Can AI power a self-organizing, barter economy?

Dr. Ben Goertzel from SingularityNETOpenCog and Hanson Robotics shares his thoughts on a system where AI’s (and eventually humans) can create complex exchange networks that can move us beyond a one dimensional monetary system. He also shares his strategy on the open source movement, and the AI code powering physical humanoid robots like Sophia, and the virtual reality agents of the future.

See the full transcript of this interview below:

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Guests 
Dr. Ben Goetzel
– SingularityNET, OpenCog and Hanson Robotics
Amber Sofia of Feminine Intelligence and NEPA
Host: Zenka

Important Links:

SingularityNET
OpenCog
Hanson Robotics
Transformative Technology Conference
Feminine Intelligence
Holochain

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Ben Goertzel: The exchange economy with the money economy which is fudgy in different in different cultures right.  The combination with the interfacing of a sort of offer network based economy based on multi party barter exchange with various sorts of one dimensional money economies – it’s also subtle and not quite clear how that will work.

Amber Sophia: Yes it really boils down – back to the living systems principles – and how the membranes communicate. Its really just breaking all the way down to the fundamentals and not just having one membrane for so many different things. And that is really what is starting to put us in these confined boxes, of the corporations and small companies and say this is the one membrane that we work from. If we are going to scale we have to have many different membranes to move through those flows but also to evolve with them.

Zenka: One of the things that is the Toffler’s pointed out – you know we’re moving into the information age where information is knowledge and knowledge is is often more valuable than money. So we’re moving into a system if we can coordinate time and knowledge and resources and money and space so it becomes a fuller thing and I think that we can organize that type of a network based on passion, aligned passion. So what is the strategy? What is the strategy that the person has – what problem are they trying to solve – and what what strategy are they employing? And then you get some resonance on the people giving the resource. I mean it’s fine to have a big resource thing but you also have to you have to define those communities and align them on it on a central vision.

Ben Goertzel: So the the concept of an offering network I came up with in 2013 or 2014 it’s probably not original and been formulated in some other form before.

But I was thinking about how to deal with exchange among parties in a complex society with a lot of different agents but without trying to project value into a one dimensional token like like like a dollar, or a bitcoin or something. I mean this is just motivated by the obvious observation that our human assessment of value isn’t always one dimensional. I mean we can have non transitive values where we value A more than B, B more than C, C more than A, and we have revealed value, revealed preferences where the value of something isn’t even even clear until you have, or the value of A relative to B is unclear until you have A. And that is just the way minds work. And they’re not necessarily bugs, right. So given these complexities of value then projecting all value into one dimension seems annoying and we sense that intuitively sometimes. Which is why you would rather exchange some things than than pay for them, right? Like you would I would you know I would review someone’s book in exchange for them reviewing my book. Probably but I wouldn’t review the book for money because I’m not in desperate need of money right. But there is some exchange there which has to do with the value in the exchange itself and then they give and take is as well as in the things being exchanged.

Amber Sophia: So that goes back to the membranes. Right. You have all these different agents and resources in the ecosystem in each agent and each research has its own membrane and then also the other ecosystems. Right.

So it’s it’s really just completely adaptable, performative, resilient, and customizable and that’s really what we need.

Ben Goertzel: So the idea I came up with which I called the offer network is basically each participant in the economy formulates a list – “Well I’m I’m willing to do X for some agent if some other agent will do Y for me.”

Ben Goertzel: And then you can specify a certain soft preferences. Well I will review someone’s work up to 200 pages. I would rather it was science fiction but any fiction is okay, IF in exchange someone will look edit this document of mine. I would I would I would prefer to have an English literature background. But as long as they know English its alright. So you have sort of hard and soft constraints. Then given these pairs and a large population you can use against constraint satisfaction algorithm to find the optimal matches of who could do what for whom. So my son, Zarathustra implemented an algorithm like that and showed that it work on a bunch of simulations and one of the interesting findings is – if you have a small percentage of participants in the network economy who are willing to just give something without getting anything in return – even two or three percent of just altruistic givers then the total satisfaction of the whole network increases a lot.

