Hi there 👋

This post details Manamorphosis, a first-of-its-kind diffusion model developed to complete Magic: The Gathering decklists. It takes a set of known cards and fills in the rest to form a 60-card main deck. Subsequently, using the completed main deck as context, it can complete a 15-card sideboard. The core generative mechanism is based on Denoising Diffusion Probabilistic Models (DDPMs), the same family of models powering many image generation systems like Stable Diffusion and Midjourney, but adapted here for the unique domain of card sets....

Analyzing how people walk using video is common in research and clinical settings, but getting accurate joint angles usually means either expensive equipment or manually annotating frames, which is slow and tedious. Over Easter weekend, I built a Python tool to help my mother with her research study analyzing patient videos. It uses YOLOv11-pose for automatic detection and adds an interactive interface for manual adjustments. What it Does The script (track....

Check out the project on Devpost and view the source code on GitHub. I spent a weekend at HackNC building something to help manage all of my other side projects. What started as a simple “Wouldn’t it be cool if an AI actually rang you to ask if you’d done your work?” turned into AccountaBuddy, a lightweight app that does more than fire off push notifications - it actually calls you, celebrates your wins, and helps you problem-solve when tasks stall....

Training multimodal models often requires large, high-quality conversational audio datasets, which are currently scarce. This document details the creation of Daily Yap, a dataset developed to address this gap. Existing conversational audio datasets present several limitations: Content Scope: Many datasets focus on assistant-user interactions, lacking the breadth of topics found in general human dialogues. Audio-Text Alignment: Datasets with precise alignment between high-quality audio and accurate transcriptions are uncommon. Speaker Diversity: The use of few speakers limits the generalizability of models trained on these datasets....

Magic: The Gathering (MTG) has always fascinated me with its complexity and strategic depth, thanks to its extensive rulebook and vast array of unique cards. Despite the game’s popularity, AI systems specifically designed for MTG have been few and far between, often falling short due to their inability to accurately interpret the intricate rules and interactions between cards. This blog post chronicles my recent endeavor to bridge this gap with large language models (LLMs) by creating a specialized dataset and evaluation metric to improve AI performance in MTG-related tasks....