 There we go. Cool. You said questions that I had. Yeah, what questions are bubbling up in your head as you start to engage in OGM conversations? Well, I would say, because I haven't quite finished the video of the Better Verse yet, but I was mostly halfway through that. So that was interesting. But it's definitely like some of the topics brought up are really good questions, less and more. Sometimes less is more kind of thing, as well as like I just got this general view of sense making. And I'm thinking of, as I mentioned before, the cross-cultural things that are happening when you are mixing international boundaries in the digital state and how that plays into it. So that's kind of like my, probably my first lingering question is thinking about what does that mean exactly? What are the implications of this and how that can be applied to creating safer spaces online? Because it's a challenge and it's like, there's not a precedent and as much, there's not so much like these, because I think in the call, you're talking about standards for the Metaverse or protocols or whatever, but it's like, I couldn't begin to guess what that might look like. And so I'm always curious kind of the trains of thoughts that people are having regarding that. Cool. So there's a piece of it that we haven't gotten to yet that's really important for you just mentioned, which is sort of cross-cultural communications, cross-cultural sense making. How do we find our way to even understanding what the other person is saying properly? Right? Because sometimes we mean very different things by the same words. Sometimes somebody does something that rubs us the wrong way. So we dismiss what they say, except they're being really smart. It's just that their culture is different or their graph or something like that. I mean, there's lots of different reasons why these things fail. And again, I don't think the people we're convening are that different that we're hitting these things and we're not that geographically dispersed that we're hitting these things yet, but they're really important. Yeah, because even in the same language, there's lots of cultural difference and slang terminology and style of communications. So it's boiled down to kind of this like semantics a bit potentially in the use and interchange of language. And I know like translational tools are helping with that. And they've gotten better even in a way that they translate to like what it's kind of supposed to be saying more so in that culture as opposed to like word for word. So I'm sure those kinds of things are gonna continue to alleviate some of that. But from a social dynamic, I never studied sociology. I don't think about that. I'm not so sure. I just think in terms of a systems level and I would like to get to know more about the sociological aspects of things. Yeah, yeah. There's also other layers of this, which is like the word liberty right now is a loaded word. And politically it's being overloaded and used as a sword in many ways. So when you start to talk about liberty or freedom in certain settings, it can really cause a lot of damage. And so then the question is, how do you make more safety in the situation? How do you diffuse the pressure? How do you, what do you do? But just trying to interpret what people mean by certain things unpack sometimes into their whole worldview, right? So one of the people, one of the sort of geekier people in our community, Marc-Antoine Perron has a project called Hyperknowledge where he's trying to go through the actual sort of semantics of arguments and how points are made, how to represent all the logic of them and then how to represent them engaged in conversation, which is really, really complicated. But it's lovely and he's pretty far down that path. He's a regular on the Monday feature he's brain calls if you're interested there. Yeah, it was really cool how you're just kind of whipping around that UI and just like dragging and showing all the pieces of how it connected to stuff. Like I thought that was really cool. It's really, it's just this very interesting thing because people either like get like totally get it and are on board and are following or they just fall off the back of the truck. They're like, nope, nope, brain is not, brain is not figuring this out. This isn't working for me. And it's like sort of bimodal, like there's nothing I can sort of do to get everybody over on board to, yep, this makes a lot of sense. So I'm really trying to puzzle through how to do this. And one of the things that we've done in Free Jerry's brain is, Pete Kaminsky wrote and Bentley Davis wrote some code separately, but similarly to basically export a brain into a website, a simple website. And Pete mostly did this for Mark Trexler who is a brain user who does a bunch of stuff around climate change and has a very, very deep brain database of climate change stuff, but realizes that a lot of the people he's trying to sell services to can't make head and or tails out of the brain interface. So exporting the stuff to simple lists on webpages seems to solve some of the problem, but we're not really sure. You know, and we don't have like a proof point or I don't know that we've solved that problem. And a piece of what we're trying to do is how to see the same sets of information in very different ways. I had a call on Sunday with a Hungarian fellow named Zolt, Z-S-O-L-T, who I learned about because Pete and others were mentioning him on the Mattermost channels. And Zolt has taken obsidian. Are you familiar with obsidian? So he's taken obsidian in a plug-ins called Excalidraw, which is a simple drawing program. And he's extended, far as I know, he's extended the Excalidraw plug-in and made it so that you can put drawings inside of pages that all kind of link. So let's say you had the word income inequality in your drawing, that word could be linked to income inequality in a document over somewhere else on your document database. And so in the demo that he did with me screen sharing, he put an exclamation point after a phrase and then just hit refresh and went back and outside of the drawing way back over on a regular outline that that exclamation point shows up, which is really interesting because then you can kind of wander through things and look at them in the way that best suits how your brain represents things. He's also the person who has best managed to emulate the brain's user interface in some other tool. And so there's a graph visualization