The whole field is propelled by deliberate misinformation and hype used to farm grants.
but maybe the sort of sensory bandwidth like required to operate say a helicopter is just a completely other order of magnitude to think that you could do it through the same channel. What's the main blockers or bottlenecks in this space?
I guess you could argue that people writing the grants should perform more due diligence, but at the same time I believe we should be able to trust scientists to act ethically and honestly in the same way we trust doctors.
But I didn't know this--what you said about the difficulty of signal collection, and rejection--and really value that alternative perspective to the one I've seen in the press about using AI, which you think is overblown. Thank you! :)
I don't disagree with that line of reasoning in general - moonshot projects have led to amazing discoveries in the past and should definitely be funded.
In this particular case, though, there are both very, very strong arguments to suggest that we reached the peak of what the current paradigm can achieve back in the late 00's - as well as very, very strong (financial and cultural) pressure to ensure all new research projects in the field adhere to the current paradigm.
>I get your frustration at the perceived support for a research direction you view as wrong, but I think this is normal, especially in emerging tech.
It's so, so much deeper than that. The researchers in the area know full well what they're doing is complete bullshit, but toe the line anyway because that's where the funding comes from.
It's not just a wrong research direction but a soft and invisible form of academic fraud. This is not normal (or at least shouldn't be normal), and we should not be feeding the beast.
We could possibly have much, much stronger BCI tech today if the incumbent culture weren't actively impeding innovation.
That's not just fraud, I think...but it's like wasted scientific capacity. You know? They're researchers, they could be working to build something, but instead they're taking money on an approach that can't work. That's sick. Feels bad....
So what do you think's the solution? Like if you could take 10 million dollars to do your own lab with BCI tech what direction would you go in? ;p ;) xx
The honest truth is I have no idea exactly how to solve the problem. I'm a data/algorithms guy, and our skills are completely inapplicable to this field at this time. My original thesis suggested we "somehow" work out how to train humans to produce signals that can be more easily distinguished by a BCI, but I had no idea where to even begin with such a system.
A mainstream BCI will require a better understanding both how the brain works and what materials can survive inside and coexist with the human body. Or perhaps a new sensor method will come along that greatly increases the quality of the data we have and render both of those things obsolete.
I think the best way of spending my 10 million would involve simply giving it to smart, frugal people and walking away without asking any questions. I mean that genuinely.
Sticking to BCI specifically and not other forms for biofeedback, most of those demos you see come from people with invasive, penetrative electrode arrays such as the Utah array. In some people, these sensors can enable a high level of control and performance (not Xbox controller level, but still Atari controller level which would be incredibly useful for people with Motor Neurone Disease). Unfortunately the body rejects them after a few months and they're back to square one.
To be honest with you, I don't think that the problem's intractable. Perhaps a clever materials engineer could develop a coating for the electrode arrays that the body accepts long-term and allows the user to train for years rather than months. Perhaps we could develop a new form of sensor altogether.
I don't know specifically what the answer is, but it won't come from the current paradigm of "turn garbage data into non-garbage output through the power of Machine Learning somehow" that we've been stuck in for the better part of two decades. And unfortunately, projects adhering to that paradigm is where all of the funding (and people) goes to.
Yeah, i was pretty turned off by this in the lab i've worked at/contracted for.
A lot of support for this kind of stuff wrt EEF neurofeedback while ignoring the physics of what could be done with the raw data (if the PI actually understands or had a E&M class at least). Ppl in charge of getting the grants don't really care about the fact we do not gain any insight into whats going on when we use black box systems… oh well.
I'd be happy to play around with biosemi 128 electrode cap+array + dsp + beamformers[0] and openemu[1] for two decades, deff not gonna happen in academia though.
For reference, the machine I used employed a bike game that supported movement across the screen. I eventually could make the bike go faster as well as up and down, nearly on command. It focused on alpha, beta, and theta waves measured by diodes stuck to your scalp. Not sure if that narrows that down, but I'm curious to know your thoughts.
Claim to use light for imaging https://youtu.be/awADEuv5vWY
There’s also the company Kernel
Both companies have pretty successful founders