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All digests tagged Edge AI
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Meet Sprout, a semi-autonomous plant robot built on a TurtleBot 4 base. It uses Gemini Flash for vision and Gemini Live for voice, demonstrating real-time edge navigation and AI-powered care.
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Discover how Gemma 4 enables powerful, private AI builds that run entirely on-device. Learn about deploying open models for robotics, remote data analysis, and offline coding.
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This tutorial details deploying a standalone VLM kiosk on NVIDIA Jetson using Codex. The process involves local asset serving, configuring automatic full-screen startup, and verifying local inference without cloud dependency.
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Jeremy Adams details building a wearable AI agent (NanoClaw) on a Raspberry Pi 4B. The system uses Neo4j and the POLE schema to create offline-first, graph-based memory, demonstrating robust edge computing capabilities.
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Smart routing for hybrid AI uses the PGX to route queries between local and cloud models, drastically cutting cloud token costs and regaining control of IT AI spend.
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Learn how to build scalable visual AI agents from a single natural language prompt using NVIDIA Cosmos and VSS 3.3. Discover techniques like Adaptive Efficient Video Sampling (EVS) to optimize video processing costs and latency.
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Discover agentic development on NVIDIA Jetson. Learn how coding agents and specialized Jetson skills accelerate edge AI development, enabling complex VLM pipelines on resource-constrained devices.
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To deploy AI on edge devices, the focus must shift from compute to DRAM cost. Tiny LLMs and aggressive quantization allow running capable models like a 2B parameter Gemma on hardware like Raspberry Pi or Qualcomm NPUs.
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