plug-in that's not Excalidraw. Excalidraw is more of a hand-drawn illustration tool, but there's another plug-in that draws maps, but he's modified it so that it actually does the brain's kind of up, down, left, right visualization, which is really nice. And I'm like, ooh, that, that, that. Yeah, it's cool. You know, I think of how neat it would be too to have each person's brain like uploaded into this cloud and then you have links between the data sets and things like that. And then you could have like rearranged those links and these things and stuff like that. Exactly. It's definitely related to the work that I'm doing with like the agent-centric approach to databaseing and things like that, kind of creating a neural network of information. But, you know, yeah, the labeling of information is really important and there's lots of different ways. I mean, there's so many different like the plethora of and again, so boils down to like, does it make sense to have protocols that are consistent? Like, do we need standards or not? Maybe it's better not to have standards and just kind of let whoever ends up being the leader or organizer of this particular sets of information and kind of leaving more up to just the developers of how they're doing it. But, you know, it is challenging because like, I think as you get maybe like more non-technical people into trying to create applications, I think I would imagine that their approach might be significantly different. They might be coming from two different directions. And so maybe you will need a need for standardization to bridge the gap between technical and non-technical. So I think about this stuff a lot because I'm not totally sure if there needs to be a standardization model or not. And it also too, I'm trying to think a little more outside the boxes to like, you know, we're used to things being done this kind of particular way and it's how our mind works. But like, does that make sense for everyone's mind and everyone's personality and everyone's culture? Like so having more of a customized modular components to this sort of thing and then creating a way in just which those need, those can exchange information if they need to, you know? So it's like the systems are different, but if they need to like transport. So it's like, that's what's happening now with the internet. Like that's how, you know, the front end talks to the back end and that's how different, you know, web and they talk about web three interoperability or blockchain interoperability. But I don't really see there being like this concept of dramatic capacities what they talk about in SEPTOR. And I kind of like the term semantic web over web three anyways. And so this idea of semantics and shared meaning commonalities of meaning. So yeah, it's a very interesting field of study. And I only, you know, I only know the kind of technical lens. I don't know the many other components that are at play here, right? Long ago in my early career as a tech analyst, one of the startups that came through had a product called Grapevine. And its sole purpose was to help companies merge or condense or agree on their vocabulary. Like what do words mean? And that would then feed their database strategies and everything else. But I learned long ago in a consulting engagement before I got into the computer business that just because you say customers doesn't mean everybody agrees on what a customer is. It's like, are they fully paid up customers or are you including the people who are in their rears? Are they active customers or are you counting people who are paying you but haven't shown up on the platform for like six months, et cetera, et cetera, et cetera, right? And most notably, sorry, this is just a fun side to excursion, but I was on a project for Blue Cross, Blue Shield of Missouri. And one of my jobs as a little consultant on the project was to go figure out their subscriber counts for which I went to the basement to a room full of paper files and met Lerlene States who was sitting at her desk and called out, Bobby Jean, bring me this. And she pulled out from her desk an oft photocopied page that had a bunch of boxes on it that weren't like a grid. They were kind of mappy and then she proceeded to call out to people and write down numbers in all these different little squares and then add them up. And that was like the number of subscribers, Blue Cross, Blue Shield of Missouri had at the moment. That was the count. And I'm like, holy God, what just happened? And that was fascinating to me. I realized that many companies were having trouble back then digging their way out from cabinets full of stuff and rolling up numbers in a really manual way. So great fun. And then coming in, like scrolling forward to today, one of my goals in these projects is to figure out how do we each get to express what we believe in a public way, preserving our individual perspectives but then make room to crystallize what we believe in. If you were to express something really crisply and beautifully, I'd be like, what Zeke said over there, that speaks for me. This chunk over here speaks for me. And if Stacy liked it, she would say me too. And over time, you might get 60,238 people who all say that this thing that you're curating, which evolves over time, speaks for them. And then for me, in the world of policy, if I were a lobbyist and could approach our Congress critter and say 60,231 people will actually vote exactly with my recommendation here. That's really different from AARP saying it represents seniors. And like, I'm never ever going to join AARP in any way at all. They've never tried to talk with me or reach out to me. I don't think they understand what a conversation would look like, right? And so an infrastructure where we can separate out issues and points of view and have arguments and provide evidence and set up experiments would allow us then to walk together solving these problems. And then occasionally crystallizing pieces of this where we some subset of us decides we agree on this subset of topics which are in direct opposition to the other political camps, solutions and experiments and whatever else, but at least then if it's explicit in this environment, at least then we can kind of hold these things up next to each other and say, here's a worldview, here's a worldview, here's how they're evolving. Now let's talk, right? That's a world I wanna see. Yeah, definitely. Yeah, I'm with you. And I love a lot of our like, I think it's in