The goal hasn't changed too much, make building decks easier by knowing exactly what you own and where it’s stored. You organize cards into boxes, search your inventory, search friends’ collections, and keep track of trades instead of digging through a similar closet of cards that my daughter and I search for.

The fun part has been the AI. I trained computer vision models that run entirely on the phone to detect and identify Pokémon cards. Training has become the slowest part. For the model that needs to be retrained every new release, I’m up to about 5 hours per epoch on my M4 Mac with 16 GB of RAM.

The Android app is currently in public testing with people from my local Pokémon league. It’s built with React Native, and I’m working on the iPhone version next.

Still lots to build, mostly around product and ux, and because a recent stupid mistake on my part, backups and deployment safeguards.

It's been pretty fun to build. Trained a couple of models to identify a card that run on the phone app. They work very well and are comparable, and much better than many, to any other card identifier in the market. As the models get more complicated training is getting a bit longer. I'm at about 9 hours per epoch on my Mac M4 with 16G of memory.

The Android phone app is in public test with a couple of my local group testing. The app is built in React Native, and I’m hoping to get an iPhone version out soon since there are a bunch of iPhone peeps.

It's been a super fun tool to build. The phone app just got approved in the Android app store. I have a bit of cleanup, but plan on releasing it soon.

I’ve been building a phone app + website (https://MyBulkCards.com) to scan cards and organize where everything is. It’s pretty basic right now, but I can store cards in boxes like “Box 1 AAA, Box 1 BBB, …” and find cards easy peasy. There’s also a friends feature so I can see what others have locally. We borrow cards from each other quite a bit.

It’s been a fun project to build. I trained one model to find a card in the camera frame and another to identify it. Still iterating a lot. One epoch on my Mac M4 takes about 2 hours, and I’m still seeing improvements past epoch 10. Even now, it can find and identify a card more often than not, even without the OCR bits. Both models are under 20MB, run directly in the camera frame, and are fast enough to identify a card as I slide it into view.

I started with Android since that’s what I have, and I’ve shared the app store testing link with my local group for testing. The app is built in React Native, and I’m hoping to get an iPhone version out soon since there are a bunch of iPhone peeps. A couple of the players also got me into MTG, so now I’ve got a pile of Turtles cards too. I’ll be training an MTG model next. I don’t think it’ll be too bad since I can reuse most of the same approach.

I’ve been thinking, for a while now, how I could merge a LLM and an Expert System. What I wanted was the ease of use of an LLM and the rules based processing of an Expert System. Over the past couple of weeks, I built what I thought was a unique way of merging the two. I choose to use auto insurance as an example because of my past history in the industry, but I feel as though it would be applicable in other industries. It’s still very rough around the edges, but if you are interested you can try it out at https://mktbx.com/#tryout I’d appreciate any feedback and your thoughts.

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The last app, the only one that was deployed anywhere, is https://catchingkillers.com This app is a simple murder mystery game where the witnesses and the killer are ChatGPT bots. The first two stories are complete and active, the third is not complete yet. The first story of the working two is taken from another murder mystery group game https://www.whodunitmysteries.com/sour.html. The second story was highly influenced by ChatGPT.

It's a bit rough because I didn't spend too much time on it, but if anyone does signup to play, I'd love to hear feedback.

I purchased the device because I was a bit worried about radon and other garbage that I might be breathing while working in my basement office. Radon and other data points were not a problem. Turns out C02 was more my problem. It's pretty surprising how quickly that number rises with a closed door. I believe I can attribute the tiredness with the C02 levels. Having history correlates with when I'm in the basement office, and opening a window, it's a walkout basement and I have windows, decreases C02 stat pretty quickly.

Overall I'm happy with my purchase, and I'm considering buying another one for the ground level of the house.

https://cruisedirector.io/ I have it running on some of my sites. It continues to run but I have no customers, and I haven't tried to sell it as a service. Tracks user actions inside an application. Every click is tracked so you can make rules based on any user clicks and show prompts made with a graphical editor. For example: Someone is button smashing, you can ask them for feedback. Popup a message on first login in the past month... Really lots of fun stuff.

https://ezdataloader.com/ I recompiled some old c# code from about 10 years ago, and with a few tweeks the backend now can run in mac, windows, or linux. Pretty sweet, other than the interface. I used electron for an interface and got it working a bit. But, I haven't put too much time into this one either. I'm tempted to scrap the downloadable executable, and turn it into a saas app. Might be a bit easier for customers I'm targeting. I've been pretty busy at my day job though, and haven't had time for this in the past year or so.