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@laura_garcia shared a post, 1ย week, 5ย days ago
Software Developer, RELIANOID

๐—ฅ๐—˜๐—Ÿ๐—œ๐—”๐—ก๐—ข๐—œ๐—— ๐Ÿด.๐Ÿฑ ๐—˜๐—ป๐˜๐—ฒ๐—ฟ๐—ฝ๐—ฟ๐—ถ๐˜€๐—ฒ ๐—˜๐—ฑ๐—ถ๐˜๐—ถ๐—ผ๐—ป ๐—ถ๐˜€ ๐—ป๐—ผ๐˜„ ๐—ฎ๐˜ƒ๐—ฎ๐—ถ๐—น๐—ฎ๐—ฏ๐—น๐—ฒ!

- ๐—ฅ๐—˜๐—Ÿ๐—œ๐—”๐—ก๐—ข๐—œ๐—— ๐Ÿด.๐Ÿฑ ๐—˜๐—ป๐˜๐—ฒ๐—ฟ๐—ฝ๐—ฟ๐—ถ๐˜€๐—ฒ ๐—˜๐—ฑ๐—ถ๐˜๐—ถ๐—ผ๐—ป ๐—ถ๐˜€ ๐—ป๐—ผ๐˜„ ๐—ฎ๐˜ƒ๐—ฎ๐—ถ๐—น๐—ฎ๐—ฏ๐—น๐—ฒ! This release represents a major step forward in ๐—ฝ๐—น๐—ฎ๐˜๐—ณ๐—ผ๐—ฟ๐—บ ๐˜€๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜†, ๐˜€๐˜†๐˜€๐˜๐—ฒ๐—บ ๐—ถ๐—ป๐˜๐—ฒ๐—ด๐—ฟ๐—ถ๐˜๐˜†, ๐—ฎ๐—ป๐—ฑ ๐—ฒ๐—ป๐˜๐—ฒ๐—ฟ๐—ฝ๐—ฟ๐—ถ๐˜€๐—ฒ ๐—ฟ๐—ฒ๐—น๐—ถ๐—ฎ๐—ฏ๐—ถ๐—น๐—ถ๐˜๐˜†. - ๐—จ๐—˜๐—™๐—œ ๐—ฆ๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ฒ ๐—•๐—ผ๐—ผ๐˜ ๐˜€๐˜‚๐—ฝ๐—ฝ๐—ผ๐—ฟ๐˜ โ€“ cryptographic verification of the boot chain - ๐——๐—ฒ๐—ฏ๐—ถ๐—ฎ๐—ป ๐—•๐—ผ๐—ผ๐—ธ๐˜„๐—ผ๐—ฟ๐—บ ๐Ÿญ๐Ÿฎ.๐Ÿญ๐Ÿฏ ๐—ฏ๐—ฎ๐˜€๐—ฒ + ๐—ž๐—ฒ๐—ฟ๐—ป๐—ฒ๐—น ๐Ÿฒ.๐Ÿญ.๐Ÿญ๐Ÿฑ๐Ÿต-๐Ÿญ-๐—ป๐—ผ๐—ถ๐—ฑ๐Ÿฌ - ๐—›๐—ฆ๐—ง๐—ฆ..

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@viktoriiagolovtseva shared a post, 1ย week, 5ย days ago

A Git and Jira Integration Guide: How to Connect GitHub, GitLab, and Bitbucket to Jira Cloud

If you ask a developer, product manager, and QA โ€œwhy integrate your Git repository with Jira,โ€ they will all give different answers. Some like it for reducing context switching and providing automation options, while others value the transparency and improved traceability. But no matter who you ask, everyone is unanimous: this integration is immensely useful for the teams.

In this article, we focus on the most popular Git applications: GitHub, GitLab, and Bitbucket. We explain how to connect them to Jira Cloud and provide you with practical tips on making the most out of this integration. You will learn how to use smart commits, leverage automation, and gain extra value from third-party apps.

Zrzut ekranu 2026-02-20 125153
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@ashwinisdave shared a post, 1ย week, 5ย days ago
Developer advocate, Middleware

From Metrics to Meaning: Building Context-Aware Dashboards That Actually Help Debug Production Issues

Most dashboards show what's happening but not why it matters. Learn how to build context-aware dashboards that actually help engineers debug production issues faster.

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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 Intellectโ€™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.