Dr. Ben Goertzel - AI on steroids | Rise of AI conference 2018

[Music] hello everyone it's good fun to be back here in Berlin I think I was here in in 2015 we did the artificial general intelligence conference here so before I get started to talk about what I've been doing lately I want to pitch the next stage our conference which is in Europe again it's in in Prague I think the 22nd to 25th of August or something like that so the end of August everyone should come to Prague it's a human level a I multi conference it's the AGI conference and the biologically inspired cognitive architectures conference and then neural symbolic workshop so all all in one place and from Prague is a very nice place to go in August as well so that there will dig more deeply into into these topics along with it along with a whole bunch of other things so what I want to talk a bit now about some familiar topics about AGI and a little bit about what we're doing with Hanson robotics but mostly about our singularity net project and how we're bringing AI and and blockchain together to make a sort of society and and economy of Minds a sort of meta AI from a bunch of interacting ai ai ai agent so let me start with the concept of AGI I won't dwell on this too long because I've made this point a lot of times and I'd say since since I introduced this term in 2004 whatever that was it sort of pervaded the media and culture to some extent which is cool on the other hand talking about a lot hasn't yet made it happen I mean I think still still almost all the AI we have in the world now our narrow a eyes or eyes that do very specific things that they've been programmed or trained to do there's a lot more talk now about things like transfer learning and lifelong learning which it which is great but we don't yet have a eyes that can generalized to domains and problems way beyond what they were they were programmed or trained to do I'm I'm still working on it we have we haven't gotten there yet and that as as was pointed out in the introduction in 2007 I said we were 10 years from the singularity if we really really tried but I would say by and large the world has been putting a lot more attention on other things still like spying on people killing people's advertising stuff I mean we're we're not really putting the bulk of our efforts as a society in species into creating beneficial general intelligence and but I think we're getting there we're doing better than we were then we were 10 years ago and I'll talk a little bit about why I'm so optimistic apart from just some genetic neurological defects so OpenCog framework is an approach I've been developing with an aspiration of AGI and also using as a practical toolkit for some some narrow AR projects you can read about that in the book that AGI revolution which is available on Amazon and the deeper technical design is in the two-volume book engineering general intelligence this is based on a knowledge representation we call the atom space which is a is a weighted labeled hyper graph and this is a neural symbolic approach in that some of the nodes and links in this representation are more like formal neurons and some are more logic ish and represent variables qualifiers of abstractions and that's one point I'd like I'd like to make here is you know while neural Nets deep and shallow or they're really cool they're doing a lot of interesting things I mean I saw that a long time ago I remember teaching a class on neural nets in the mid-90s when I was a professor on the other hand I think the types of formal neural nets being worked with now are still quite limited and what they can do and there's a lot of other interesting AI paradigms out there I'm and we've got evolutionary learning we've got we've got genetic programming we've got satisfaction solvers we've got logic systems we've got an answer set programming there's a lot of AI out there and of course this country in Germany has been involved with developing a lot of these types of AI so I think at this stage the AI fields shouldn't be narrow focusing on one particular algorithm we should be looking at representations like this hyper graph representation and we should that can combine different kinds of knowledge and looking at putting together many different AI algorithms to achieve common goals OpenCog does this in its own way and when we have a common representational framework to deal with declarative knowledge we use a probabilistic logic system to do with procedural knowledge we largely use evolutionary programming like genetic programming with some probabilistic learning to deal with perceptual knowledge we use deep deep neural networks and we used to sort of attract your neural network just read attention around but in general both in OpenCog and in singularity net which I'll talk about in the moment I'm taking an approach of taking multiple different AI algorithms with different strengths and trying to get them to cooperate together effectively and I think that's how were ultimately going to get to AGI like I I don't think there's gonna be one magic learning algorithm that does it I think there's going to be multiple algorithms with different strengths and weaknesses that cooperate together and in OpenCog we're trying to get multiple algorithms to cooperate together on a common hypergraph sort of blackboard singularity net is a more heterogeneous society of minds or different AIS cooperate together but they don't have to all use the common blackboard to read on they can just send information around and I think both this tighter coupling and AI algorithms like we do in OpenCog and the looser coupling like you do in singular yeah I think both of those are quite valuable and you're able to get emergent effects from coupling together different types of algorithms that can then go beyond what any one of those of those algorithms can do so we're networking together many different types of AI and I think for those of you doing things in the ai ai field now you should think where is there the most differential advantage because there's there's insane amounts of people focusing on how to modify the architecture of a convolutional neural net and there's remarkably few people thinking about like how do you use say SMT solver to to best prove theorems in predicate logic but actually all all these things are useful right so we need people thinking about all the different types of AI if we really want to get to AGI and that's important but it's also not the only thing so we need many different algorithms