Updates and recent posts about INTELLECT-3..

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@rafidbottler gave 🐾 to Artificial Intelligence vs Machine Learning: What's the Difference? , 2 days, 19 hours ago.

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@anjali5 shared a link, 3 days, 15 hours ago

How to Fix Developer Productivity at 50+ Engineers

You ship a feature. It works. A week later, someone asks why it's not in staging yet, and you realize it's behind an infrastructure request that's still in review. The ticket isn't urgent enough to escalate. It's also not small enough to ignore. So it waits.

That's what a developer productivity problem feels like at 50 engineers.

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@laura_garcia shared a post, 3 days, 15 hours ago

Software Developer, RELIANOID

AI Reliability Engineering: The New Era of SRE

🤖 As AI becomes part of critical business operations, reliability is no longer just an infrastructure concern. From latency and model drift to observability and trust, AI workloads introduce a new set of challenges for modern SRE teams. In our latest article, we look at how reliability engineering i..

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@pluto_native started using tool Terraform , 6 days, 9 hours ago.

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@pluto_native started using tool Kubernetes , 6 days, 9 hours ago.

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@pluto_native started using tool Google Cloud Platform , 6 days, 9 hours ago.

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@pluto_native started using tool Amazon Web Services , 6 days, 9 hours ago.

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@eon01 shared a link, 6 days, 14 hours ago

Founder, FAUN.dev

A curated list of free AI models, APIs, and tools you can use without paying a cent.

Running AI shouldn't require a credit card. This list curates genuinely free models — open-weight models you can self-host, free API tiers from major providers, and tools to run everything locally.

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@eon01 added a new tool Unsloth , 6 days, 19 hours ago.

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@eon01 published a course, 6 days, 19 hours ago

Founder, FAUN.dev

Local AI Engineering with Ollama

#LangCha... #Unsloth #Fine-tu... #Ollama #MCP

Run, understand, customize, fine-tune, and build agentic apps on your own hardware

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.