Ben Goertzel: So without any altruistic givers you have a lot of cycles that almost close. But there’s no one to close the loop so a little bit of altruistic giving can close a lot of loops which is interesting and I mean makes you wonder if that’s part of how we humans evolved to be slightly altruistic but not that altruistic. So a little bit of altruism in a more exchange based society can increase the average utility a bunch.

So his implementation with a centralized optimization algorithm because that was the easiest thing to do any one to get his master’s thesis done right. Now Kabir Veitas is working for my SingularityNET – he is working on designing but hasn’t yet finished coding. A sort of decentralized framework for the same thing where it’s purely peer to peer and there is no centralized optimization algorithm.

It’s just each agent is locally making making its judgments and sort of sending some feelers out there in the local network. So which cat which can be done can be done also.

Amber Sophia: So I think we also have colleagues tech like that called Holochain if you are aware of that – holonic data structure. Purely peer to peer.

Zenka: And again I think that it would be interesting to have agents in there that could close that loop – so funders for example, that maybe that tiny little closed loop needs to be a paid person. You know everything else is like let’s say 80 percent of the network is free. But then there is that

Ben Goertzel: Right. So I mean you could offer sort of if there’s no one who will do a certain thing because there’s no one they need something now, you can. the AI can figure out well you may need this in the future so if you do this now we can give you this. You can redeem anytime in the next year or something. Yeah. That’s one of the subtler things in the offer network is sort of the differing timing extents of different offers. So we’re looking at this initially as something to implement within our SingularityNET platform where you have transactions among AI’s.

So then it would be AI’s is making the offers and the requests. One AI may need a certain type of question, answer and it maybe willing to perform a certain type of calculation in exchange or something. And this of course has advantages because AI’s could be very good at formulating offer request pairs right then and they could have a lot of different hard and soft constraints in their minds are more amenable to this than people probably.

For this to apply to human exchanges instead of exchanges among AI’s makes perfect sense. It’s just user interface and explanation problems and seemed – you’re going to end up wanting to mix probably money type exchanges with offer network type exchanges where for some things they’re very standardized goods. Maybe they’re not that expensive. It’s just simpler to exchange some tokens for it and be and be done with it. If I want to get you know a bottle of ice tea from a vending machine it’s not worth the energy to formulate an offer request pair. It is easier to put in a dollar and push the button.

If I’m looking for a publisher for a book or a hardware manufacturer for robot design or something. That’s a big thing. There’s a lot of subtly to how it could be done – you want done with some love and care and attention and these are complex enough entities that there are things I could offer that I could circle back to them and in meaningful ways. I think those kinds of cases offer network will probably make more sense and you see that in Chinese and Japanese economy a lot where companies exchange money but they also have a long sort of informal quid pro quo relationships – more so than the US economy is more things are objectivize and quantified completely.

But when we thought about how to do this among humans instead of amoung AIs then we need to present to people so as to seem very application specific I guess. I mean if you are making something if you were to exchange like book or movie reviews or something that’s one thing.

If you’re making something for people to form teams or groups like – match for table to make a software start up a match with the band members to make it rock band or something these are sort of different interfaces they different ways of thinking about it to people even know the same thing behind the scenes.

Amber Sophia: Agent centric applications with pluggable protocol.

Zenka: And I and I really do think the difference between having the AI’s talking is that if you do have passion and strategy towards species level threats or species level opportunities, that’s a different kind of ask than oh do I have like a thing that someone wants or am I willing to – am I willing to washin someones car. If you align people based on these species level threats and species level opportunities that are coming into our view right now. Then you get the passion of people and you get alignment on projects.

Ben Goertzel: This probably comes into the framework we’re working on in terms of what I was calling soft constraints but it doesn’t have to be that I mean because in many cases we do have some specific need that we want fulfilled. But then there are certain ways certain ways we would much rather have a it fulfilled than others. Like I’ve I’ve got to eat something. But I mean if if I can eat something that was produced in an environmentally friendly way, that’s a big plus. But I’m not going to starve myself to death because of that. So my hard constraint is I’ve got to get like food with X number of calories, that that doesn’t make me sick. Right. But then there’s a bunch of soft constraints of how I would like that like that to be produced. And this is where AI, ultimately one of the places AI can help out a system like this is sort of matching people’s preferences and soft constraints because it’s a whole thing of like environmentally sound produced things.

