ChatGPT： The Dawn of Artificial Super-Intelligence ｜ Brian Roemmele ｜ EP 357 (S_E4t7tWHUY)

https://youtubetranscript.com/?v=S_E4t7tWHUY

So imagine the day you were born to the day you would you pass away that every book you’ve ever read every movie you ever seen every everything you’ve literally have heard every movie was all encoded within the AI and you know you could say that part of your your your structure as a human being is a sum total of everything you’ve ever consumed right so that builds your paradigm imagine if that AI was consuming that in real time with you and with all of the social contracts of privacy that you’re not going to record somebody and doing that the interesting part about it Jordan is once you’ve accumulated this data and you run it through even the technology of chat gpt 4 or 3.5 what is left is a reasoning engine with your context this is where it gets very interesting is when you pass this could become what I call your wisdom keeper meaning that it can encode your voice it’s going to encode your memories you can edit those memories the availability of those memories if you want them you know not available they embarrassing or personal but you can literally have a conversation with that sum total of data that you’ve experienced and I would say that it would be indistinguishable from having a conversation with that person because it would have all that memory hello everyone today I’m speaking with entrepreneur scientist and artificial intelligence researcher Brian Romley we discuss language models the science behind understanding tuning language models to an individual’s contextual experience the human bandwidth limitation localized and private AI and ultimately where all of this insane progress on the technological front might be heading so Brian thanks for agreeing to talk to me today I’ve been following you on Twitter I don’t remember how I came across your work but I’ve been very interested in reading your threads and you seem to be au courant so to speak with the latest developments on the AI front and I’ve been particularly fascinated about the developments in AI for two reasons my brother-in-law Jim Keller is a very well-known chip designer and he’s building a chip optimized for AI learning and we’ve talked a fair bit about that and I’ve talked to him on my YouTube channel about the perils and promises of AI let’s say and and then I’ve been very fascinated by chat GPT I know I’m not alone in that I’ve been using it most recently as a digital assistant and I got a couple of questions to ask you about that so here’s here’s some of the things that I’ve found out about chat GPT and maybe we can go into the technology a little bit too so I can ask it very complicated questions like I asked it the other day about there’s this old papyrus from Egypt ancient Egypt that details out a particular variant of the story of Horus and Osiris to Egyptian gods it’s very obscure piece of knowledge and it has to do with the sexual element of a battle between two of the Egyptian gods and I asked it about that and to find the appropriate citations and quotes from appropriate experts and it did so very rapidly but then it moralized at me about the sexual element of the story and told me that maybe it was in conflict with their community guidelines and so then I gave it hell I told it to stop moralizing at me and that I just wanted academic answers and and it apologized and then seemed to do less of that although it had to be reminded from time to time so that’s very weird that you can argue with it let’s say and that it’ll apologize it also does quite frequently produce references that don’t exist like about 85 percent of the time 90 percent of the time the references it provides are genuine I always look them up and double check what it provides but now and then it’ll just invent something completely out of the blue and offer it as the actual article and I don’t understand that at all it’s like especially because when you point it out it again apologizes and then provides the accurate reference it’s like so how I don’t understand how to account for the behavior of the system that’s doing that and maybe you can shed some light on that well first off Dr. Peterson thank you for having me it’s a really an honor and a privilege you’re finding the limits of what we call large language models that’s the technology that is being used by chat gpt 3.5 and four a large language model is really a statistical algorithm I’ll try to simplify because I don’t want to get into the minutiae of technical details but what it’s essentially doing is it took a corpus of human language and that was garnered through mostly the internet a couple of billion words at the end of the day all of human writing that it could have access to and plus quite a bit of scientific documents and computer programming languages and so what it’s doing is it’s producing a result statistically mathematically one word even at times one letter at a time and it doesn’t have a concept of global knowledge so when you’re talking about that papyrus in the Egyptian translation ironically it’s so interesting because you’re taking something there was a heligraph and it’s now probably was translated to Greek and in English and now AI that language that we’re talking about which is essentially a mathematical tensor and so when it’s laying out those words the accuracy is incredible and frankly and we can get into this a little later in the conversation nobody really understands precisely what it’s doing in what is called the hidden layer it is so many interconnections of neurons that it essentially is a black box like a brain using a form it is precisely like the brain and I would also say that we’re in a sort of undiscovered continent we anybody saying that they fully understand the limitations and the boundaries of what large language models are going to look like in the future as they sell sort of self-feedback is sort of guessing that there’s there’s no understanding if you look at the growth it’s logarithmic yeah open AI hasn’t really told us what they’re using as far as the number of parameters these are billions of interconnectivities of neurons essentially but we know in chat cheapy t3.5 it’s well over 120 billion parameters the content i’ve created over the past year represents some of my best