Wordle Solving Robot - Learn how a Wordle-solving robot was built using a 3D printer and a Raspberry Pi, tackling challenges like locating the phone screen, mapping printer bed coordinates, and selecting the best possible guesses.

Sudoku Grab for the iPhone - Unleash the power of technology to effortlessly solve Sudoku puzzles with this incredible iPhone App available on the App Store! Click to learn more and get started.

The PCB Motor Works! - Unlock the potential of weak robotic arms with the latest research and solutions in this captivating video, addressing the challenges and overcoming limitations to achieve remarkable results!

AR Sudoku Solver in Your Browser: TensorFlow & Image Processing Magic - Discover how to recreate a Sudoku app using browser APIs and ecosystem advancements, and explore the image processing pipeline technique for extracting Sudoku puzzles and solving them.

Augmented Reality iPhone Sudoku Grab - Experience real-time augmented reality capture with the new version of Sudoku Grab! Learn to build your own app with detailed guidance provided in the linked article.

Augmented Reality In The Browser - This blog showcases the progress of my idea to create an augmented reality Sudoku solver using technology that enables us to solve puzzles in our browser rather than with dedicated apps. I have developed an AR Sudoku solver with a simple image processing pipeline. It identifies and extracts Sudoku puzzles from pictures, recognizes each cell's numbers, solves the puzzle, and renders the solution on top of the original image. This process is accomplished by converting the image to greyscale, conducting thresholding, OCR-processing, and puzzle-solving. I've also done parallel image location and extraction. It's a technical journey that's achieved some high-quality, low-drift results, visible in the video included. The full codebase is accessible on Github. Enjoy the joy of leveraging technology to efficiently solve Sudoku puzzles!

How does it all work? - In this blog, I explain the process behind my Sudoku Grab app, a solution that uses basic image processing techniques to recognize Sudoku puzzles. This is done by locating the puzzle in an image, turning it back into a square form, segmenting it to find potential numbers, and lastly, recognizing those numbers. This involves simple thresholding techniques, blob extraction algorithm, perspective transform, and a Neural Network for Optical Character Recognition (OCR) to recognize digits from the photograph. I conclude by mentioning the potential for multiple enhancements to this process.

Why does ChatGPT make mistakes - a layman's explanation - In this enlightening blog post, I dive into the tantalizing world of ChatGPT and Large Language Models. Clarifying its operation, I unlock this enigma by comparing its mechanisms to a simple language model. However, Challenges arise due to the explosion of possible token combinations, leading to an inherent 'lossy' compression of our world's vast information. Surprisingly, even with such compression, these models can mimic human language in a compelling manner. I also investigate possible strategies to optimize this amazing technology - including zero-shot learning, one-shot learning, few-shot learning, and fine-tuning. Entering the era of prompt engineering and larger models, we're stepping into a thrilling future, so buckle up, folks!

AI Tools in Coding: Progress or Just Optimization of the Status Quo? - Pondered the future of coding with a colleague of mine recently, as one does. Couldn't help feeling a tad underwhelmed by the programming tools like GitHub's Copilot X and ChatGPT. Sure, these AI-powered coding buddies are smart, helpful and do save time, but they more or less tinker around the edges - optimize the existing processes but don't fundamentally alter them. Software development still remains a tedious enterprise - a loop of problem-definition, code-generation, code-validation, and feedback. Not so different from what it was 30 years ago really. We're surrounded by subpar software everywhere - the bugs, the slowness, the vulnerability. My, what a mess! We need a massive, transformative solution. Imagine an AI system that could take high-level concepts and materialize fully functional apps from them! We've seen glimpses of such capabilities in ChatGPT, generating apps from sketches, but that's just it - glimpses. Still a long way off. My hope for the future? An era where writing code is antiquated. We instruct AI to generate, tweak, even test code - on a constant iterative feedback loop. Maybe, what we know as 'code' could be on the cusp of extinction, replaced by something machines create and understand - and we don't. A brave new world, indeed!

It's Plausible, But Is It True? - Here's a wild ride with ChatGPT and other large language models! They're ace at cooking up plausible-sounding text, but they're not always the best when it comes to spitting out the truth - they've got a funky relationship with facts. One research paper showed they can come out with believable but totally fake answers to seemingly straightforward facts. But when I messed around with various models, there were a few discrepancies. Some got it right or plausibly wrong, but we humans are pretty gullible and tend to believe plausible-sounding info. So when it comes to using ChatGPT, make sure you fact-check, stay away from complex reasoning tasks, and don't try and solve maths problems - seriously, just stop. But it's a cracking tool for generating marketing copy, code (with a fact-check), finding bugs, and getting the creative juices flowing. Stay tuned though - tech's ever-evolving and these intelligent library computers aren't going away anytime soon!