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

NEW RELEASE: RELIANOID 8.4 Enterprise Edition is here!

- We’re excited to announce the launch of RELIANOID 8.4, bringing greater performance, security, and automation to your Application Delivery Infrastructure. - What’s new in 8.4: - High-Performance Proxy – Now with HTTP/2 support and Hot Restart for seamless, zero-downtime updates. - Multi-Factor Aut..

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Customer Marketing Manager, Last9

OpenTelemetry Spans Explained: Deconstructing Distributed Tracing

Understand how OpenTelemetry Spans capture, connect, and explain every operation in your distributed system for deeper visibility.

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

🔁 In case you missed it:Incident Response in 2025: Lessons Learned

🔁 In case you missed it: Our August blog post — “Incident Response in 2025: Lessons Learned” — looks back at a summer marked by major cyber incidents, from supply chain disruptions to large-scale data breaches. Discover how AI-driven detection, faster response strategies, and new resilience tools ar..

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Customer Marketing Manager, Last9

Top 9 APM Tools for Node.js Performance Monitoring

Compare top APM tools for Node.js — from open-source options to enterprise-grade platforms — and choose the best fit for your stack.

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@anjali shared a link, 1 month, 1 week ago
Customer Marketing Manager, Last9

Top 11 Ruby APM Tools for 2025: A Performance-Driven Selection

Explore the top Ruby APM tools for 2025 — from open-source to enterprise — to monitor, trace, and optimize your app’s performance.

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@4e4c52 started using tool Ruby on Rails , 1 month, 1 week ago.
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@4e4c52 started using tool Ruby , 1 month, 1 week ago.
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.