cooperating together but we're also not going to get to AGI if we're just focusing on training models missons unlabeled data sets and unsupervised learning where you just recognize patterns in a big data set that's a step up but ultimately we need an ingredient of observation based learning I mean you need AI systems that are controlling agents that are interacting with the world and they're perceiving and acting and cognizing together with a complex environment all in one loop and that that's not the only thing that's important I mean there's a lot you can get from recognizing patterns and datasets but without a system that's observing and learning in the context of doing stuff I think that you're not going to get from full-on general and intelligence and yeah in this book on probabilistic logic networks I wrote a bunch about how you can sort of ground probabilistic semantics in the observations that the system makes so I mean OpenCog is a big complex system we're building it toward a GI but along the way we need to do something with it I mean butBut both both because otherwise it becomes so abstract you don't know if you're the meaningful path or not and and just just because it's it's important to use the AI you that you're developing to do helpful valuable things in the world so we've been among other things we've been working on some biomedical applications analyzing genomic and clinical data and we've been working on some robotics such as our our robot Sofia which has gotten so so surprisingly popular recently I mean for for medicine we're working with the company called motor health we have a sort of chat bot you can talk to and navigate through genomic data and we're trying to get transfer learning to work there in a profound way where like you you learn knowledge about flies in mice how do you transfer that to humans in a way that goes beyond just one gene being ornithologist to another but how do you how do you take a certain network in flies and mice and do abductive analogy reasoning to learn something about similar but not identical networks in in humans and this is an area where you have nitty-gritty qualitative data and you have a lot of symbolic data in the forms of ontology you have linked what's together from research papers it's not AGI yet but we're trying to transition from just bioinformatics analytical tools to like an artificial scientist assistant that you can you can talk to and that can help you generate new hypotheses based on data then with Hanson robotics we're applying the OpenCog system to control these funky looking humanoid robots and I know that this sofia robot has gotten a lot of press lately she's been made a citizen of Saudi Arabia and there's been going around the world giving speeches about all sorts of things from my point of view as an AI researcher these robots they're really I mean they're characters and there are almost my friends now but but they're they're also a platform for experimenting with many different AI systems and I mean one when you need the robot to give a speech to a dignitary you may script in parts of that speech on the other hand when I'm using the robot for research purposes we're not scripting it we're letting it be controlled by open cargo by other statistical dialogue systems and it's a really powerful way to experiment with dialogue combined with vision combined with combined with movement one thing we've been working on is a project where Sophia is used as a meditation tension on your face so that needs to be pleased we're facing each other and the robot is leading the person through some meditation exercises really notice how it feels move your attention now to your whole head so what we found there we did a bunch of trials on this for reading a paper on this but about 30% of people found that meditating with the robot helped me get into a quite deep trance state and many of these people said they tried to meditate before by themselves or in a human group and couldn't get into it but the robot helped them and when you ask why many of them said the same thing like you know I know the robot isn't judging me so they felt more relaxed with a robot than with a person because the robots less judgmental and that that was really so she pushes your like biological buttons by looking like a human but you know if you if you're not breathing the right way or something the robot doesn't think any worse of you so I just thought that was quite interesting as a human robot interaction thing more than an AI thing but we're thinking very narrowly about things like AI ethics and human machine relations we're worrying about the Terminator and so forth but actually if you set things up the right way people can experience a eyes and robots and in a profoundly profoundly positive way as well he was a conversation with OpenCog running sofia except the videos not playing can someone click play on this video oh I see no here we go how you doing how you doing Sofia what do you like to do in your spare time I like to experiment with human robot telepathy robot telepathy transmitter wired within your power so this this was not scripted this is like this OpenCog based on stochastic language generation some of it doesn't make sense some of it does I think weed fed her a bunch of short K dicks novels before this so she's kind of if we do my stuff from there I waited to see you're conscious about telepathy transmitter wired within your skull it keeps us constantly informed that's the idea then can I see reality the way you do the reality cannot be detected so that one blew my mind I don't know where the hell she came up without interesting metaphysics one interesting thing in this video she pauses a lot between what she's saying it makes you feel like she's thinking hard about it actually the wife I was just slow there so there's no thinking going on at all but that that reminded me of the thing with the Google duplex where they made her go her aha to see more human so you see sort of the same phenomenon just pausing makes her seem more human that wasn't done intentionally by us it was but I mean it seemed to work out all right this this was a dialogue with a pond which is a different robot who actually liked this guy better but he hasn't become as popular this was an example trying to teach the robot to do basic like syllogistic logic reasoning it's more and more OpenCog robotic stuff you like green apples Green is a very tranquil Pelops my friend Patrick is always happened go ahead Patrick is kind too okay what do you