Episode Summary In this episode, we explore a groundbreaking journey of running AI models on modest hardware with DeepSeek R1 operating on a Raspberry Pi. This feat pushes the boundaries of edge AI, showcasing how powerful AI can be harnessed on a budget. We also dive into the cybersecurity realm with Lazarus Group's latest threat, the Marstech1 JavaScript implant, targeting frontend developers. Additionally, we discuss optimizing Node.js response methods for better backend integration with frontend applications.Key Stories 1. **Running DeepSeek R1 on a Raspberry Pi** Innovator Jeremy C. Morgan demonstrates running the DeepSeek R1 AI model on a Raspberry Pi 5, using Ollama to manage the constraints of ARM architecture without CUDA. Despite running solely on CPU, the performance achieved is impressive. Morgan extends his experiments to work with a 7-billion parameter model and explore applications like a Dockerized VueJS chat. This approach democratizes AI experimentation by making it accessible on low-cost hardware. 2. **Lazarus Group’s Marstech1 JavaScript Implant** The Lazarus Group introduces Marstech1, a JavaScript implant attacking frontend developers through GitHub. Targeting major geographical regions, it threatens crucial web extensions and cryptocurrency wallets, highlighting the need for vigilant security in the developer community. 3. **Node.js Response Methods** Mastering response methods such as `res.send()`, `res.json()`, and `res.download()` in Node.js is key for seamless backend integration in frontend applications. These techniques enhance data handling and user interaction, crucial for modern e-commerce platforms.Sources - Running DeepSeek R1 Locally on a Raspberry Pi - Dev.to: https://dev.to/jeremycmorgan/running-deepseek-r1-locally-on-a-raspberry-pi-1gh8- Lazarus Group Deploys Marstech1 JavaScript Implant: https://thehackernews.com/2025/02/lazarus-group-deploys-marstech1.html- Node.js Response Methods: https://dev.to/queentiol/response-methods-heo

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