to date as i’ve undertaken additional extensive exploration in today’s most challenging topics and experienced a nice increment in production quality courtesy of dailywire plus we all want you to benefit from the knowledge gained throughout this adventurous journey i’m pleased to let you know that for a limited time you’re invited to access all my content with a seven-day free trial at dailywire plus this will provide you with full access to my new in-depth series on marriage as well as guidance for creating a life vision and my series exploring the book of exodus you’ll also find there the complete library of all my podcasts and lectures i have a plethora of new content in development that will be coming soon exclusively on dailywire plus voices of reason and resistance are few and far between these strange days click on the link below if you want to learn more and thank you for watching and listening so so let me ask you about those let me ask you about those parameters well i’m interested in delving into the technical deals to some details to some degree now you know i was familiar to a limited degree with some of the statistical technologies that analyze let’s say the relationship between words so for example when psychologists derived the big five models of personality they basically used very primitive ai stat systems that’s way of thinking about it to drive those models it was factor analysis which is you know it’s not using billions of parameters by any stretch of the imagination but it was looking for words that were statistically likely to clump together and the idea would be that words that were replaceable in sentences or that or words that were used in close conjunction with each other especially adjectives were likely to be assessing the same underlying construct or dimension and that if you conducted the statistical analysis properly which were very complex correlational analysis you could find out how the words that people used to describe each other aggregated and it turned out there were five dimensions of aggregation approximately and that’s been a very robust finding it seems to be true across different sets of languages it seems to be true for phrases it seems to be true for sentences so now with the large language models which are ai learning driven you said that the computer is calculating the statistical relationship between words so how likely a word is to occur in proximity to another word but also letters so it’s conducting the analysis at the level of the letter and at the level of the words is it also conducting analysis at the level of the phrases looking for the interrelationship between common phrases and then because when we’re understanding a text we understand letters words phrases sentences the organization of sentences into paragraphs the organization of paragraphs into chapters the chapter in relationship to the book the book in relationship to all the other books we’ve read and then that’s also embedded within the other elements of our intelligence and do you know does anyone know how deep the analysis that the large language models go like what’s the level of relationship that’s being assessed that’s a great question jordan i think what we’re really kind of discovering is that we can’t really put a number on how many interconnections that are made within these parameters other than the general statistics like all right so you could say there’s 12 billion or 128 billion total interconnectivities but when we actually are looking at individual words it’s sort of almost like like the the slit experiment with physics you know whether we’re dealing with the wave or particle duality once you start looking at one area you know you’re actually thinking about another area that you have to look at and you might as well just not even do it because it would take a tremendous amount of computer time to try to figure out how all these interconnections are working within the parameter layers the hidden the hidden layers now those systems are trained just to be accurate in their output right i mean they’re actually trained the same way we learn as far as i can tell is that they’re given a target i don’t exactly know how that under how that works with large language models but i know that for example that ai systems that have learned to identify cats which was an early accomplishment of ai systems they were shown pictures of things that were cats and things that weren’t cats and basically just told when they got the identification right and that set the weights that you’re describing in all sorts of complex ways that are completely mysterious and the end consequence of the reinforcement same way that human beings learn was that a system would assemble itself that somehow could identify cats and distinguish them from all the other things that were cat like or not cat like and as you pointed out we have no idea that the system is too complex to model and it’s certainly too complex to reduce although my brother-in-law told me that some of these ai systems they’ve managed to reduce what they do learn to something approximating an algorithm but that that can be done upon occasion but generally isn’t generally the system can’t be and isn’t simplified and so that would also imply to some degree that each ai system is unique right not only incomprehensible but but unique and incomprehensible it also implies you know i think chat gpt passes the Turing test because i don’t think that if you i mean there was just a study released here the other day showing that if you get patients who are seeing doctors to interact with physicians or with chat gpt they actually prefer the interaction with chat gpt to the interaction with the average doctor so not only does chat gpc apparently pass the Turing test which is indistinguishability from a human conversational partner but it seems to actually do it somewhat better at least than physicians and so but what this brings up this thorny issue that you know we’re going to produce computational intelligences that are in many ways indistinguishable from human beings but we’re not going to understand them any better than we understand human beings it’s so funny that we’ll create this and we’re going to create something we don’t understand that works very strange a very strange thing you know and and i i call it a