Ben Goertzel: So in the US you may have a stamp of approval when I am in Ethiopia. No one gets something stamps if its environmentally sound right? On the other hand, like all they do is go to some local farm and get some goat and kill it or something, right. It actually is environmentally sound but it’s not it’s not chopped that way but some certifying authority.

But an AI that had any conceptual understanding would figure would figure figure it out that this local place in that setting is more more environmentally sound somewhere with packaged goods or something, right.

The other place where AI can play a big role here is in the reputation system because if you’re if you’re engaging all these exchanges you want to minimize the amount of unfulfilled or very badly fulfilled requests. So then you need a way for agents to rate each other but then you need like a reputation police almost to stop strange scamey games of just people rating each other really high so they get a high reputation and then screwing over other people. So and this is something we’re working on in the SingularityNET platform. Just for general purposes because the AI’s and the network need to rate each other and you need to protect against against malicious behavior. These are the reasons why this sort of system wasn’t feasible like 30 or 50 years ago right. I mean you had a very subtle exchange networks of course prior to the emergence of money as the sole means of exchange. Now it’s gotten so big and complicated you just can’t keep track of all your tacit implicit exchange relationships but using AI and using data structures and so forth on the computer you can go back to this sort of a more informal and human friendly exchange mechanism in a very large group of agents like we have now.It’s not my main focus at the moment but it’s both something that can improve the functionality of our singularityNET network it’s an interesting application of the of the of the AI in the network.

Amber Sophia: Yeah. And it goes hand-in-hand with scaling collective intelligence because if you have data being exchanged to find out resources you also have that data and knowledge coming through which what is going on with the exchange of the resources.

Zenka: And you side step money.

Ben Goertzel: You get a lot more data from this than from from a money exchange system, certainly true. And this data can be used help assist the formation of networks of people or other agents.

Zenka: And marshal resources toward toward the pressing issues of our time where we can work together.

Ben Goertzel: Yeah. Yeah. There’s some obvious applications of stuff like this to marshaling resources for things that don’t exist yet so I can – in the regular, everyday world. Where my mom used to live in Rehoboth Delaware on the East Coast of the US she moved from there while I would go over there. There was no bus from Rehoboth Delaware to anywhere. So if you didn’t have a car – they claim there to be a bus. I waited for like three hours and they were like oh yeah we start running the right and on the other hand many people around there would have liked there to be a bus to get to Wilmington which is the nearest city which has an airport and so forth.

Ben Goertzel: If there were some…The thing is the state as a whole didn’t care about that. And it was the state who controlled the bus system. I mean if there was some mechanism for people in that area to say – if someone runs a bus I will commit to spend at least a hundred dollars per year on bus tickets. And then that would be enough to justify someone buying a bus and for that and putting it there. And as long as most of them didn’t wig out on it, it would work right now among humans. There’s no reason that doesn’t exist. No one bothered to set up a AI’s this is all much easier right. See you could have a bunch of agents in the network like singularity. They’re like I would I would really like to have some agent which does optimization of this kind of function with these performance characteristics and each of us will pay like ten thousand AGI tokens. If someone implements this agent right and then that’s posted for someone to take that task and implement it. So initially it’s humans who would do that. Eventually you could be AI’s who take that specification and then then fulfill

Amber Sophia: It’s actual super mission critical right now. There’s tons of real world applications that are already available in the fields of exponential tech but there’s not enough structure for them to self organize into at this level to be able to start actually catalyzing deep planetary impact which is what we need to begin seeing at this time. [00:22:31][19.2]

Ben Goertzel: I mean there is insane number of things that have already been prototyped and used in some local area. Many people would love to have it in their life if it were there but no one quite wants to make it their passion to bring it there. And there is no easy way. There is no easy way for people to say, “Well I would chip in X amount for this thing and then someone else to grab that and provide.

I mean this has to do with the temporal aspect of offers like I would give this at any point in the next “N” months if someone gave up. Within within the next “N” months.

Amber Sophia: We are in a field that is interested in modeling this in whatever way that we can stewarding it forward.