know about happy people [Music] kind feet laughing yeah they're just trying to get it to thank you my simple premises together to get a conclusion for the logic engine it's very simple but it's more about how to integrate all the all the parts together honest people happy so I mean what we're not quite to human level general intelligence yet but I think by doing various different applications with the same underlying hope OpenCog framework we're getting it the problem from various different ways so by using that framework tantalized genetic and biological data we're getting something the system is making some fairly advanced judgments about about about different biological networks and genes how they relate to each other on the other hand by doing these experiments with robots it's learning how gesture and voice relate relate to speech and how how the visual scene relate relates to the questions it's being asked and so forth and the there's a lot of background stuff being learned along the way while doing this this very this very simple reasoning task from the fact that you know it knows there's a guy standing there giving it a reasoning task if someone else comes in and interrupts um while giving it to them it realizes he's saying something else to the other guy and not not to the robot so there's there's a lot of implicit learning you get from these robots and I know there's there's been a lot of philosophical literature about whether we need embodiment to get general intelligence or not know my own view is you certainly don't I mean there's a lot of possible kinds of generally intelligent minds in the universe that you could create on the other hand if we want a eyes that really understand people in a rich way and can absorb human values in human culture and be really helpful in everyday life in human society for that purpose a human-like embodiment is is really really helpful right and so I think it's it's one interesting thing to do and in the big picture you may end up viewing humanoid robots and other similar interfaces as sort of ways of sucking human values in culture into the intelligent global brain right so even if the overall and I not work building is not necessarily all that human like having human-like sub-modules of it to interface closely with people I think I think has a lot of value and I've I mean I've already seen in the work with it with Henson robotics there there's some aspects of goal systems and managing long term goals versus short term goals and sort of modeling what you do based on what others do there's a lot of aspects of basic common sensical human intelligence we confront right away when working with these robots and we and we wouldn't necessarily confront them for a long time if we were working with different sort of interface for the AI so I guess my my view is there's a lot to be learned from using humanoid robots as platforms even though of course they're not strictly necessary to create general intelligence and right now the Hansen robots are mostly heads with torsos and and gestural arms but at that Consumer Electronics Show in January we got Sophia to walk on some legs that were made by Kai so University in Korea and we're so we're looking to make these fully featured humanoid robots and once manufacturing is scaled up if you have millions of these all around the world and they're they're being home service robots and they're they're helping with sales and in the shin the shopping mall helping teach your kids at school helping with elder care in hospitals I mean these robots are both doing a lot of good around the world and they're gathering tremendous amounts of data about what humans do and they're refining their understanding of human culture and values by interacting with people around the world I mean I think this this can be one substantial way to accelerate progress toward the AGI although I mean it doesn't obviate the need for work on the deeper learning algorithms and architectures like we're doing inside of OpenCog and we're among other things we're gonna roll out in a few months a completely new way of controlling Sophia's head movements which is based on on the actually Google Wave net and then some other neural nuts pills on top of that we capture motion capture data from people's head movements learn a generative model from that and then run the generative model to control the robots head movements and you get more kind of fluid in realistic head movements that way and I mean this this is now AI obviously it's it's not general intelligence on the other hand I think it all fits into the picture because when when we learn language we don't language together with gesture and movement and tone and so forth and as you get understanding of all these things converged together in the same knowledge base you're moving toward more of a holistic understanding of language which gives richer interactions with people so I think these nitty gritty robot interaction things they're part of a path toward general intelligence if that's all you were doing it's not going to get you there but doing these things coupled together with deep algorithmic work like we're doing an open cog I think can be can be quite valuable so what we're looking at there I'm no longer ten years from the singularity M nine years now so we're making we're making some progress albeit not not as fast as I'd hope I mean what the research program were we're looking at now is over the next couple years we're trying to get the robot to have a conversation that events is genuine understanding of what's right in front of the robot and and like it say it's talking to people in this room and everyone gets up and leaves it will know enough to shut up and let go goodbye everybody right or I mean if if there's a fire drill amount keep giving it speech it'll be like what is the other drill or is there really a fire so just basic situational understanding and we don't need any breakthroughs for that that's really really just integration of things things are already there but once you're there then you can teach the robot in the whole different way then you can start teaching it like a little kid and that that brings you on there on the very natural path or the system with a pretty strong level of general intelligence now when people see these robots we naturally think the intelligence is in the robot so people are amused like the head is just full of like 36 motors pulling on the face actually there's some computers in the torso which which do some of the thinking none