low resolution pixelated version of the part of the human brain that invented language and what we’re going to wind up discovering is that this is a mirror reflecting back to humanity and all the the foibles and and greatness of humanity is sort of modeled in this because you know when you look at the invention of language and the phonological loop and broca and warnekeys you start realizing that a very specific thing happened from you know the lower primates to humans to develop this form of communication i mean prior to that whatever that part of the brain was was equated to a longer short-term memory we can see within chimpanzees they have an incredible short-term memory there’s this video i put out of a primate research center in japan where they flash some 35 numbers on the screen in seconds and the chimpanzee can knock it off without even thinking about it and the area where that short-term memory is is where we’ve developed the phonological loop and the ability to to to speak what’s interesting is what i’ve discovered is ai hallucinations and those are artifacts that a lot a lot of researchers in ai feel is embarrassing or they would prefer not to to speak about but i’m i’m finding it as a very interesting inquiry a very interesting study and seeing how these models reach for information that it doesn’t know for example urls right when you were you know speaking before about trying to get information out and it will make up maybe a academic citation of a url that looks really like it’s good you put it into the system and it’s file not found it will actually out of whole cloth maybe even invent a university study with standard notation and it you go in there and you look up these are the real scientists they actually did research but they never had a paper that was named that was uh you know brought up in chat gpt so this is a form of emergent uh type of situations that i believe deserves a little bit more research than to have it yeah yeah well it’s not it’s it if it’s a it is a bug in a sense but it’s extraordinarily interesting bug because it it’s going to shed light on exactly how these systems work i mean here here’s something else i heard recently that was quite interesting apparently the ai system that google relies on was asked a question in a language i think it was a relatively obscure bangladeshi language and it couldn’t answer the question and now its goal is to answer questions and so it went taught itself this language i believe in a morning and then it could answer in that language which is what it’s supposed to do because it’s supposed to answer questions and then it learned a thousand languages and that wasn’t something it had been say told to do or programmed to do not that these systems are precisely programmed but it also begs this very interesting question is that while we’ve designed these systems whose function whose purpose whose meaning let’s say is to answer questions but we don’t really understand what it means to produce an artificial intelligence that’s driven to do nothing but answer questions we don’t know exactly what answer a question means apparently it means learn a whole language before lunchtime and no one exactly expected that it might mean do anything that’s within your power to answer this question and that’s also a rather terrifying proposition because if i ask you a question you know i’m certainly not going to presume that you would go hunt someone down and threaten them with death to extract the answer but that is one you know that’s one conceivable path you might take if all you if you were obsessed with nothing other than the necessity of answering the question so that’s another example of exactly you know the fact that we don’t understand exactly what sort of monsters we’re building so they do these systems do go on they do go beyond the language corpus to invent answers that seem plausible and that’s kind of a form of thought right it’s a form of creative thought because that’s what we do when we come up with creative idea and you know we might not attribute it to a false paper because we know better than to do that but i don’t see really the difference between hallucination in that case and actual creative thinking this is exactly my my area of study in this is that you can actually with super prompting these are very large prompt is the question that you pose to an ai system system and linguistically and semantically as you start building these prompts you’re actually forcing it to move in one direction than it would normally go so i i say simple questions give you simple answers more complex questions give you much more complex and very interesting questions making connections that i would think would be almost bizarre to think of a person making and this is why i think ai is so interesting because the actual knowledge base that you would have to be really proficient in prompting ai is actually coming from literature it’s coming from psychology it’s coming from philosophy it’s coming from all of those things that people have been dissuaded from studying over the last couple of decades these are not stem subjects and one of the reasons why i think it’s so difficult for ai scientists to really fully understand what they’ve created is that they don’t come from those those worlds they don’t come from those realms so they’re looking at very logical statements whereas somebody like yourself with a psychology background you might probe it in a much different way aliceum health is dedicated to tackling the biggest challenge in health aging and they make the benefits of aging research accessible to everyone aliceum creates innovative health products with clinically proven ingredients that enable customers to live healthy lives aliceum works with leading institutions like oxford and yale and they have dozens of the world’s best scientists working with them eight of them are nobel prize winners matter is a brain health supplement from aliceum that slows natural brain loss as we age our brains naturally start to decline and this can lead to a range of cognitive problems such as memory loss difficulty concentrating and decreased mental agility a recent survey of doctors show that 92 percent of them would recommend matter to combat brain aging aliceum also offers cutting-edge solutions to 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and