VDF AI Networks
Self-improving on-prem agent networks for complex work
What it does
VDF AI Networks lets you describe what you want to achieve — and turns your goal into a multi-agent workflow. It automatically decomposes tasks and orchestrates the right agents, tools and models for each step, with retries, fallbacks and full audit trails. Every run generates feedback, helping Networks continuously improve routing, tool selection and planning. Track cost, latency, energy for every run. Deploy in the cloud, hybrid, or 100% on-prem — with your data staying on your infrastructure.
Deploy and govern AI agents inside your own infrastructure: private RAG, multi-agent orchestration, LLM routing and EU AI Act audit trails. Start free or book a demo.
gate), so the media attribute keeps the warm socket for desktop while clearing PSI mobile's "unused preconnect" flag — browsers that ignore media on hints simply preconnect as before. --> wrapper keeps every existing element/class selector working, the svg tracks font-size via 1em and color via currentColor. -0.125em matches Font Awesome's own SVG baseline shift, so icons sit exactly like the old font glyphs. --> New VDF AI Enterprise is now available on AWS Marketplace → × Production-Grade · Private · Infrastructure-Ready Enterprise AI Agent Platform for On-Premise Control Deploy and govern enterprise AI agents, orchestrate complex workflows, route workloads across models, run…from vdf.ai
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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.
AI · 17d ago · simedw.com
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AI · 18d ago · company-app.joinastute.com
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 · 26d ago · cactuscompute.com
Launched alongside, August 2026
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Life & fun · 10d ago · louisabraham.github.io
- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
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.
AI · 17d ago · simedw.com