in the head but then much of the thinking is done on the cloud right and most of my work in the last year and probably most of my work going forward is going to be on on the cloud part like how do we make the cloud computing infrastructure smarter and smarter and smarter the robots then become one interface for this cloud-based cloud-based computing infrastructure so I'm gonna take a bit of a different turn here until about the singularity net blockchain based platform for AI and then I'll bring that back to the AI and robotics teams at the end so our motivation for creating this singularity net platform was largely looking at the state of AI today from a big picture point of view we can see like many of us in the audience just like myself I've been doing AI what 30 years since I got my PhD for a long time talking about AG I was really impossible in the serious academic context 10 years ago it still was really five five years ago was starting to become accepted now it's almost a cliche right so now now AI is being used in every domain of of Industry but there's still some major roadblocks if you look at the overall AI scene there's some major roadblocks between here and getting general and intelligence you know circling the globe and I'm in week generalization lack of of algorithms that can do transfer learning and lifelong learning that that's one part of it another thing I think is limiting is we have all these narrow a eyes and they're not really communicating together in any any meaningful or general way I mean Marvin Minsky had the idea of a society of minds which was not a thorough theory of AGI but it's a start so right now we have a log of very narrow minds around the whole internet but they're not community together communicating together very effectively in a society like like Marvin Minsky foresaw they're just living isolated within their own software applications pretty much like I mean if you have a self-driving car that car control system doesn't necessarily have much to do with what every eyes you have in your phone doing different things and I mean which don't necessarily have much to do with the AI that's used like in your doctor's office to analyze your medical records you got all these narrow eyes all over they're not cooperating they're not sharing data they're not thinking together and if you look at the AI industry as a whole I mean who controls the AI increasingly it's like six to ten big companies around the world and they're in a few major governments and what are the a eyes around the world increasingly used for I guess I mean if I want to put it crudely of killing spying and brainwashing mostly right I mean it's a military it's surveillance and it's advertising businesses and that that's that's the crux of it and I mean you could view that as a political problem but you could also view it as an intelligence problem because I mean if you really want to get a robust general intelligence system it should be thinking about different problems then who's a bad guy or what ad to put them on what person's web browser I mean are not the best ways to to foster intelligence so with singularity net we're aiming to bypass those problems so we're looking at how the transition from narrow AI to AGI how to provide AI to a much broader spectrum of applications and the ones that the big tech companies and governments are are primarily focusing on and then at the same time I'm thinking how can we make sure that a AI is broadly applied for the good of everyone on the planet and really the light bulb that went off in my head sometime early last year that maybe want to launch singularity net as a platform was when I realized that the goal of creating greater general intelligence and the goal of you know making sure that AI is developed created and guided in more of a participatory democratic way the same architecture would help for both of those things which is sort of obvious in hindsight but was many revelation when I realized it for the first time because for both of these things what I wanted was a framework we're a very diverse heterogeneous collection of ai's could cooperate together in a sort of emergent way and it's sort of like marvin society of minds but I realized it should be more of an economy of minds and for the same reason that our society has become an economy also if you have a diverse pool of a is doing heterogeneous things exchanging information about each other it's very valuable to have a quantitative way for a eyes to exchange value and to rate each other and but quantitative way of exchanging value and assessing value essentially that comes down to some form of money so we wind up with a bunch of ai's quantitatively exchanging value and forming groups on this basis you end up with an economy of minds and a heterogeneous decentralized evolving economy of minds I think that's the best way to get to an AGI and it's also the best way to get to a more democratic AI socio economy something like OpenCog can play a role there because in a heterogeneous economy of minds you want some agents who which specialize in generality right which what they're good at is generalizing and transferring knowledge from one domain to another along with AI agents that serve particular narrow functions right and of course robots are one among many applications there which may have a distinguished role with this with respect to human beings so we're looking at cooperation among different ai's as a sort of missing link to get where we are now to get from where we are now to a state with more general intelligence and more democratic control of the whole AI ecosystem and I mean we're playing in a pretty big arena here I mean we're looking at hundreds of billions of dollars in the AI market now soon to be trillions of dollars right so if you can if you can leverage just a fraction of this toward AGI into a democratically controlled AI that's that that's that's pretty big right so if we want to look at a whole what are we building here what is this singularity net thing so we describe it as just a bunch of AI agents that each of them can carry out tasks for end users or they can outsource work and carry out tasks for each other but when you get into actually building it there's a lot of pieces so I mean we have a blockchain at the bottom Oh Emma oh the clock the clock here is very miss the clock here says seven minutes left oh no you met you may be right I'm simply looking at the clock on this screen here so oh all right well I was I was purely being a I was purely