many cases Arthur Brock's language but you talked about dramatic capacities. One of his phrases that I really like was expressive capacity, that certain tools give you some, give you some expressive capacity which is really important. Yeah, absolutely. And the way that we categorize things too is important, like they have a wealth of living systems model and it's the different types of wealth. And I like when you're talking about customers, right? We like the way that it works is like, here's customers and then there's like another branch and category of customer, this type and it's like a tree that breaks it down. And so it follows that. So it's like the label, the category is kind of like the parent of like top part of it. And I'm thinking, what if we flip that around and what if instead it's actually the person? It's like, I'm a person, what am I? Well, I'm also a customer of like this type. And so I've got this information, I've got this information. And so it's kind of like changing maybe the hierarchical structure of how we kind of label and categorize things. And again, maybe even eliminating the hierarchy and having it more like Holonic overlap, like lapping these categories, kind of like what you were relating to these perspectives could be kind of more like a Venn diagram, so to speak of shared meanings, you know? That's kind of like, but it's both, it comes from the view of the person and the things and then their knowledge tree and the categories that they use and then you can just identify other people that are having similarities to you or are considered like in the middle, they're somewhat similar, but maybe only in these pieces kind of thing, right? So just think of it as like this embedded web of knowledge really or like a meaning. Scrolling back to the ancient days of prehistoric data, one of the acid tests for me back then was asking a company, do you know if you take one individual, do you know how many lines of business they have with you? Like what products have you sold them? Are they your customer for? And they didn't know because the life insurance people and the property and casualty people had different systems, different databases, whatever, and they weren't referring to the same individual, they had their own roles of who was on. So one of the acid tests was, can you give me a sort of a view of one customer and all of the things that they have for you, they were struggling with and probably some companies still are. But then in the modern decentralized world where we're hoping to get, whether this is web three or something else, but there's a lot of people working on data sovereignty where you and three of us would each manage our own data and then release it selectively to different entities depending on what they had a right or a desire to know, et cetera, et cetera. Who's solving that well? Cause I think that's like key and how does that roll up easily, right? If you have two million people who are each data sovereign, how do you do a query against that, that works at the same speed as, hey, I've got a relational database here running all by myself with all the data locally. Right, exactly. Yeah, and it's tough because once you share it, it's out there. Data is really hard to kill off. I mean, really hard to kill off. I might say, expunge all my data and what are you gonna do? You're gonna go find the backups that you ran every week and you're gonna delete my records from each of them. You're not gonna ever do that, right? That's not going to happen. And so data is gonna live out there. It would be cool if you could somehow find out if somebody was sharing your data. So it's like, if I share this data, I've got it cryptographicly linked to though but I find somehow able within the rules of a network to be able to know if that got shared because it's the same way you can keep track of retweets. In a way, cause theoretically keep track of like the sharing of data now. The problem with that though is that you can take a photo, a screenshot and then now it's off that network. It's not within the same kind of file storage system. So again, it's you run into this challenge of maybe we need to think of an alternative approach and not worry so much about that aspect of it because it's just really tough. I mean, what can you do if someone's just taking a photo of something and then they're sharing that in their network later down in that storage somewhere and you don't even know about it. Yeah, exactly. It's really challenging. So you mentioned sort of applying neural networks to these sorts of problems. Can you talk a little more about the piece of this that you most care about that you're working on? Sure. And how like, I don't want to be too technical either I accidentally make that mistake because I'm kind of been more involved in like the technical conversations lately. I can totally rely on Stacy. Stacy will understand all the technical stuff. Yeah, so I'm going to rely on her to translate. So go right. Don't worry about me. I'm just watching. Go ahead. Be as technical as you need. Yeah. Yeah. Do this. I have to think about it sometimes if I'm talking like outside of that technical space but could you ask me what the question was again? Yeah, yeah. So you mentioned sort of the applications of neural network models into some of this and I'm forgetting what the rest of your statement at the time was in these applications. So I'm wondering more what the nature of your work is and like how that fits together. Yeah. Well, so it's like the decentralized web that is like totally different and it's kind of like the Wild West was, you know? It's when you don't have the centralized servers anymore there's tons of different implications that I got. I wish I had finished the video before this call I was traveling a little bit this weekend I've got some things coming that I'm working on. So, but yeah, it's like you were talking about some of the implications. So I'll be curious to find out what more of those were but that's the thing is there's a lot more and it's a lot different in also too when it comes to like integrity and security, it's like, well now you're relying on other people hosting your data. Like you're in you, there's not necessarily these, there's not a mechanism for what the protocols should and are gonna look like. And that's what I'm saying is whether we standardize them or not. Like you can have a protocol and it doesn't need to be standard, obviously but then that just means there's a