Metis + Orange Pi 5 Plus = edge #AI in your pocket. Here's how to set it all up with Voyager SDK. Still experimental, but seriously intriguing! Anyone else hacking AI on Orange Pi or other SBCs? Would love to see your builds. https://
eu1.hubs.ly/H0kZW3W0 #EdgeAI
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Edge AI Setup: Metis and Orange Pi 5 Plus with Voyager SDK
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Prolog Genius: Why Elixir and Haskell Matter
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i learned even prolog absolutely genius programming approach never used again elixir is the closest thing to haskel reality for me
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iOS Lock Screen Widgets Get More Prominent AI Assistant Icons
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We made the icons on Lock Screen widgets more prominent on iOS. Search, Research, Dictate, Voice Mode (Siri / Assistant).
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Quicksort Implementation in Elixir Programming Language
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you can do similar stuff in elixir which is kinda half-way python (maybe ruby) and haskell (b/c built on erlang) # Base case: empty list def quicksort([]), do: [] # Recursive case: split & sort def quicksort([pivot | rest]) do lesser = Enum.filter(rest, &(&1 <
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Lovable Step 6: Iterate Design With Precision Control
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Step 6: Iterate With Precision We made edits to: Colors Layout Functionality
Lovable makes it easy to roll back or fine-tune your page visually. Control without complexity. -
Lovable: Deploy AI-Built Pages with CRM Integration
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Step 7: Add Lead Capture & Go Live We added email forms & connected them to our CRM. Then deployed directly to our custom domain — all from inside Lovable. From idea → deployed page in one session.
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Lovable AI Tool Delivers Perfect Responsive Design Without CSS Tweaks
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Test Responsiveness
Live preview in Lovable showed a responsive layout out of the box. Mobile looked great. Desktop was spot on.
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Rocket: Prompt-to-Product Engine Generates Deployable App in 6 Minutes
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Rocket is a prompt-to-product engine that doesn’t just generate code – it reasons through your idea like a dev team would. In 6 minutes, I had: Homepage
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Responsive UI
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DeepSeek’s nano-vllm: lightweight Python vLLM implementation
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DeepSeek engineer Xingkai Yu just dropped nano-vllm — a lightweight vLLM reimplementation from scratch. It's a clean implementation under 1,200 lines of Python code with comparable inference speeds to vLLM. Perfect for learning or building lean! Project:
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Stable Diffusion 3.5 Optimization Delivers 2.3x Faster Generation
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As announced at @NVIDIAGTC today, we've collaborated to optimize Stable Diffusion 3.5 using TensorRT and FP8 quantization. Compared to the base @PyTorch models, these optimizations deliver: 2.3x faster generation with SD3.5 Large 1.7x faster generation with SD3.5 Medium