Thank you. It's always nice to know someone is reading. I haven't really taken the time to write โmanuallyโ in some time, lol. With all the side notes and projects, it's always nice to ask an agent to summarize my notes, but I feel like people appreciate something written.
It's funny you say that. I know this differs a bit, but I was just thinking about this the other day. I had a realization in a conversation with a friend. We got on the topic of Star Wars, and for a slight moment they expressed how much they loved C-3PO and R2-D2. Then we got on the topic of AI later, and there was such a negative pushback from them on the subject. On one hand, I saw their fascination and love for characters that embodied, in a lot of ways, exactly what they hated.
It made me think when you said, โlook at the painting the math was intended to create in the first place.โ In a nutshell, that seems like how disconnected the painting can be sometimes, even in the simplest forms.
I just think it's good to zoom out when we tinker with these models, because we're so zoomed in while we work. At least for myself, that's how I feel. I'm so concentrated on what levers to pull and which ones I shouldn't.
What started this idea to begin writing as well was something that happened about a year ago. I was making a joke to my cousin, who had just bought a Honda from Japan. He was telling me about the mods and the scene, how everyone is invested in making changes to really make the car theirs. My joke was something like, โYou guys are going to be the ones making robots like Chappie.โ
Fast forward to now: people are 3D-printing small robots and hooking them up with their own small models. I don't think it's so far off from us having DIY guides for humanoid robots that are fully 3D-printed at home. Maybe we all should start hoarding servo motors. They might become like GPUs one day, lol.
I think itโs fun to sometimes get lost in training, be really immersed in a project, and be proud of the work. But we also canโt plant too many flags of victory when the board is still changing. If we can all somewhat try to predict where this ends up, it seems like finding the proper experience-based datasets will be our next journey.
I look at it as another version of a large movie file being compressed into an MP4. I think quantization will keep getting better, and training methods will improve alongside it. Somewhere in the middle, they will meet for the purpose of fitting into a portable version that becomes the mind of our robots.
Just like AI 2027 (https://ai-2027.com/), I think itโs fun to plot out predictions and see how many darts land later on.