bunch of people that have to come up with a bunch of different types of protocols for very specific use cases and then eventually figure out if those need to interoperate with each other or not. And so the thing that I'm most excited about is kind of like thinking of that decentralized server web as a neural network. And of course it can be scary because you're talking about AGI and having access to your data, I mean, they've been doing that already a lot anyways, right? But the thing is I see, and I think of it as like intentional intelligence, like not so much artificial or simulated but maybe more like programmable intelligence or intentional intelligence, that kind of thing. I see there being a lot of upside though because since a lot of that stuff is already going on, I feel like decentralization is going to potentially open up the door for more protections from the consumer side, it would seem likely that it would, right? And so then having a lot of these processes automated is really cool. I mean, like I've already seen in programming what they can do with like filling in what your code should look like and the computer is typing it for you. There's a thing called co-pilot, right? Exactly. And you've got these robots that are standing there talking to people like, hi, how are you answering questions? I can see my cameras detect you've got to watch on and if your color or shirt color is this, whatever. So it's getting to that level already. And so if you can imagine that in terms of doing the protocols now, I think there could be some very interesting things that what it will do is since the government's already using this technology very likely. I mean, there's very little probably that they don't have or aren't using, but it's like now if we can deliver some of those same advantages to the everyday person, we lower their barrier of entry to things. We potentially lower the costs for those services because now it's not like this hidden niche technology. And as well as like I said, it opens up by lowering the barrier of entry it opens up for the fact that you just don't have to have that technical know-how and expertise anymore. So now all of a sudden teams don't have to get as many developers to do stuff. You don't necessarily need as many technicians on a particular task. And I think that eventually with these different, like whatever you wanna call them membranes, I mean, I think of them as like private networks, right? As you have your own little private internets everywhere and as people do kind of like synergize themselves to like be sharing commonality, functionality, then now it's like we're the new Google for ourselves within this little thing. And especially if you keep it like more smaller, like compartmentalized and not have it scaled too much too big. So it's like you're just saying like, it's just the OGM community. So however many that is a couple hundred people or something. Now all of a sudden, it's like you can make really meaningful sets of data information like between themselves and you're getting to, it's like becoming, in a way it's becoming its own aware organism. I know it sounds kind of strange, but you know what I mean? I like it. There's sort of a lot of threads cutting through what you're saying. One of them is like sentience and AGI and self-awareness and does the network aware? Is the software aware? How do these things interact? Who's responsible? What's identity in that world? All those issues are like burbling just beneath the surface too. I think I have a good way to say it now. Right now, Google has all this information and it's creating links between you and all your stuff and all this thing, whatever. But now instead of like them looking on this set, it's us looking at each other and now we're doing it with ourselves, of ourselves, of other people. And you're doing it of the people that trust you, they're giving the trust to do whatever the functionality is or have access to certain bits of data on that backend. And so since you're sharing that same network that would normally just be over here in Google, be looking at it, it's like we're learning about each other in ways that it's like, it's off. It's just unprecedented. It's like we get to now as a society learn more compared to just like other people against us learning about us and then deciding whatever they want to do with it. Exactly. Is it too much of an oversimplification to call it crowdsourcing the knowledge graph? It's good because Google's knowledge graph is the way they maintain those sets of links and what they infer and learn about us. But if we could voluntarily crowdsource that with boundaries so that we can maintain our privacy and our sovereignty and all that, that'd be great. And it's interesting to me that you were, you've been involved in Sceptre and stuff like that because I've known Arthur and Eric Harris-Bron and so forth since meta currency days. And they've been chewing on all these issues for 30 years, right? And Holochain is like a hunk of this thinking spawned or, you know, calved off the glacier into the world. I'm not involved in it, I just inspired by it very much. Yeah, yeah. And so it's really interesting and it's also interesting to me how hard it is just to stand Holochain up, right? Because it's quite the task to just create a platform that somebody can actually use and go start coding and so forth. Yeah, well, and that's the thing is it's not really a platform in the sense it's a framework for platforms. Right, right. That's a bigger difference. People are so used to just having one thing be the one all be all and all, whereas this is just like... And we had a conversation yesterday in Fridges, Spain about protocols, not platforms. Yeah. Which is like, okay, so how do we do this? Like, how do you get the benefits of a platform without the centralization of an actual platform? Yeah, that's a really good, that's one of the questions. It's interesting. And then the other big piece here that's very interesting is how many different ways machine learning can help? And there's just lots and lots and lots of different roles and places where it can help. And then at each of those junctures, you have to go, oh great, how do we keep it from killing us and make sure that it's helping us, right? Because machine learning at every one of those junctures is getting access to too much information and stuff that could be used against people and so forth. So how do we regulate it, control it, govern it, keep