Zenka: We want it to come from the dreams and desires not conceptually of businesses and governments but from conceptually what we desire for our own lives. What is it to dial back a little bit and bring people up to speed on a few things. So number one you mentioned that we’ve got- we’re in the No Turning Back Stage of AI in the sense that you know you’ve got Tencent you’ve got Google you’ve Amazon.

Ben Goertze: The only way we are going to turn back is a thermo nuclear war. Right right right right. Something that of that ilk – which is not impossible.

Zenka: You talk about the data coming in – from the more data you have. For example in China they’ve got a lot of data coming…

Ben Goertzel: In China, they’re collecting their data in a centralized and well organized way. We have more data per capita than them because they’re still a very rural country. But they just take it all and they put it in their government database. Where as we don’t do that, not as well as they do anyway.

Zenka: I wanted to ask you why why you think SingularityNET is the architectural structure of the future – why you design it that way – and why you think it’s the solution?

Ben Goertzel: I mean I think it’s I think that SingularityNET is an example of the right way to architect and network and collections of eyes that will be robust with respect to various nasty human oriented, human based failure modes. Right.

So there is a couple points there. I mean I’m on the computer science side, of course you want a fairly heterogeneous framework or is a different nature can all communicate with each other and share data outsource work to each other where you can pay these guys and they can pay each other and share data. But that’s only part of the design right because you can implement something like that just inside Google or Amazon or something like that. They haven’t quite done that because the frameworks are more focused on particular specialized types of algorithms that they like but they’re not THAT far from having having something like that.

Ben Goertzel: The next aspect is what we’re using blockchain for making a network like this which is not owned or controlled by any one party but the control is decentralized and sort of democracy based, right. And the advantage of that ultimately is more about the embedding of the AI network in human society than about the AI network itself. Because of course if there was some guaranteed – you know benevolent and cooperative entity being a central controller. I mean that’s not that inefficient on the Internet today. That would basically they would basically work and you could have sub controllers around the world.

The nature of the actual political and economic world is that if you make something susceptible to central control there is high odds it will be taken over by some party whose goals are different than the then the greater good. Right. Which means either you start is acquired and then that company controls it and that company may have been run by a great person at one point but then the business model shifts or government either controls takes over the network or legislates this or that thing can’t be on the network or this part of the network can’t communicate with that one without paying a tax to communicate with that one. A lot of things can happen if the network is not controlled by any central authority then it’s very hard for anyone to take over or shut down so it can grow in a way that’s resilient. With respect to shifting human power structures. Right.

So still of course you’re not escaping humanity as a whole. You just said that the bet here is that humanity as a whole has a more beneficial orientation than the concentrated power structures like large corporations and large governments. Right and not everyone believes that. I mean you could mount arguments you can mount arguments one way or the other – but then anyway – we’re throwing out a lot then that camp. In principle of course it’s appealing. You think if me my 10 best friends control everything., then that’s much better. And of course it might be. But there is a lot of human history showing like one of your ten best friends is co-opted by some guy with a tremendous amount of money and decides to go do something else.

Amber Sophia: I think it really shifts the frame when you actually are truly looking from the whole systems design approach that every piece is a part of the whole. And so when you’re building the data architectures in that way with biomemetic protocols and in the data structures are holonic right. Unlike blockchain which is not truly scalable – to the level that we need – that is sustainable for the planet. Right. And so going back to the whole systems design approach when you look at everything is an agent or a group agent and therefore the data of an agent or a group agent can be looked at as an associative network of data. Right. And so as long as those associative networks are communicating at some fundamental peer to peer protocol layer there really is no centralized data center.

It’s all just aggregating from the different associative networks which is it which is really the holistic way. Yeah. And so this is a part of what some of some of our colleagues have been developing with with Holochain and also what I have been working on with the cognitive assistant. It some really profound work and it’s clear. When you follow the living systems principles it really shows you the way you really look at the whole systems design approach and you really look at the fractal field physics principles. It just pulls it through, every time. I really feel that this is this is how we’re gonna be able to scale this level of information which is also energy right.

Zenka: How do you see the future in- of open source. It’s had sort of a mixed childhood.