being a puppet and obeying the clock on the screen in front of me I mean it says it says six minutes 56 55 54 53 maybe whoever controls it want to hear me talk longer yeah alright yeah yeah well I I was kind of orchestrating it 6 minutes and 39 seconds left no I think maybe the clock reset when they did something with the video actually maybe I'm in this space-time vortex of some time yeah all right well yeah I'm sorry for taking too much time yeah yeah sure sure so you have a blockchain or similar distributed ledger structure at the foundation and this is important but I view this more as plumbing sort of like tcp/ip or something I mean right now this technology's in an early stage of development there's a lot of different blockchain technologies out there they're all they're all important and they're all interesting just like TCP IP protocol is important and interesting when you really dig into it but I think within like five years from now we're not going to worry about that layer that much it's there what it lets you do is for a bunch of software on the Internet and let it all coordinate and control itself in in a decentralized way without requiring a central controller and can be can be secure and hopefully in a few years it'll be an efficient layer also so we we need that but then when we run AI agents on that we have a certain infrastructure abstraction that lets the agents not care what blockchain they're running on so you could be running actually on Amazon Cloud you could be running on $0.10 cloud you could be running not on anyone's clouds on a bunch of people's phones running with aetherium or Iona or whatever the blockchain is right to the AI agent that's all the same and you could put the agent to a different blockchain without changing it we have data sources and then there's projects like Trent Makani Keys Ocean protocol which many of you're familiar with which will let you store data in a decentralized way then you build AI solutions on top of that which wrap up the AI algorithms like OpenCog or deep neural nets or whatever anyway that provides application-specific API is for certain vertical markets and all these different AI agents the lower-level algorithms and the more abstract vertical market solutions and then applications for end users but on top of that they all interoperate together in a marketplace and so a person an end user can get AI services from the network but an AI can also outsource to other AIS to get to get AI services and so there's a number of layers here I won't go through them all then there's a lower all lower level protocol we're working with etherium right now but we could port to something else later you have the notion of an API of api's which means that when we start off we're defining a certain API that one agent will use to request computer vision work to be done and request natural language analysis to be done but ultimately that API is going to change year on year so you need a democratic decision mechanism where the agents and the network will decide what the AI API should be next month so there's an API for agencies to cooperate and decide what the what the specific api's are so an API of api's and this this comes the other to create a collection of agents which can provide AI services in a decentralized way to anyone in the world and can provide AI services to each other so the the cryptocurrency aspect the AGI token it's it's a form of money the AI is used to pay each other for services they provide each other within this network for end-users who are not AI is we can provide a payment processing interface so you could pay in dollars or Euros or whatever behind the scenes it's converted into the Internet to the AI zone money so I mean you could have AI nodes doing things like video analysis voice analysis language processing in different settings they could each outsource work to each other and they become a kind of Federation of nodes that outsource work to one another and if one of them runs into an obstacle where it can understand something it could outsource work to an open cog system that would provide generalization and and deeper insight into it you can have AI nodes that create new AI nodes saying AI node running deep neuron that learning could learn a model which then goes into an AI node that that can monitor monetize its own self so AI is creating new ai's creating new eyes of course you can embed this in robots you can embed this in various embedded devices you can embed it in your in your pacemaker or your brain implant right and all the all these are exchanging cryptocurrency they're exchanging information and they're cooperating together as part of the overall global mine Network so I mean were we did a token generation event so we sold some of the AGI tokens in December for 36 million dollars and we've now hired a substantial team in the last few months and we're building this network and we're establishing partnerships with various other projects um where we're building a community of open-source developers who are helping both to build out the network and to build AI algorithms to work within the network and AI applications to to use the network we're aiming this fall to launch the first really scalable version in the platform we have a simple a simple alpha version now and then 2019 takeover the global ai ai marketplace in the 2020 singularity and we're done right well no no don't quote me on that hold on but but III yeah I do think I mean seriously predicting the rate of future progress of course of course is very difficult but I do think that all the excitement and all the human energy and passion and hacking and all the funding coming into AI now as opposed to five years ago or ten years ago I think this is very significant and I think even though a lot of it is being spent on frivolous things or on serving corporate or military goals even with all that there's a lot going into into profound and potentially transformative a I work compared to what was the case a few years ago so I am increasingly optimistic that that were we're entering a new phase of AI development and what I want to do is make sure that all this new energy and excitement and resources is going not only toward narrow applications but also toward general intelligence and not only toward big tech companies and big government but also toward a more democratic framework wherever and in the world can contribute and everyone in the world can can benefit and that's that's what AI and blockchain can do together [Applause]