it so that it's working on our behalf, not against our interests? I do think that's related to the idea that like centralization by default isn't necessarily a bad thing. So it's like, if you don't have decentralization, then you don't have any emergency, we all agree we need to shut this thing down. Well, if it's not, if there's not some level of centralization, then you can't do that. Now, again, and that's also this whole idea of labeling, it's like, okay, if one person has control, is that that's centralized for sure. But if it's two, is that really centralized? Yeah, it kind of is basically, but five, 10, 15, at what point do you stop saying something is centralized and then it becomes decentralized? Like it's, to me, it's a very arbitrary number of like, well, if 15 people are controlled, we would consider that centralized, but at the same time, that's technically not. It's technically decentralized by a factor of 15. So it's like- Yeah, and also like, so we've been using GitHub to try to share documents in simple markdown format. And if 15 people are all using the same repo and collaborating on the same canonical documents, then it's not very decentralized. But if each of them has a separate place where there's storing files that are being synchronized back together, and then you get into the data synchronization problem, which is part of the conversation we had yesterday as well. So there's a cost to decentralization is the thing, right? And then all data scientists have known this for a long time. It's like, as soon as you fragment information, you're gonna pay it probably somewhere in lots of different ways, huh? So how that's related to AI is, you know? I mean, anyone can really make AI. And so I think like one good thing maybe would be to have it so that, you know, people, people can like know what's going on a little bit more. Cause like right now it's like, how many people are gonna sit down and read the lines of code and try to figure out what the algorithm is. And like, there are people that may, will do it and share it and write about it and stuff, but that's not gonna be all over necessarily prevalent. And so if we can somehow again bridge this gap between technical and non-technical know-how, you know? Well, yeah. Kind of the problem is worse than you just described because if you're using rules-based systems, you can go read the lines of code. If you know how to do that, you can sort of figure out the logic. If you're over the fence in the neural networks deep learning world, there are kind of nothing you can do to look at the weights on the fake neurons that are busy learning and doing stuff. You can't actually understand the snapshot of what's happening in there. It can give you better answers than logic often, but it has a rough time explaining itself. Yeah, it does, yeah, exactly. So I think like, and two, you know, the other topic about it is like, do we make them human-like or not? You know, it's like, do we want our bot to chat to us like a human would or do we want our bot to chat to us like a bot would? So that's an interesting element, I think, at play as well in turn. Again, I don't know anything really about sociology at all. I kind of see this for is like that in ergonomics, you know, user experience. So I don't really know. It's interesting. You're reminding me of the speech synthesizer that Stephen Hawking used, which is sort of known as Stephen Hawking's voice, right? And how, yeah, wait, you want us to chat like bots? More civility. More civility, oh, but bots can get out of control. I mean, you know, especially the killer Fembots. So I'm reminded of Stephen Hawking's voice, which kind of stayed the same until he died. And like speech, text-to-speech synthesis got much better. I mean, we have Google Assistant at home and dang, if it doesn't sound like a human speaking to us and it's all being generated and woven together as sentences like in the blink of an eye, it's just astonishing. But I think that Hawking sort of opted to be, to stay with the level of technology where he was. I think it was a conscious choice, you know, as time passed and things got better. He was like, we're good. Yeah, thank you. I don't know, I haven't sort of read anything about that, but I think we're facing a whole series of choices like that that are gonna cut across what we do, how we collaborate, how we store data, all that. And some of them will be hidden behind the curtain by no code, low code interfaces to systems, right? So that as you said a little earlier, we'll be able to do much more sophisticated things just by a couple of simple configurations. Yeah, I'm gonna type this in, ML can help us study ourselves. Yeah, I was so... Like surveys, customer feedback surveys, but also just personality, like studying yourself, like journals, keeping track of your daily practices or whatever is on your mind, that kind of thing. Yeah. Making it help with that element. Self-awareness. Make ourselves better. Right. And each other, ourselves and each other. When I mean ourselves and each other also. The brain hasn't had an API for a long time so nobody can really sort of peek into it. But I've been looking forward to having my brain more visible outside and letting people analyze it with different tools in different ways. So, you know, let's have a go. Yeah. Have a go at it. It'd be fun. And I hope with that, you know, just again, more access to information is gotta be helpful. Like, you know, you still have to know what that means and that's probably the most difficult part of maybe of science is like, you know, what does it actually mean at the end of the day? Like, is this useful or not? Yeah. It's really tough. It's really tough to be able to track the path to me. Yeah, results, outcomes, like, you know, but there are instances in which you can. And so focusing on those activities, those things that you can and using that as a foundational layer and then look, and then you've got all these pieces and you look at them and say, okay, well, now we're getting into the more abstract. So there's a guy I know, a friend of mine, his name is Brandon, he talks about layers of abstraction. And so I'm kind of going to look into some of that stuff more in complex systems. This like filter, this idea of filtering layers of abstraction. That's kind of cool. That makes sense. One of the problems in this problem space is that lots of people aren't that interested in putting in the extra effort to organize information and to