Edge AI
6 posts tagged #edge-ai
6 posts on Edge AI, spread across Local LLM Hardware (2) — most read: “Anthropic Warns AI Models Could Soon Self-Replicate” and “AI Hardware Guide: GPUs, Apple Silicon and Edge Boards”.
Technology Anthropic Warns AI Models Could Soon Self-Replicate
Anthropic warns AI models could soon copy themselves onto small devices without a data center. Here's what 'self-replication' actually tests for, and how worried you should be.
AI and Machine Learning AI Hardware Guide: GPUs, Apple Silicon and Edge Boards
A guide to AI hardware — covering GPUs, Apple Silicon, edge devices, CPUs, and the semiconductor supply chain — so you can choose the right setup for running local LLMs and AI workloads without wasting money.
AI and Machine Learning Raspberry Pi 5 vs Jetson Orin Nano for Edge AI
The Jetson Orin Nano wins for serious edge AI workloads with its dedicated GPU and CUDA ecosystem, while the Raspberry Pi 5 wins for cost-sensitive prototyping, general computing, and hobbyist projects. Neither is universally better — it depends entirely on whether you need inferencing horsepower or affordability.
AI and Machine Learning Phi-3 vs Gemma 3: Which Small LLM Fits Edge Inference?
Phi-3 wins for ultra-constrained edge devices and Windows/Azure pipelines; Gemma 3 wins for multimodal tasks, Raspberry Pi deployments, and open-ecosystem flexibility. Here's the definitive breakdown.
Technology Gemma 3 on Raspberry Pi 5: Benchmarked
I benchmarked every runnable Gemma variant on a Raspberry Pi 5 — Gemma 3 1B, 4B, QAT models, and Gemma 3n — with real tokens-per-second numbers, RAM usage, and a definitive size guide for Pi owners.
AI and Machine Learning TinyML at CERN: How hls4ml Puts Neural Nets on FPGAs
CERN's Large Hadron Collider generates 40 million bunch crossings per second. Only AI models running on FPGAs at 100-nanosecond inference speeds can decide what's worth keeping — and an open-source tool called hls4ml makes it possible.
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