #Report #FAUN.dev #open so...

This article ranks the 100 developer tools developers acted on most in 2025, based on real interaction data from across FAUN·dev() ecosystem.

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.

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