try to express things in different ways. And I get that feedback a bunch. It's like, hey, you know, I go organize stuff every day as I curate stuff into my brain. And one of the things I love about that is that it throws me into system two thinking immediately. I have to engage the cards in my head because it's like, is this worth remembering? Okay, good, where do I put it? What do I call it? What do I link it to? There's a bunch of things that spill out of the act of deciding to memorialize something that floated by in the info stream. But that's rare. Most people are like, how do I make this least effort? How do I just sort of collect things in the bin and find them again or whatever? And I'm wondering how much can machine learning help that process? Either helping people adopt and customize their own processes or just automating the tagging and collection of stuff that goes by or whatever else. And we saw there's a startup that just sort of came into the OGM circle, a startup called Bloop that basically has its own little browser that watches the websites you're going to as you go to them and then weaves them together into a little visual narrative that's running next to what you're doing. So then you can go back and say, oh, I went here and then that led to this side of this thing and this thing and then none of that. And then totally new topic, but there's a cluster of things over here. They're trying to kind of do that. And it's sort of a lightweight way to mark up, tag up your breadcrumbs, I guess. Yeah, that's really cool. Yeah, cause you know, at first the web three or semantic web, are people using those terms interchangeably? Not really. I think if you had asked two years ago, maybe the answer would be yes. But at this point, web three seems to me to mean more blockchain, DAOs, NFTs, the DeFi web and the semantic web is now interesting to a few people, but not as central as it might have been in thinking about what web three might have been from the web, you know, the W3C consortium with Burnersly and so forth. Cause they cared a lot about semantics and ontologies and all that kind of stuff, but that feels dated now. It feels like it's five years back. Okay, gotcha. Yeah. And this is just my amateur perspective cause I'm not a coder in that space. At first the interoperability is going to be a longer road and it's going to be tougher. So interoperability goes down, but then over time it's going to go way, way up. And so that's what I'm trying to think about and predict is to, once it is interoperable, that means some really cool things. And so let's try to play with that basically. Yeah. What are the levers do you think in the middle of that? Where to push to increase interoperability? Oh, I don't know. That's a very, very complex topic. Who's working? That depends on a ton of things. So we should get involved. Who's doing the best work on that? Who have you seen that seems to be like really smart on that topic? Cause I'm trying to figure out how to get close and talk to those people. I don't know. It's like kind of like when you have stuff that's like bleeding edge or cutting edge, whatever. And it's just newer uncharted territory, at least at like what we know about. Again, I'm not conspiracy about it, but like it just seems very logical and rational that the government would be, different governments would be highly incentivized not to let other groups find technology or even know they have certain technologies, just kind of a logic thing. I would imagine there's a ton of stuff out there that just like makes whatever I'm saying look really stupid, you know, but yeah, that's in terms of like, if you're on stuff that's uncharted, then no one really yet. I don't think it's quite matured to the phase of then there'd be like a ton of projects or people that are maybe like really doing it well yet. It's just so new and it also does just depend on a lot of factors and a lot of approaches, you know? So yeah, I don't really know. I mean, I'm not, we haven't gotten so far into that part of it yet because it's so much, like it's becoming less few forward thinking now because it's been a couple of years, but you know, it's still a little far away, it's away from like what I'm thinking about yet because of the fact that like I'm designing a system that you wouldn't really, you wouldn't really want to have it be interoperable necessarily like you, it doesn't need to be. So I'm like when I, if I come up with a network say, it's a blockchain network, whatever, it's not gonna be blockchain because blockchain is not quite accomplishing what we wanted to in my opinion. That itself is fractally compartmentalized and so then the network itself is many, many networks within sight of it, you know? And that's like kind of the power of all the chain is it can divide within. So it's not really just one singular network, but it's many, many, many like partitional fractions. And so like that network itself, I haven't given much thought or consideration to it needing to interact with like the older tech stack or blockchains and things like that because like the way I look at it is why would you want to necessarily interact with a blockchain when you have something that's newer and like doing more stuff, you really have a reason to need to go outside of that. All you have to do is be able to function within sight of itself, you see? And so since the rules are, since like the base, think of it like a simulation, right? If we had a simulation, you have rules of the code and then you have another simulation, it's like you don't need to interact between the two because everything is baked into the rules you're operating within yourself. And so since those rules are much different than the other technology rules it would be like, to me I don't think there's a reason to interoperate with like older technology, you know what I mean? I think so, I mean, correct me if I'm wrong but you can hand the solution from one simulation out through the window to the other simulation and compare notes, there's no reason to go down inside the representational systems and the logic and mechanics of each of those systems because it gets really tangling really fast and whatever efficiencies or improvements you thought you were winning, you suddenly lose because you're too deep in the bowels somehow. Yeah, cause I just don't think I'm gonna be very good at like figuring out how to interact with the older tech stack. And so I'm just skipping the bridge steps. So