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Rohan Paul@rohanpaul_ai
this is just so next level for personalized AI.
arousal signals scored by a simple embedding plus k-NN reward. RL with Neural Feedback (RLNF), reads a viewer’s arousal signals directly from the brain, while they look at a generated image and uses them as the RL reward.
this direction looks so natural now. Human preference anyway lives in the brain, RLHF routed it through a click, and RLNF routes it from brain signals straight into the reward.
All that said, I'm generally excited about this new paradigm.
It gives us a whole new axis to scale AI models - towards personalized responses.
Which is more impactful to large scale adoption than just intelligence.
If AI can understand you, it can make things more beautiful for you. We are hoping to help make a more beautiful world for everyone.
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BCI is moving away from clinical applications to consumer uses, and applications like these will become more abundant w time.
Robust and dependable regulation on user safety and standards of use on neural data can do great work in setting such standards for safety that allow users to trust such systems.
If brain signals can be used to understand private thoughts and personal preferences, users will want the service providers to be more trustable, and sufficient regulation to enforce the same.
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