Ben Goertzel: I think it’ll continue to play a huge role and I think the more broad based the usage of something is more likely to end up being open source. And until we get rid of capitalism entirely probably not everything’s gonna be open source. So what we’re doing. Our SingularityNET platform is open source and the core algorithms we’re building are all open source.

Ben Goertzel: We were creating a spinoff company called Singularity Studio to make enterprise software applications whose AI is back ended on the SingularityNET. If we build a product specifically to apply our AI for credit risk assessment for financial industry or something right there’s no special reason that needs to be open source. Because I mean the goal of that is to extract money from the financial industry and put it put it into this decentralized network and if some other fin-tech company copies your code and does the same thing but doesn’t direct the AI into our network and then we’re not we’re not benefiting the network that way. 

So the direction we’re going in is some like highly vertical market specific application code will be proprietary and then the platform and the core learning and reasoning algorithms will be open source and that is partly because there are vibrant open source communities you can draw – like to to build a decentralized like Linux based blockchain or Hashgraph or whatever based platform.

[There’s a lot of crypto developers who will help with that for AI there are lot of PD students which will help with those algorithms I mean in the end if you’re building something to help financial institutions predict risk or something. There’s not a huge open source community that’s going to that’s going to add value there anyway. And there’s a lot more people who will copy your ideas and put it into their closed source products and then try to beat you in the market by putting a better user interface on something. So I mean in the end I would like to see everything open source but as a tactical move, some things will be and some things won’t be.

Amber Sophia: Yeah. Absolutely, That’s also guiding us too. It is at the beginning until we’re able to bring enough integrity and coherence to what we’re developing I would say some of it has to not be opensource.  

Ben Goertzel: You can also have security through complexity works pretty well.

The OpenCog is open source but no one outside the team can understand what the fuck it going on.

Amber Sophia: Its so true .

Ben Goertzel: But on the other hand if you get a huge enough amount of revenue from something then eventually they’ll pay someone to look hard enough to figure that out.

Amber Sophia: That was another through that came through around open source data. It’s really not about the data it’s about the recipes of the data that is the nectar.

Zenka: Ben I have one more question for you before I just want to leave you to to ask the world for what you need to do to make your work even stronger. So the question is you’re working on actual robots.

Ben Goertzel: Yes we are doing that.

Zenka: I know I was thinking the other day. It’s almost as if we’re getting to a point where we might leap over the physical robots and move to virtual robots in an augmented reality or something like that. Do you see that kind of shift happening where I think oh this might be easier just to put in AR

Ben Goertzel: There are many kinds of robots, first of all, Industrial robots that build stuff aren’t going away anytime soon.

So someone needs to build those VR goggles that go in your head and that will be done.

Zenka: But Sophia, I mean.

Ben Goertze: Social and emotional robots. – to what extent they can be replaced by VR agents? That’s sort of an open question, actually, that is an open research question and in human factors. Because I mean VR has been about to become amazing and revolutionary since at least the early 80s.

Right. I mean VR is all is always about obsolite everything else. And so I’m sort of I’m not holding my breath for it personally. But if it if it happens that s that’s awesome.

I guess I’ve never spent much more than ten minutes in virtual reality. And I guess personally I like so far. I like being in the physical world better than the alternatives. I love backpacking. I would much rather spend a week backpacking up and down the mountain range than spend the week sitting in my living room stuffing Oreos in my face I can go up and down a virtual mountain range or something right. But on the other hand I’m 51 years old. So my preferences may not reflect that of my son is nine months old now.

Maybe if he gets VR goggles that work when he’s five years old maybe then he’ll lock like his body into a treadmill machine. While he is running up or down some alien planet.

Right. So I mean I guess I’m open to any of those possibilities but I’m slightly skeptical because VR is always just around the corner and it never seems to it. It’s definitely been slow to fulfill its promise so far. Now that was said of AI for a really long time in the last five years the practical applications of AI started to accelerate. So I guess the question is no one will VR hit that really massive improvement in quality that leads to leads to massive adoption.