there's many people working on the bridge and further doing fantastic work. I just haven't given much thought to what that is. I'm just saying that we're gonna have web four soon enough like, so. What do you think web four looks like? What's web four in your head? That, you know, like, I don't know exactly what's gonna be in the middle. I'm gonna learn along the way and try to produce tools that are helpful to people but I'm thinking more of like what is the next step beyond this traditional tech stack? Like it has to do with an artificial neural network that is basically, it seems inevitable that it will be nearly completely decentralized. And so it's going, and it's not gonna follow the same like rules as like the other internet. So we're not gonna need to the same schemas and tech elements of it because it's gonna be, it's more like an operating system. So it would be more as if like, say my operating system is downloaded to my computer, but instead now that operating system, the brain of that operating system is scattered amongst a bunch of computers. Yeah, that makes sense. And so we wind up wandering around with sort of localized networks of capacity and insight that are collaborating across the network. It's funny because there's so much research built on trying to emulate how one brain works, right? Just like, you know, models of human memory and processing and all that kind of stuff, trying to figure out how to replicate a person. But the really interesting stuff is trying to replicate a group of people wrestling with something. That gets really complicated, really fast but really fun. Yeah, I will send you the link to Perspectivism. I mean, it's a school project is about the meta ontology for interoperability amongst different networks. And so it could be central or decentralized. It's basically backend agnostic. Cool. It looks pretty cool. I just don't, I haven't onboarded myself enough to it yet to be able to do it justice in terms of describing or explaining it. But it's Nicholas Luxe project. He was one of the core Holochain developers. And now he's like kind of doing this in conjunction with some Holochain people. Let's see if we can find, I think it's 80 point in that debt. So it's an interesting concept and read. And so I think that those people have a much better understanding of what's going on than myself. Very interesting. Nicholas Luxe LUX or LUCH? LUCKCK, gotcha. And then there was another project I heard about too. I can't remember but I'll send to you if I think of it. Thank you. Thank you, thank you. And sorry, I'm sort of distracted from other conversations I've had today. Any other topics of interest to you that we can turn over here? Yeah, let me think about it. I don't know, Stacey had any input. Yeah, Stacey, what do you think? No, I'm good, I'm just listening and cooking in the background. Gotcha. Well, the one thing that like when I first looked at OGM and started thinking about is like, in a way, as things are becoming more open, it is naturally pulling away from the old system. So it's not like necessarily intentionally trying to, although I'm sure many want to and are trying to and I very much like to pull away from the old system. But it's like not all things about the old system are bad. Like, I'm upset with our government, I don't think he's doing a good job but that doesn't mean like it's all bad or a lot of it is bad necessarily. But as it stands, it's like things aren't, things are going well, I guess they would argue compared to like how it was 100 years ago or whatever it's improving and things like that. But I just, I wonder how does pulling away from the old system look like because it's like you create a new thing and then it's like you have to sustain this thing and pull away and so there has to be this like, I almost think of like a teeter totter, you know, right? Yeah. It's called the two-curve problem. Okay. It's like if you take S-curves, S-curves are basically something grows and then it gets overpopulated, runs out of resources and it dies off. So kind of everything follows as S-curve through its lifespan. And as one S-curve dies, then it gets replaced by some other technology and you have to jump from one curve to the beginning of the next curve, right? There's this problem and sometimes the S-curves don't quite line up in time. So you wind up on old stuff for a very long time because the new thing just wasn't materializing or didn't work or something like that. There's a bunch of complications to it, but it's really interesting and the Institute for the Future that I used to do a lot of stuff with, they use the two-curves problem a lot as a framing issue because they're trying to say, what is the next platform? What are the next sets of technologies? What are we moving toward? And also, when is the right time to jump to the next curve, right? Jump too soon. If it's not baked in your hose, jump too late and everybody jumped before you and you have no market, you have no whatever, so. Yeah, so I think about the S-curve a lot and what's happened here, which is much different now is not only is that changing for like all the industries, basically, so it's not just tech now, it's not just that it's like everything, education, government, governing ourselves, education, like even just like where we live and how we take care of the nature of the environment, how we make our products and stuff like that. So that's happening everywhere, which maybe is always true, but it just seems like because of the pandemic, things kind of grinded to an actual near halt for a significant period of time where I don't know how much that has happened before. I haven't studied much about history for say like World War II or whatever, but it's like, I'm always curious people that do know about that aspect of it is like, what does that mean when things kind of just like are grinded to a halt for a period of time and then it's like re-scrambling and now there's all these things coming up and to me it just seems very chaotic and I don't think that that is such a normal aspect of the S-curve. I don't think it's normally it's like shaking it up and now it's all these things like, I don't know. It seems to me more chaotic than it would normally be traditionally like from a transition. So it's interesting because a long time ago I was kind of pondering this and I didn't mix the two thoughts together but I am now because of this conversation, this idea of S-curves versus step functions. And what I've