TLDR: I took Meta’s TRIBE v2 brain model (predicts fMRI-style brain activity from video/audio/text), built a real-time pipeline around it, and gave it a voice and a 3D face. The result is a live AI character that watches YouTube (like Mr. Beast) and reacts based on predicted brain activity. Built it in days with Codex. It is not reading real brains, but the signal is real, and the whole thing working is kind of insane. Disclosure: this is my build, not a product launch, no waitlist, no subscribe pitch. I just want to show what I made because it genuinely blew my mind that this is possible now. Meta released TRIBE v2, which predicts fMRI-style brain activity from video, audio, and text. That alone is already insane research. But it is basically a research model. You do not just point it at YouTube and suddenly have a little AI brain watching and reacting to things. So I tried to build that. And somehow it actually works. I wired a real-time pipeline around TRIBE v2 where the system watches the video as it plays, processes the predicted brain-response stream, and uses that as a core signal for live AI commentary. Then it turns that into a voiced, animated 3D character that can react to the clip, make jokes, pause, comment on specific moments, and explain why something seems attention-grabbing or weird. The part that is blowing my mind is that it does not feel like a normal LLM reaction bot. It is not just reading a transcript and making stuff up. The commentary is tied to the brain model output, so there is this extra signal underneath it. Predicted cortical response becomes part of the character’s perception. The rough architecture: TRIBE v2 processes the video/audio/text stream and produces predicted cortical activity over time A real-time reaction layer turns that signal into immediate commentary A deeper context layer keeps track of what is happening and why it matters A humor/personality layer makes it feel like a character, not a dashboard A voice + 3D avatar layer gives the brain a face that can talk and react That last part is important. A stream of neural prediction data is cool if you are already into the research, but for normal people it is abstract. Giving it a rough, funny 3D face suddenly makes it understandable. You are watching a character react, but under the hood the reaction is being shaped by a brain-prediction model. I know that sounds ridiculous. That is why I am excited. I can take a published brain model, wire it into a real-time media system with Codex, give it a voice and a face, and suddenly I have this live character reacting to the internet from predicted neural activity. In a couple of days. The thing that still trips me out is that it really does feel like it is watching the content. You can see it process a viral clip, react to specific moments, pause, and explain why it thinks something is attention-grabbing based on the predicted brain-response signal. To be clear: I am not claiming this is reading anyone’s actual brain. It is predicted average-subject cortical activity, used as a signal layer. Interesting signal, not magic. But it is a very real signal, and the whole thing working together is honestly kind of insane to me. Being able to turn a published brain model into a live-reacting 3D character feels like a glimpse of a completely new creative format. The question I keep coming back to: What happens when we get enough brain data to actually hook up AI and simulate our real brains? Are we almost already there? Curious how people here read it, especially if anyone else has been building on top of TRIBE v2. Demo video: https://youtu.be/I4oGPLMVoC0 submitted by /u/MerlinMimer
Originally posted by u/MerlinMimer on r/ArtificialInteligence