There’s another question of just the gut psychological impact of having a physical robot there in the same space as your body. And that’s an experimental question. Like we’ve experimented with Sofia as a meditation guide in physical reality and then with her head on the tablet as an avatar as a meditation guide. There is – so it’s subtle. I mean only a few experiments like after meditating with the robot Sofia or with the robot here with the Avatar Sophia. The boost in happiness among participants was the same. The boost of compassion was more for the people interacting with the physical robot. But a small sample size, but it is suggestive. So I’m not sure what why that would be.

But again, this is because it’s with people who identify with their body in the physical world not with the avatar. If you had someone for whom they identified with the Avatar in the virtual world as much or more as with their physical body then maybe they’d be better off with the avatar. Right. So I think that’s that’s not quite clear.

Amber Sophia: That is the beauty of it too. Getting to choose how you want to create and what tools you want to use from the physical to the virtual.

Ben Goertzel: Maybe some of each. If we think about it like a massive real technological singularity may come in say, two to five decades or something – who knows right? Then what we’re talking about with applications like compassionate loving robots is sort of – how do you improve people’s state of consciousness. So as to maximize the quality of the singularity you get the overall benefit of the singularity you get. Toward that end we have to think about the different classes of people who actually exist. And I’m pretty sure for a lot of people who are alive now especially older people the physical robot is going to have a special impact. It might be the case that if younger people end up growing up in VR then they don’t care whatsoever about the physical robot looks. So far I’ve got two dogs in Hong Kong.

I’m not going to trade them for virtual dogs or for like avatars that are puppeteer by real dogs running around somewhere else or something. I still get something from having stuff my actual physical space but I but I look forward to the full body VR suit with full tactile sensation like smell-a-vision sensation and then everything. I mean that would be great.

Did you try the magic leap?

Zenka: Yes I have and that’s where it integrates with your world area because you’ll be hiking on the mountain. It’s just that you will have a guide that is volumetrically like a hologram.

Ben Goertze: Is the Magic Leap as good as hiking on the mountain?

Zenka: Well the field of vision is still very very small. They haven’t solved that – it was not. We are far away from it but it will be good that you are developing all the algorithms to put in.

Ben Goertze: It’s just I would rather it was VR because dealing with factories and manufacturing robots. I mean it’s interesting but it’s very very annoying right.

So if you just make software code in VR then that’s really cool. But I don’t know how to tell we are five years or 20 years away from having VR that actually does does does what we want.

Amber Sophia: I see it perhaps we can look at maybe where we are on the software and digital tech side and the back end.

Ben Goertze: Yeah.

Amber Sophia: It’s kind of as above so below the same software.

Ben Goertze: It is the same software, you can use the same software to drive the robot or the same thing for the driver the robot or the VR agent.

Sophia’s facial movement is driven from the blender game engine. So we just have an avatar there and then there is an adapter that translates movements into the avatar into signals to control the robot face. So it’s that it’s actually the same software on the back end. [

Amber Sophia: But you guys are also looking to perfect the robotics to even be able to be a compassion, loving AI robot. So maybe it is going to take that amount of time IN VR.

Ben Goertze: A lot of it’s the same it’s like facial expression mirroring and making eye contact and understanding the person’s emotions. All this should be about the same whether it’s from a robot or from a virtual agent

Zenka: It’ll just be a lot cheaper for everybody you afford the …

Ben Goertzel: The question is what lives are we living in?

So if you have a the AI , the robot in school, where kids go. The question is are kids going to school? Or are they sitting home putting a VR headset on?

Zenka: But remember what Magic Leap is doing. It’s mixed reality. So VR is when you’re closing off the world you’re in another way. That’s that’s one thing. You might be with your other friends in school.

Zenka: But then it brings this other thing where you’re just putting a holographic three dimensional virtual object that has the same lighting as it just looks like it’s real it’s just not there. But again we’re so impressed with what you’re doing in this space to ensure that we get the right outcome with AI, this is this is important and we we believe in your approach. We’re very happy that you collaborated on the loving AI loving project. If robots, if AI can teach us unconditional love then…