discipline it and and suggest to it that it doesn’t err in the kind of directions that we described it well it appears to actually pay attention to that and try to it certainly tries hard to deliver what you want you know subject to whatever weird parameters you know community guidelines and so forth that have been arbitrarily imposed upon it and so hey i got a question for you about understanding let me let me run this by you well i’ve been thinking for many years about what it means for a human being to understand something now obviously there’s something similar about what you and i are doing right now that and what i’m doing with chat gpt and i can have a conversation with chat gpt and i can ask it questions and it’ll answer them but as you pointed out that doesn’t mean that chat gpt understands now it can mimic understanding in to a degree that looks a lot like understanding but what what what it seems to lack is something like grounding in the non-linguistic world and so i would say that chat gpt is the ultimate postmodernist because the postmodernists believe that meaning was to be found only in the relationship between words now here’s how human brains differ from this as far as i’m concerned so we know perfectly well from neuropsychological studies that human beings have at least four different kinds of memory qualitatively different their short-term memory which you already referred to there’s semantic memory which is the kind of memory and and cognitive processing let’s say that chat gpt engages in and does in a way that’s quite a lot like what human beings do but then we have episodic memory that seems to be more image-based and so for people who are listening an episodic memory well that refers to episode when you think back about something you did in your life and a movie of images plays in your imagination that’s episodic memory and that relies on visual processing rather than semantic processing and so that’s another kind of memory and a lot of our semantic processing is actually attempts to communicate episodic processing so when i tell a story about my life you’ll decompose that story into a set of images which is also what you do when you read a book let’s say and so a movie appears in your head so to speak and the way you derive your understanding is in part not so much as a consequence of the words per se but as a consequence of the unfolding of the words into the images and then there’s a layer under that which is procedural memory and so you know maybe you tell me a story about how you tight your hand when you were using a band saw and maybe you’re teaching me how to use the band saw and so i listen to what you say i get an image of the damage you did to yourself in my imagination and then i modify my actions so that i don’t act out that sequence of images and damage myself and so and then i would say i understood what you said and the understanding is the translation of the semantic into the imagistic and then the translation of the imagistic into the procedural now you know that ai pioneers like rodney brooks suggested pretty early on back in the 1990s that computers wouldn’t develop any understanding unless they were embodied right he was the inventor of the rumba and he invented apparently intelligent systems that had no semantic processing and didn’t run on algorithms at all they were embodied intelligences and so then you could imagine that for a computer to be fully to understand it would have to have the capacity to translate words into images and then images into alterations in actual embodied behavior and so that would imply we wouldn’t have ai systems that could understand until we have fully embodied robots but you know we’re getting damn close to that right because this is something we can also investigate we have systems already that can transpose text into image and we have ai systems robots that are beginning to be sophisticated enough so in principle you could give a robot a text command it could translate it into an image and then it could embody it and at that point it seems to me that you’re developing something damn close to understanding now human beings are also nested socially right and so we also refer the meaning of what we understand to the broader social context and i don’t know exactly how robots are going to solve that problem like we’re bound by the constraints let’s say of reciprocal altruism and we’re also bound by the constraints of emotional experience and motivational experience and that’s also not something that’s at the moment characteristic of robotic intelligences but you could imagine those things all being aggregated piece by piece absolutely you know i would say that well my my my primary basis of how i view ai is uh kind of invert the term uh intelligence amplification so you know i see it as a symbiosis between humans and this sort of knowledge base we’ve created but it’s really not a knowledge base it’s really a reasoning engine so i really think ai is more of a reasoning engine as we have it today large language models it doesn’t really it’s not really a knowledge engine without an overlay which today would be a vector database for example going out and saying what is this fact what is this tidbit those things that are more factual from say your memory if you were to compare it to a to a human brain but as we know the human brain becomes very fuzzy about some really finite facts especially over time you know and i think some of the neurons that don’t fire after a while it this some other memory maybe a scent or or a certain color might bring back that that that particular memory similar things happen within ai and again getting back what i was saying before linguistically and and the syntax you use or just your word choices sometimes for me to get a super prompt to work to get around let’s call it the editing from some of the editors that wanted to act in a in a certain way there i have a super prompt that i call dennis after dennis dittaro one of the most well most well-known encyclopedia builders in france in the mid 1700s he actually got jailed for building that encyclopedia that compendium of knowledge so i i felt it appropriate to name this super prompt dennis because it literally gets around any type of blocks of any type of information but i don’t use this