noticed in technology is very much a step function where my first computer was an Apple II Plus and I worked on that for quite a while and then I got an early Macintosh that was like a boop big leap up and I had one of the first Macintoshes that had only floppy drives, no hard drive. You had to put the drive, you had to swap disks all the time, the whole thing. And I've got the box in my living room right now because a bunch of old tech is we've pulled it out of storage and I need to get rid of it. But then you get this new thing that mouse and windows and like, what's this mouse thing? And that takes over for a long time and then gets really pretty long in the tooth. And then we bump to something else. And by the way, I'm still talking to you over exactly that Macintosh interface, right? It's got much faster and much more powerful but the metaphor, the desktop, the icons, the toolbar is pretty much as they shipped it in 1984. So 1984 to 2022 is a long ways. Like shockingly, I'm just realizing how long that is. And in the meantime, we got things like the smartphone and a couple other interfaces that are different from this thing, but this thing lives on. And years ago, when the brain was available for the first time on Linux, there was a moment also when Microsoft had lost its antitrust suit and there was the ability for some laptop manufacturers to ship laptops that didn't have to pay the Microsoft tax. So part of what was happening that was anti competitive was Microsoft was talking to Dell, Compact, all the old laptop vendors. And for every laptop they shipped, they had to pay for a Windows license, even if they didn't intend to run Windows on it when they were selling it. So they lost that case, which meant they could now ship boxes with Linux but Linux is ugly. You have to be a coder to love Linux. So I was like, hey, Harlan, the inventor of the brain. Hey, Harlan, why don't you modify the brain a bit to be like an OS layer that runs beautifully integrated on Linux. And then my OS could look like the brain instead of a file system with drawers and all that. And he never went for it, but I've always kind of wished that that had been a thing because imagine that then less expensive and very capable machines could have come out that use the brain as the default interface, which then would integrate your brain with my brain. If it was a collectively feasible brain and would let us associate files differently and think differently and express ideas, the whole thing. Yeah, yeah, that's definitely what I'm talking about. And imagine if that brain now is spread out amongst multiple devices. So it's like, you have your own little mesh network. So let's just say like in your house, within your house you have like four different computers. Or whatever, maybe you have like your neighbors, you have a neighborhood and you have your own like little computers, you can have that now is hosted on different devices. So it's kind of like the same way that the brain is decentralized. Your operating system can now be also decentralized, which has advantages. So it's still kind of like centrally controlled in the terms of it's like not going off to Timbuktu or anything like that, it's still within this vicinity. But you can do some cool things like within that too, for more of like customized functionality and different stuff like that. But I think you're exactly right. I mean, that would be, to me that's what makes a lot of sense. Like I think that it's still two dimensional and it's still too like it's like top down file system and it's just linear versus like, why is it not three dimensional? Kind of like when you said that, I was in picturing this, I was potentially picturing operating system as a three dimensional brain, as opposed to this two more cabinet healing like two dimensional brain rocket. And there've been a couple of experiments at like 3D visualization operating systems. I remember Sun Microsystems years ago, I had a video that they shipped where your files started to look more like a city or something like that. And they really didn't gel, they really didn't make sense. And a geographic 3D environment doesn't really work because you don't wanna traverse space to try to find the file. It's a conceptual space and it's like, what's nice about the brain is that I can link concepts to each other and they can be like right next to each other and they don't have to traverse space to get there, right? Well, and now with nanotechnology, I mean, I'm sure they can do that. They have these, I'm sure it's like kind of like that, how it's even though it's small, it's still got a ton of like this neural network going on. I haven't done research on operating system as a cloud, but I would imagine that that would have some potential advantages. Yeah, I'm just looking at the time and someone else is gonna drop into this room in two minutes, whose name is Alice Albrecht, whom I haven't met before, this is our first meeting. So. Well, I appreciate and enjoy the conversation. I'm trying to get better at articulating myself. You're doing great. Practice. Great. Yeah. Yeah, I don't, you know, I'm forcing myself to like try to do more of that because I've had, I normally don't. And so I'm trying to talk more and so I'm grateful for opportunities to speak with people. And it's awesome. Glad you appreciate what I have to say. I really appreciate what you have to say. And, you know, I want to, I wanna be able to help. So like, I really much look forward to seeing how I can participate and contribute to OGM. Thank you. And part of this conversation helps me store in my head like what you care about, what your perspectives on these things are, where you sort of fit into the puzzle. So thank you for that. Do you have a LinkedIn page that I can point to? I have boycotting, Facebook, LinkedIn, Twitter, Instagram. That would explain why you're not findable there. Okay. I would boycott Google. I was boycotting them kind of until I realized I just kind of have to use them. I don't really have a choice right now. Well, there's much before today that I don't have to use the Google single sign on. Yeah, yeah. There's DuckDuckGo, but that's just kind of a front end over Google. Yeah, it just ends up really helping make my life easier. So I do it, but I would ideally not like to, but, you know. Yeah, yeah. Yeah. Goodbye. Yeah. Thanks all. Yeah. Appreciate it. All right. I'll send you a message on Telegram or something. That's perfect. Yeah, please do. Other info.