Are there any details on how this works? Based on what is available in the linked article, it looks like they have an LLM+RAG and are trying to pass off the responses as speech from the user. Done with full transparency, and right protections, this could be useful, but calling it BCI, and overselling it as user's voice (especially given voice cloning is also being done) can be misrepresenting it.
Agreed - I don't want to come across as negative, but this is certainly in the "extraordinary claims" category for me right now. If this works, it's obviously huge, but I really want to see third party validation before I can let go of my skepticism.
I would be very curious to hear about interviews with the patients (conducted through their current means of communication, eg: eye gaze interfaces). Are they finding that the speech generated by the system reflects their intentions accurately?
EDIT: the EEG peripheral they are using is 4 channels / 250 Hz sample rate. I freely admit I have little knowledge of neuroscience and happily defer to the experts, but that really doesn't seem like a lot of data to be able to infer speech intentions.
If that's all they were doing - showing when the patient wanted to speak - that would be fine. Presenting speech as attributable to that patient, though? That feels irresponsible without solid evidence, or at least informing the families of the risk that the interface may be just totally hallucinating. Imagine someone talking to an LLM they think is their loved one, all while that person has to watch.
You’ll get no argument from me there. The whole LLM part seems like a gimmick unless it’s doing error correction on a messy data stream like a drunk person fat fingering in a question to ChatGPT except with an EEG. It might be a really fancy autocorrect.
I’m just saying that EEG data is so unreliable and requires so much calibration/training per person that reliably isolating speech in paralyzed patient would be a significant development.
Definitely, seems like the wrong tool even, or not the right first one, surely you need some sort of big classifier for EEG patterns to words or thoughts/topics; then if used an LLM it would be 'clean up this nonsense into coherent sentences keeping the spirit of the ideas or topics that are mentioned'?
