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@dwisiswant0 shared a post, 2 weeks ago

The most practical, fast, tiny command sandboxing for AI agents

Need to run one sketchy command without a full container? Here is the most practical, lightweight way to lock down one risky command in your AI pipeline. No daemon, no root, no image build.

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@laura_garcia shared a post, 2 weeks ago
Software Developer, RELIANOID

🚀 Deploy RELIANOID Community Edition v7 on Microsoft Azure using Terraform.

⚡ Infrastructure ready in minutes ⚡ Official Terraform module ⚡ Fully automated Azure deployment Simple. Fast. Reproducible. #Terraform#Azure#DevOps#IaC#LoadBalancer#CloudInfrastructure#RELIANOID https://www.relianoid.com/resources/knowledge-base/community-edition-v7-administration-guide/deploy-reli..

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@laura_garcia shared a post, 2 weeks, 1 day ago
Software Developer, RELIANOID

🚀 See you at DeveloperWeek — February 18–20, 2026!

🚀 See you at DeveloperWeek — February 18–20, 2026! The world’s largest independent software development & AI engineering conference lands in San Jose, bringing together developers, architects, and tech leaders shaping the future of software. From AI & cloud-native to DevSecOps and developer experien..

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@kala shared an update, 2 weeks, 1 day ago
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OpenAI Hires OpenClaw Creator Peter Steinberger; Project Moves to Independent Foundation

OpenClaw

Peter Steinberger, creator of OpenClaw, is joining OpenAI to work on bringing AI agents to a broader audience, while OpenClaw will move to an independent open-source foundation and continue development outside OpenAI’s direct control.

OpenAI Hires OpenClaw Creator Peter Steinberger; Project Moves to Independent Foundation
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@juliocalves started using tool Terraform , 2 weeks, 2 days ago.
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@juliocalves started using tool Kubectl , 2 weeks, 2 days ago.
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@juliocalves started using tool Grafana , 2 weeks, 2 days ago.
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@juliocalves started using tool Amazon ECS , 2 weeks, 2 days ago.
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vLLM is an advanced open-source framework for serving and running large language models efficiently at scale. Developed by researchers and engineers from UC Berkeley and adopted widely across the AI industry, vLLM focuses on optimizing inference performance through its innovative PagedAttention mechanism — a memory management system that enables near-zero waste in GPU memory utilization. It supports model parallelism, continuous batching, tensor parallelism, and dynamic batching across GPUs, making it ideal for real-world deployment of foundation models. vLLM integrates seamlessly with Hugging Face Transformers, OpenAI-compatible APIs, and popular orchestration tools like Ray Serve and Kubernetes. Its design allows developers and enterprises to host LLMs with reduced latency, lower hardware costs, and increased throughput, powering everything from chatbots to enterprise-scale AI services.