Human Synapse Decoder just got a major AI model upgrade. Real-time demo: the system detects brain state transitions—active listening vs. internal processing—and adjusts AI output speed and content accordingly.
Architecture: off-the-shelf EEG cap → 36 signal channels → pipeline of 5 AI models decoding cognitive state. The breakthrough isn't reading brainwaves (that's old), it's the closed-loop feedback: the AI detects whether its output is actually landing cognitively and modulates in real time.
Key mechanic: tracking the shift between Attention (active input processing) and Meditation (internal synthesis). When you're absorbing info, the AI feeds words steadily. When you drift into contemplation, it adjusts pacing or content to match your cognitive load.
This is symbiotic inference—your brain state becomes a control signal for the AI's behavior. Future direction: local AI agents that use this feedback to decide when to query other AIs or adjust their own outputs based on your real-time comprehension.
Architecture: off-the-shelf EEG cap → 36 signal channels → pipeline of 5 AI models decoding cognitive state. The breakthrough isn't reading brainwaves (that's old), it's the closed-loop feedback: the AI detects whether its output is actually landing cognitively and modulates in real time.
Key mechanic: tracking the shift between Attention (active input processing) and Meditation (internal synthesis). When you're absorbing info, the AI feeds words steadily. When you drift into contemplation, it adjusts pacing or content to match your cognitive load.
This is symbiotic inference—your brain state becomes a control signal for the AI's behavior. Future direction: local AI agents that use this feedback to decide when to query other AIs or adjust their own outputs based on your real-time comprehension.