Multi-modal Large Language Models (MLLMs) are gaining significant attention for their ability to process multi-modal data, providing enhanced contextual understanding of complex problems. MLLMs have demonstrated exceptional capabilities in tasks such as Visual Question Answering (VQA); however, they often struggle with fundamental engineering problems, and there is a scarcity of specialized datasets for training on topics like digital electronics. To address this gap, we propose a benchmark dataset called ElectroVizQA specifically designed to evaluate MLLMs' performance on digital electronic circuit problems commonly found in undergraduate curricula. This dataset, the first of its kind tailored for the VQA task in digital electronics, comprises approximately 626 visual questions, offering a comprehensive overview of digital electronics topics. This paper rigorously assesses the extent to which MLLMs can understand and solve digital electronic circuit questions, providing insights into their capabilities and limitations within this specialized domain. By introducing this benchmark dataset, we aim to motivate further research and development in the application of MLLMs to engineering education, ultimately bridging the performance gap and enhancing the efficacy of these models in technical fields.

This course is being covered by a Semiconductor Industry Professional with about 4 years of industrial experience with Masters Degree in Embedded Systems and will have elements of practical application throughout the course for better understanding. Digital Electronics course is essential for many graduate courses and forms the basis for many other courses. It's important to get these basics right to build strong foundation. You can quickly go through introductory lectures which are available for preview and signup for the rest of the course! Check out the initial few lectures for dis counts on the course!

Nowadays the term computing is very broad. The definition covers everything that is necessary to handle information with computers, e.g. Whole disciplines like Computer Engineering, Information Technology or Cybersecurity also belong to this term. I want to start this article with a very brief history of computing and based on this extrapolate where the journey could go. Computing is as old as mankind.

As anyone who can operate a personal computer knows, the way to make the machine perform some desired task is to open the appropriate program stored in the computer's memory. Life was not always so simple. The earliest large-scale electronic digital computers, the British Colossus (1944) and the American ENIAC (1945), did not store programs in memory. To set up these computers for a fresh task, it was necessary to modify some of the machine's wiring, re-routing cables by hand and setting switches. The basic principle of the modern computer--the idea of controlling the machine's operations by means of a program of coded instructions stored in the computer's memory--was conceived by Alan Turing.