
ailone
Private AI that runs in your office, not in the cloud
What it does
Ailone deploys complete on-premise AI systems for businesses. We set up dedicated GPU hardware (NVIDIA DGX Spark, ASUS, MSI), install optimized open-source LLMs (Llama 4, Gemma 4, Qwen, GPT-OSS), and integrate AI with your email, CRM, and SQL databases. Your data never leaves your servers. No cloud, no subscriptions, fully GDPR compliant. One-time deployment starting at $2,500. Based in Warsaw, remote deployment available worldwide.
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- RLRunning LLMs in one line of Python without Docker2023 · lepton.ai · ▲68
Hello Hacker News! We're Yangqing, Xiang and JJ from lepton.ai. We are building a platform to run any AI models as easy as writing local code, and to get your favorite models in minutes. It's like container for AI, but without the hassle of actually building a docker image. We built and contributed to some of the world's most popular AI software - PyTorch 1.0, ONNX, Caffe, etcd, Kubernetes, etc. We also managed hundreds of thousands of computers in our previous jobs. And we found that the AI software stack is usually unnecessarily complex - and we want to change that. Imagine if you are a…

AI Hive May 2026 · app.aihive.global · ▲53Build, deploy, and run all your AI agents in one platform.

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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com


Launched alongside, June 2026
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- H6Homebrew 6.0.0▲1,481
Today, I’m proud to announce Homebrew 6.0.0. The most significant changes since 5.1.0 are a new tap trust security mechanism, the new faster, smaller, default internal Homebrew JSON API, sandboxing on Linux, better defaults informed by our user survey, many brew bundle improvements, improved performance and initial support for macOS 27 (Golden Gate). Happy to discuss any questions here!
Dev tools · Jun 2026 · brew.sh
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Life & fun · Jun 2026 · vorpus.github.io


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Life & fun · Jun 2026 · hackernewstrends.com