Ben Goertzel: I would say right now people’s minds are blown by sitting across the table from a physical humanoid robot. More so than by an avatar on a tablet. But we haven’t tried the VR thing so I’m happy with any of them. Actually I don’t…. I’m not a hardware guy. I mean I can see other stuff. It’s very tedious and takes a long time. So ifI weren’t good friends with David Hanson who makes these robots I would never bother with that because it’s just a whole bunch of difficult tedious work. Since one of my closest friends makes these amazing robots anyway it’s it’s a fun collaboration to me to be doing. But I guess there will be a period of time when the same AI is used to control physical robots and AR/VR robots and avatars on the phone and everyone’s scurrying around carrying around all the time. [

Amber Sophia: I think once again going back to the holistic approach and making sure that there is holistic or biometric protocols in place so that way where we’re just utilizing the technology to really orient with the experience. I truly believe that that we are utilizing technology to be able to expand our awareness of what our actual biological technologies are capable of doing.

Ben Goertze: The awareness that the AI has as well as the human culture and values into the AI by getting into shared social emotional and cognitive space with it.

Amber Sophia: Yeah absolutely. So I feel like the true singularity is when we merge with the technology and we actually transcend the technology because we’re aware of our biological technologies and understanding how light, frequency and vibration and geometry actually work through the fabric of space time without hardware. [

Ben Goertze: Do you plan to mind upload?

Amber Sophia: Mind upload? I don’t think that that’s going to be necessary. I think we’re going to mind upload to the very fabric of the cosmic consciousness. I think that’s them that’s the mind meld or mind upload.

Ben Goertzel: So you’ll mind upload while retaining your physical body.

Amber Sophia: Yes. So I think it’s uh it’s a matter of evolution and transmutation as like we’re a certain level of density and as we evolve we will become less dense and less dense and less dense as we begin to use the technology to orient and reflect and

Ben Goertzel: Sounds like the Fedora of the Russian Cosmos from the 1800’s. We’re all going to become beings of pure light. And then beam ourselves out to the galaxy.

Amber Sophia: I’d say this is so.

Zenka: I will be mind uploading if I don’t live forever through regenerative medicine we’ll see how that goes.

Ben Goertzel: You can do both.

Zenka: Yes, right right. All of it – cosmic travel all of it.

Ben Goertzel: Its the best of both worlds.

Zenka: Ben in closing. How can people support your work at Singularity. Not in the spring when you guys are moving into the next level. How can people assistance support your work and your vision for the future.

Ben Goertzel: We don’t actually have quite as good answers as we would like. I mean once we launch SingularityNET platform in February. I mean if people are AI developers there is an obvious way to help by putting algorithms into the platform. And if people are software developers or working in businesses you need of AI, of course using using the platform is a way to help grow it. We do get asked a lot by people who just support and love the vision that we’re doing. How can I how can I help with this and we don’t we don’t have a good way of doing this yet. But but we are working on that actually.

One thing that people are contributing now to large companies and surveillance organizations is a whole bunch of data about themselves so I think there should be created a way for people to take data about themselves that they generate by using their phone and everything they’re doing in life. Put that in some secure online container and then you intentionally make that available to projects doing beneficial things. Perhaps as an exchange for use of those products eventually in the future that would that to which the data contribute right. So actually we have. That’s not part of our beta. But I think there could be something quite valuable.

Zenka: Are you going to have a system where the people in the singularity net can request like oh I’m in a you know put a bounty on this. We want this so that there is a request system that developers can look at. Oh this is this is not, I am going to develop this and put out there see if anybody wants it. But are you working on a system that would allow requests to be fulfilled.

Ben Goertzel: We will do that, yeah, sometime early next year. There’s been a bunch of demand for that just within the SingularityNET community already.

Zenka: Well thank you for joining us Ben. You stand out because your original thinker and you’re brave in your you’re embodying and living a new way of thinking about problems that no one else is doing. So if it weren’t you, we have this legacy that you’re building right now and we’re very grateful.

Ben Goertzel: Well thanks. I mean I think it’s an interesting time. So actually every idea that I’m stating is probably a hundred or a thousand people in the world coming up with variations of that idea which is the way history works. So it’s an amazing time when all these ideas are sort of bubbling up to the surface because it’s becoming possible to build instead of just thinking about it.

Interesting topics, this has been a fun conversation because we touched on things people don’t usually ask me about. No one asked me if they can go on a date with Sophia in this interview.

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