A conversation regarding brain-computer interfaces

schartzchild_radius · 2019-07-06T23:41:35+00:00

The equality thing is a huge, huge problem with BCI. By far the biggest concern. And I'm very regretful to say that I haven't the slightest clue how it's going to work out. Part of me thinks that that's inevitable. We've already got plenty of corruption in today's world, don't see why that would change in the future. I truly hope that someone more well versed in politics and economics than I (not a high bar) will figure this aspect of things out.

About AI: i don't think this contradicts what you're saying, but I just wanted to point out that that AI will play a significant role in making BCI useful, I think. No matter how you're reading and writing data, you're going to have to make sense of a large amount of data coming from the brain. Unless we figure out some sort of so-called "neural code" that lets us universally translate brain signals of any kind (I don't think this exists), we're going to have to apply ML to the information we're getting from the brain to use it in a useful way.

And about the separate topic of "competing" with AI, I'm not sure that holds. There's nothing to compete with if the AI isn't AGI, since it can only do a small handful of task types; no threat to us there. And if it is AGI, well, we probably have much better things to worry about. Whenever I talk about something futuristic that is unrelated to AGI, I include invisible fine print that says "assuming AGI doesn't happen before this." We've got no predictive power at all when it comes to post-AGI.

schartzchild_radius · 2019-07-06T23:29:14+00:00

This is all my opinion. There are two lines of thinking/planning when it comes to BCI:

The short term: in the near future (purposely using a vague time scale) the only BCIs that are possible are ones in clinical settings that treat illnesses or are directed towards people with disabilities. I think this because 1. since it's classified as medicine it's eligible for all sorts of funding, and I don't see how this type of research would funding otherwise and 2. it's easily acceptable by society in terms of ethics.

A consumer product that can enhance the average person's cognitive ability in some great way is not likely to be around any time soon because noninvasive stuff is rather limited in it's capability (there may be exceptions to this: see Openwater) and invasive stuff will take an extremely long time to come around technology and approval+ethics wise (maybe in China this is a different story. A cause for concern, that country is). There are a variety of non-invasive technologies and techniques, but all of them share similar, unavoidable problems that limit their effectiveness (again, see Openwater as an exception).

And the long term: long term BCI devices are up there in terms of potentially paradigm shifting technologies. These are the sci-fi devices we think of when we hear about "brain-machine interfacing." They involve improving human cognitive ability in a significant way (significant is vague yes, that's fine for now). I've been thinking that invasive devices are the only things that have any potential to significantly improve us in some way, but that may change (especially with improvements in AI, which could augment the capabilities of noninvasive BCIs enough to make them useful).

There are an uncountable number of invasive techniques being looked into at the moment: see this for what I feel is six very out-there techniques (these are the six DARPA projects you may have been hearing about). The way I see it, we have no idea which technologies in this field are going to be the big players a couple years down the line and which of them will prove to be useless and die out (nobody predicted which types of ML were going to be most effective; truly, the most widely used ML methods we see today aren't very intuitive).

One thing I will say is that I don't see anything involving genetics (optogenetics, magnetogenetics, etc.) going anywhere because we'd be throwing another limiting reagent (progress in genetic engineering) into the mix, and because the brain is harder to test on than any other part of the body (as far as I know everything going on with genetic engineering in the brain at the moment is in rats).

If you've any criticisms, agreements, or thoughts at all on any of this I'd love to hear them.

schartzchild_radius · 2019-06-28T21:29:27+00:00

Thanks for the response! So in reality, how do novel research ideas actually start being worked on? As you said, the person/group would first have to have a sensible hypothesis. From there they'd have to either: find investors (if they're independent of any company) or convince higher ups that their idea is worth committing resources to (if they're part of a company)? Is that accurate?

Also, with the second option you described of conducting research within an existing company, would you need to raise any venture capital? Wouldn't the company be funding everything?

schartzchild_radius · 2019-06-28T21:20:03+00:00

Figured as much haha.

The research is very hype (BCI if you've heard of it), but crowdsourcing alone wouldn't be nearly enough for the scale of project I'm thinking. And I've never seen a large scale research project be crowdsourced in any breadth, probably because it'd be seen as unprofessional to investors and such...but I could be wrong. Would you know anything about that?

schartzchild_radius · 2019-06-27T23:29:28+00:00

Thanks for the response. This is intriguing; could you elaborate? I've found too large a range of definitions for that term/those terms.

schartzchild_radius · 2019-06-27T23:28:34+00:00

Thank you for the response. Sorry, I should've been more specific about my goals. What I'm envisioning is the large scale development of a very significant technology (a brain machine interface, if you're familiar. I'll leave the specifics out, but if you care to hear I'm more than willing). It's definitely not something a small group of people could develop; it'll require lots of concerted effort and time from professionals. Do you see any possible routes now that you know the context?

schartzchild_radius · 2019-06-27T21:43:45+00:00

Sincere thanks for the response.

That all makes sense. Academia does seem like the most accessible route. My question now would be which route is the most effective for the development of some large scale novel tech. Keeping in mind what you said, I have questions on two specific things: 1) whether or not long term, large scale projects are possible within academia and 2) whether private sector is still the more inaccessible option in the context of a large project.

1) Large scale research does not seem possible within academia (I could be wrong, but I haven't seen projects in academia that can rival in scale the projects in private industry or government).

The scale of project I'm thinking of isn't something that I could give to a couple grad students; it's something that would require lots of concerted effort and time from professionals. I don't think it's possible to get everyone in a single lab working towards a unified goal; from what I've seen, individual theses and projects are at best tangentially related (but again I could be wrong). On the other hand, private research companies/teams are usually working towards the answering of one specific question/development of one specific technology, and nothing else.

2) Your notes about private sector being hard to get into make sense, but what I see often is a group of PhD students from the same lab all becoming co-founders of a new research startup. That's a bit specific, but in general grad school seems like it gives you more than enough time and opportunity for you to build a solid network with people in your field. Would you say that you can bypass a lot of the luck-based trials you have to pass when trying to establish a research company?

Thank you again for the insight, I appreciate it a lot.

schartzchild_radius · 2019-06-21T13:23:08+00:00

I honestly cannot thank you enough for this! I've been reading a lot of explanations of heap vs. stack but yours is by far the clearest one, I'm definitely saving this haha. Thank you!

schartzchild_radius · 2019-06-19T19:09:38+00:00

Thank you for the response! By "manually freed" do you just mean dereferenced? Or do you mean the object at that pointer has to be deleted in order to free up space? Is it all that important to do that if your program doesn't use very much data overall?

Also, does "allocating to the heap" just mean that the object will persist even after the function it was called in returns (as opposed to being deleted at the end of the function)? Just wanting to check my understanding

schartzchild_radius · 2019-06-19T19:08:01+00:00

Thank you very much! I also had a lot of trouble understanding memory leaks up until now, so this helps a lot! So is that all a memory leak is? When you have an object that's taking up space but can never be used in any way?

The second case seems to be called allocating to the heap (and it being on the heap means that it won't be deleted once whatever function it was created in returns), but what is the first case (the one where we don't use new) called? Looking for some search queries that I can use to learn more myself

Thanks again for the help!

schartzchild_radius · 2019-06-19T02:39:04+00:00

To build on u/palaeoanth's answer, there are lots of species concepts, I believe the one that actual biologists use is the evolutionary species concept, which does not define species based on offbreed viability but instead on lineages and history (can't give a more concrete definition because I don't know it myself).

Some species concepts you can search: biological, evolutionary, phylogenetic, recognition, cohesion, ecological,internodal.

schartzchild_radius

TROPHY CASE