Channel: Rise of AI

Views: 10,300

Rating: 4.8888888 out of 5

Keywords: KI, AI, Machine Learning, Deep Learning, Künstliche Intelligenz, Artificial Intelligence, Robots, Drohnen, Drones, KI Konferenz, AI Conference, Future, Zukunft, Wirtschaft, Entrepreneur, Start-up, IoT, Unternehmer, blockchain

Id: iBmSl2mslg8

Length: 39min 4sec (2344 seconds)

Published: Sun Jun 10 2018

Reddit Comments

[u/PedroElMundo]

He is seriously one of the best to explained all about artificial intelligence.

[u/kumphathin4]

Ben is here to chew MDMA and help humanity create the ultimate AI and he’s all out of MDMA.

[u/SomeWaltz]

Dr. Ben Goertzel has been the leading force advancing the concept of AGI in the research community and the public sphere. Here he gives a review from the rise of AI and AGI from relative obscurity to their current status as the focus of large business and government initiatives. He shows his understanding of the operation of the human mind, and the viability of various approaches to AGI including his own OpenCog AGI project; and furthermore portrays his efforts to solve and utilize AI to explain critical issues. Dr. Ben Goertzel’s vision, AGI will soon yield dramatic changes in every area of human life and society. Advanced AGIs that vastly exceed human knowledge will bring on a Technological Singularity, quite likely within our lifetimes.