Neurons to Electrons

For a while now, I've been using local GPTs – specifically Large Language Models (LLMs) and image generation. The idea of running these powerful tools on my hardware, without relying on cloud services, is incredibly appealing. It’s about control, privacy, and frankly, a bit of tech nerdiness! This post details how I’ve set up my local LLM environment, including integrating Stable Diffusion for some amazing image creation.     My Local Setup Let’s start with the basics. My system is running Ubuntu 25.04 (codename "Plucky") on an Intel-based machine. Here's a breakdown: Operating System: Ubuntu 25.04 Kernel: 6.14.0-33-generic GPU: NVIDIA RTX 500 Ada Generation (Driver Version: 580.95.05, CUDA Version: 13.0) Display Server: Wayland [$XDG_SESSION_TYPE] - Crucially, I switched to Wayland as it significantly impacted GPU utilization. Initially, I experienced limitations with GPU performance compared to X11, but I’ve found optimized settings to mitigate t...

AEC-Q100 vs. ASIL-B: Quality Meets Safety In the era of autonomous driving and electric vehicles, the electronic components that run your car are more sophisticated than ever. But there’s a critical difference between a chip that is merely durable and one that is truly safe . In the automotive world, this distinction is governed by two major standards: AEC-Q100 and ASIL-B (Automotive Safety Integrity Level). For any electronic control unit (ECU)—from the brake system to the battery manager—to be considered safe, it must satisfy both. Here’s a look at what these standards mean, how they differ, and why they must work together. 🚧 Pillar 1: AEC-Q100 — The Quality and Reliability Guardian AEC-Q100 is the standard established by the Automotive Electronics Council (AEC). Its focus is purely on the physical robustness and reliability of integrated circuits (ICs). This is the baseline that ensures the chip is ...

Just watch what the inventor says.... don't ask me: One of the most simplest explanations and Arbiters, where touring machine screwed up...

 For a long time, I’d heard the buzz around functional programming – the elegant code, the focus on immutability , the promise of easier testing. But frankly, it felt abstract. My background was largely in imperative languages , and the shift felt… significant. This post isn't about converting you to a functional evangelist, but rather about my personal journey into this paradigm, particularly focusing on the deep technical challenges and rewards of embracing it.  Before starting, let me share some of great talks I've bookmarked: https://www.youtube.com/watch?v=ZhuHCtR3xq8 https://www.youtube.com/watch?v=z0N1aZ6SnBk   The Initial Resistance (and Why It’s Valid) Let's be honest – the initial learning curve was steep. Moving from thinking about how to change data to thinking about what to compute was a mental shift. The lack of side effects felt restrictive at first. I wrestled with recursion , struggled to visualize immutable data , and questioned the efficie...

Steering the Future: Automotive Software Standards and the Rise of the Software-Defined Vehicle 🚗💻 The automotive industry is in the midst of a revolutionary shift, transforming from mechanical marvels into sophisticated, software-defined vehicles (SDVs) . For aspiring and current automotive software engineers, navigating the complex landscape of standards and emerging trends is no longer optional—it's essential. The Foundation: Understanding Classical AUTOSAR The backbone of modern Electronic Control Unit (ECU) software is AUTOSAR (AUTomotive Open System ARchitecture) . This standard has been instrumental in enabling software portability, reusability, and modularity across different vehicle platforms and suppliers. Key AUTOSAR Concepts: Layered Architecture : Think of AUTOSAR like a structured building. Application Layer : The "user" level, where high-level functions like cruise control logic reside. Runtime Environment (RTE) : The crucial middleman, enabling communica...

Implementing a CRDT Application with JavaScript and C++ Clients In today’s interconnected world, distributed systems are everywhere—from collaborative editing tools and messaging apps to cloud databases and IoT networks. One of the biggest challenges in these systems is ensuring that data remains consistent across multiple devices and platforms, even when updates happen independently and network partitions occur. Traditional approaches often rely on complex conflict resolution or central coordination, which can introduce latency, bottlenecks, or even single points of failure. Enter Conflict-free Replicated Data Types (CRDTs) , a family of data structures designed to make distributed consistency simple, robust, and scalable. A Brief History and Theoretical Foundations of CRDTs The concept of CRDTs emerged in the late 2000s as researchers and engineers sought better ways to handle data replication in distributed systems. The foundational work by Marc Shapiro and others formalize...