Every 6-12 months, someone will write a puff piece about their research in order to get grant money[1]/street cred. And every time, HN responds as if it's sci-fi tech from the future and I shit on everybody's dreams.
So here we go:
At a glance, nothing about this system in particular is new. It seems to solve the same problems as older invasive arrays from 15 years ago, with the same deal-breaking flaw still unfixed (namely, the body rejecting the implant over time).
He had OK-ish performance in a single patient (one character per minute on a good day), but single-patient performance is misleading as it's very common for a system to work with one "golden" patient but not others. Interestingly, no real research has been done (at least, none as of 4 years ago) to look into why this is the case - most "breakthroughs" are people throwing machine-learning spaghetti at the wall to cover up deliberately flawed benchmarking. (To be fair, this is more of a comment on the field as a whole than this particular trial. His results seem honest and humble.)
The field is going nowhere, and this article is yet another shining example of this. Nothing will ever be achieved until we abandon the current paradigm and actually learn more about the underlying neurophysiology (or possibly create batshit-insane sensors).
[1] They actually explicitly mention this in the article this time, which is pretty bold:
>Chaudhary’s foundation is seeking funding to give similar implants to several more people with ALS. He estimates the system would cost close to $500,000 over the first 2 years.
I'm a comp-sci student too, and considering what possibilities there are for studying BCI, machine intelligence and the brain. But I think that maybe, having approached it from a more biologically oriented angle would have been better. After having read "On intelligence" I'm just more aware how disconnected our modelling of intelligence and the brain/BCI is. On one hand, there's just "throw more computing power at it", and the other, there's cutting a fruit fly's brain into slices and building a special machine just to do so, while afterwards scanning the resulting pathways [0]. We can't even understand brains way less complex than our own, so I fear that a bottom up approach is way beyond my lifetime. I remember a Danish neuroscientist once said, that there's a higher chance to understand every star in the universe, before we understand the inner workings of the human brain.
Do you mind me asking, what did you do instead?
[0] https://ai.googleblog.com/2019/08/an-interactive-automated-3...
I think what we should be doing is something different to what we are now. The current "throw machine learning at things and expect it to magically work" paradigm has achieved nothing more than bullshit non-results for two decades straight, and unfortunately this is where a disproportionate amount of the grant money/researcher's eyeballs go.
BCI research, at least on the algorithms side, is basically a "bullshit job" where you do something you know will fail, it fails, and then you scream from the rooftops how successful you were until grant money gets thrown at you.
>Do you mind me asking, what did you do instead?
I got a real job as an SWE. It was at a really good company (Blackmagic Design in Port Melbourne) with a fantastic, highly politically incorrect culture. Quit that job just before the pandemic to run my own business and be a dad, but still get nostalgic about it to this day.
Question, if you've got the bandwidth - I've got a cochlear implant which feels like it's at least a little tangential in terms of hooking into the electrodes and auditory nerves ... been wearing this wonderful thing for 30 years, and I'm curious as to why the body would reject his implant versus mine (and other folks who wear CI's)?
There are non-penetrating arrays that sit just above the brain (avoiding this problem to a large degree), but they don't have anywhere near the precision of the penetrating sensors.
https://amp.theguardian.com/science/2010/feb/03/vegetative-s...
What do you think about the few groups actually doing electrode design (i.e. there was a UC Berkeley/Lawrence Livermore group looking at electrode designs)?
Vs. I think most of the innovations in BCI engineering happen to be in the commercial sector (i.e. deep brain stimulation electrodes from Boston Sci, Medtronic, Abbott, the arrays from Black Rock in Utah, Neuralynx, etc).
The study comes in the context of past findings of serious misconduct against Birbaumer and Chaudhary. The findings concerned the data and analysis in two previous papers published in PLoS Biology. The two articles, subsequently retracted, also concerned the use of brain activity to decode the thoughts of completely locked-in patients. The German research agency, Deutsche Forschungsgemeinschaft (DFG) found that the scientists failed to show complete analysis of their data and patient examinations in these previous studies and made false statements. The allegations do not relate to the findings of the current research which involved different methodology, supervision and analysis. In a statement to Technology Networks, Birbaumer said that the new study “shows that all accusations are wrong” and suggested that additional forthcoming legal developments would further exonerate his and Chaudhary’s prior research.
This article seems to be actually, entirely, and directly based on brain activity.
Or are we seeing reports of incremental improvements to technologies for communicating with locked-in people.
I've seen a lot of the latter. I don't think I've ever seen the former.
That sentence speaks volumes to me.
It's a good thing he wanted a band with a nice short name. Imagine if he was a fan of these guys https://www.metal-archives.com/bands/Paracoccidioidomicosisp...
One of the other sentences he made out was "I love my cool son," which hit particularly close to home given I'm the same age as well. Oy.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6914248/
(Elon Musk is author of this publication)
https://pubmed.ncbi.nlm.nih.gov/34140486/
https://pubmed.ncbi.nlm.nih.gov/33955717/
https://pubmed.ncbi.nlm.nih.gov/33894832/
https://pubmed.ncbi.nlm.nih.gov/33784612/
https://pubmed.ncbi.nlm.nih.gov/33236720/
https://en.wikipedia.org/wiki/The_Diving_Bell_and_the_Butter...
https://agenda.hep.wisc.edu/event/792/contributions/18594/at...
With accuracy on par or better than described:
> He eventually explained to the team that he modulated the tone by trying to move his eyes. But he did not always succeed. Only on 107 of 135 days reported in the study could he match a series of target tones with 80% accuracy, and only on 44 of those 107 could he produce an intelligible sentence.
In fact, some of these successful efforts were done back in the early 2000s.
From the article:
> Researchers inserted two square electrode arrays, 3.2 millimeters wide, into a part of the brain that controls movement. When they asked the man to try to move his hands, feet, head, and eyes, the neural signals weren’t consistent enough to answer yes-or-no questions, says Ujwal Chaudhary, a biomedical engineer and neurotechnologist at the German nonprofit ALS Voice.
The speed and accuracy does take a hit using external nodes, but brain implants are frankly dangerous. They come with serious risks.
There’s also risks associated with the surgery (that’ll be much higher than 1/15,000; you’re probably talking at least 1/1000 just for risk of initial surgery).
Further, no implants last forever. They develop scar tissue around the implant. So you’ll have multiple surgeries if you survive years.
Technology can mitigate much of that risk, but we are pretty far away from removing risk. We also will need multiple major independent breakthroughs.
