@crazydave

I decided to implement the change where the model outputs a number between 0 and 1 to represent somewhere within the high/low range of numbers it can currently guess between, and also added a new input to the neural network telling it the number of guesses so far. Both of these changes drastically improved the model and now it averages around 9 guesses to find the number, which is an amazing result. I only got to this after playing around with trying to change the fitness function again to not much success, but I am glad this idea worked. Next time I work on it I will add a user interface on an online website with the final trained model so people can try it out.

After training it overnight it was able to solve the game in an average of 35 attempts, however as I cut it off after 50 I reckon the actual attempts would be much higher. Due to this lack of performance, I have decided to try and improve the fitness function so that it trains more effectively. I spent many hours trying to modify the fitness function and test it hoping that it would lead to a better solve rate but so far I am without success. It would keep repeatedly guessing the same number so I added a penalty if it guesses the same number as the round before. It would then alternate between guessing two numbers, so I tried to increase the reward if it got a correct solve. After those changes and a few other experiments, I was still unable to get it to train properly and seems to still perform poorly with the new fitness function after 1000 generations of training. The graph below shows the fitness of the best model per generation, and you can see quick initial improvement before it stagnates for the rest of the training time. I am considering changing the output from being a number between 1 and 1000 to being a number within the high/low range, where 0 represents the current low and 1 represents the current high, and hopefully after training it would learn to guess around 0.5 each time. Another strategy I could implement would be to give the network more information, such as guesses from even more rounds, round number, or width of the search interval and maybe increase the number of hidden layers and/or neurons in those hidden layers.

I am trying to make an evolutionary neural network which plays a number guessing game where it has to try and guess a random number between 1 and 1000 in as little attempts as possible, and I am hoping that it will learn binary search from scratch, which would be cool. The first version that I made had a very low solve rate as I hadn’t done the fitness function very well, but this version I have changed the fitness function and a 50 generation quick run was showing good results, so I am going to run it with 10000 generations and then go to sleep, and hopefully when I wake up it will be done fingers crossed. Let me know if you have any other interesting number games/number related things I could try and train it to do, any ideas are welcome!

I first followed the guide to create the nasa daily astronomy site but I didn’t do the part for CSS as I knew I wanted to take the site in a completely different direction. I wanted to make a custom new tab page like the chrome extensions I used to use in primary school so I first added a basic searcher that can search on google. I then added slash commands that let you search on YouTube, duckduckgo, GitHub, and chatgpt and made it so the icon updates alongside it. I also added unsplash images for the background using the Unsplash image api. I then added a weather widget by first getting the user’s location and then using the free open-meteo api to get the weather at that location. I wanted to show an icon for the weather but the API, to my knowledge, doesn’t support return images but instead returns weather codes that correspond to the descriptions, like partly cloudy, and the icons that you normally see on weather apps, so I got chatgpt to code an array that maps the weather codes to the description and icon. I then added hints for the slash commands below the searchbar.

Added a longer delay before it times out so hopefully that fixes the errors that have been stopping it from getting approved.

I managed to set up autorouting and got it to route all of the components except for 9 of the connections, so I did those manually. I then added 3D footprints to all of the components so I could render the nice 3D model you can see below. After that I began working on the 3D model for the case, however after making the base of it and extruding the walls up, I made the plate using the plate generator website, but once I imported it I wasn’t sure how to do the extrusion step they do in the tutorial on it, let me know if you know how to do that.

I made the PCB layout and I now have to do the routing between all of the components, but I am going to try and install an autorouting plugin to do that for me.

Made the schematic for my 3x4 button macropad and added led’s to go under the switches as well as a rotary encoder. I was planning on doing a 4x4 macropad with oled and rotary encoder but the MCU doesn’t have enough pins for that so I decided to go with 3x4 + rotary encoder + LEDs. I also assigned the footprints for the PCB but I haven’t started laying out the PCB yet. I am not sure where to place the diodes or LED’s so if you know please let me know in the comments (I want one LED under each switch and need the diodes for the matrix layout).

Made the pcb in kicad for the tutorial 3 key macropad and also made the case in fusion 360, but I must have done one of the dimensions wrong as the cutout doesn’t line up with the case size, so I will have to restart that next time I work on it. I am also planning on making a 3x3 or 4x4 macropad but I want to do the tutorial first to get a feel for working in kicad and fusion before I do a more complex version.

I switched to using my own url shortener as the other api’s weren’t working with slack (so my ship got rejected, should be fixed now), it kept on timing out on the response so it would just send an error message. I used the url shortening from my other projecting and just wrote a small bit of code to have an api for short url creation. I then set it up with nest again and it took forever to get the Nest server working as for some reason the internet connection on the nest would just randomly stop working so the bot wouldn’t work either.

Added bot commands to create QR codes as well as url shortening. I was trying to create the QR generation myself using an npm package but I couldn’t figure out how to send an image from a “data:” url so I instead switched to a free API, and I did the same for the url shortening. I also tried to host it using vercel but it didn’t work so I instead switched to using the hack club nest. Feel free to try it out with this on the slack: /url-tools-help.

added QR code generation as well as redirects to the qr code’s destination, and GitHub oauth for logins using supabase

Set up the project and made some simple redirects, can’t really show in a photo as its just a link on my site redirect to something else, so here’s a photo of some of the code (it’s super basic so far).

finished the ui so it doesn’t suck

added animation to the vector transformations so now I just need to improve the ui and then the MVP will be complete, also added an FPS counter to see how it performs when I change the size of the grid.

just a quick one, made it so that the matrix transform also applies to the coordinate grid by making the line coordinates be based off of the transformed world coordinates

I started making a website that will allow people to visualise how matrix transformations change how the 2d grid looks. I have so far set up the project, made a 2d grid using html canvas, and added an input where the user can type in a transformation matrix and it will apply it to the red vector. Next time I work on it I will make the matrix transformation apply to the entire grid. For some reason the grid doesn’t display properly on the vercel deployment so I will try to fix that next time. Let me know if you have any suggestions.