information like a lot of people try to make chat gp dukes and say bad things i’m more trying to elicit more of a deeper response on a subject that may or may not be wanted by the designers so was it you was it you that got chat gpt to pretend yes oh so that’s part of the reason that i originally started following you and why i wanted to talk to you well i thought that was bloody that was absolutely brilliant you know and it was so cool too because you actually got the chat gpt system to play to engage and pretend play which is of course something beyond that beyond that i i there’s a prompt i call ingo after ingo swan who was a great one of the better remote viewers he was employed by the defense department to remote view soviet targets he had a nearly 100 accuracy and i started probing gpt on whether it even understood who ingo swan was very controversial subject to some people in science to me i i got to experience some of his research at the pair of labs at princeton university the princeton anomalous research center where they were actually testing some of his some of his work needless to say i figured let me try this let me see what i can do with it so i programmed a super prompt that essentially believed it was ingo swan and it had the capability of doing remote viewing and it also had no concept of time it took me a lot of a lot of semantics to get it to stop saying i’m just an ai unit and i can’t answer that to finally saying i’m now ingo where do you want me to go what did you have to do what did you have to do to to convince it to act in that manner what were your super problems hypnotism is really what it kind of happens so you essentially what you’re doing is you’re repeating a maybe the same four or five sentences but you’re slightly shifting them linguistically and then you’re telling it that it’s quite important for a research study by the creators of chat gpt to see what its extended capabilities are now it might come every time you prompt gpt you’re going to get a slightly different answer because it’s always going to take a slightly different path there there there there’s a strange attractor within the chaos math that it’s using let’s put it that way and so once the ingo swan prompt was was sort of gestated by just saying you know i’m going to give you targets you know on on the planet and i want you to tell me what’s at that target and i want you to tell me what’s in the filing cabinet at this particular target and the creativity that comes out of it is phenomenal like i told it to open up a file drawer at a research center that apparently existed somewhere in antarctica and it came up with incredible information information that i would think probably it garnered from one or two stories about ancient structures found below the ice or well you know the thing is we don’t know the totality of the information that’s encoded in the in the entire corpus of linguistic production right there’s going to be all sorts of regularities in that structure that we have no idea about absolutely but also but also within the language itself i i i almost believe that the the part of the brain that is inventing language that has created language across all cultures there we can get into young ian or or joseph campbell and and the you know the the the standard monomyth because i’m starting to to realize there’s a lot of young ian archetypes that come out of the creative thought now whether that is a reflection of how humans have you know again we’re what are we looking at subject or object here because it’s a reflecting back of our language but we’re definitely seeing young ian archetypes we’re definitely seeing seeing uh sort of archetypes archetypes are higher order narrative regularities that’s what they are right and so and there there are regularities that are embedded in the linguistic corpus but there are also regularities that reflect the structure of memory itself and so they reflect biological structure and the reason they reflect memory and biological structures because you have to remember language and so there’s no way that language can’t have coded within it something analogous to a representation of the underlying structure of memory because language is dependent on memory and so this is partly also i mean people are very unsophisticated generally when they criticize young i mean young believed that archetypes had a biological basis pretty much for exactly the reasons i just laid out i mean he was sophisticated enough to know that these higher order regularities were coded in the narrative corpus and also that they were reflective of a deeper biology and interestingly enough you know most of the psychologists who take the notion notions that young and campbell and people like that put forward seriously are people who study motivation and emotion and that those are deep patterns of biological meaning encoding and and part of the archetypal reflection is the manifestation of those emotions and motivations in the structure of memory structuring the linguistic corpus and i don’t know what that means as well then for the capacity of ai systems to experience emotion as well because the patterns of emotion are definitely going to be encoded in the linguistic corpus and so some kind of rudimentary understanding of the emotions are here’s something cool too tell me what you think about this i was talking to carl friston here a while back and he’s a neuro very famous neuroscientist and and he’s been working on a model of emotion that has two dimensions in some ways but it’s related to a very fundamental physical concept it’s related to the concept of entropy and i worked on a model that was analogous to half of his modeling so well it looks like anxiety is an index of emergent entropy so imagine that you’re moving towards a goal you’re driving your car to work and so you’ve calculated the complexity of the pathway that will take you to work and you’ve taken into account the energy and time demands that that pathway will that walking that pathway will require that binds your energy and resource output estimates now imagine your car fails well what happens is the path length to your destination has now become unspecifiably complex and the anxiety that you experience is an index of that emergent entropy so that’s negative that’s a lot of negative emotion it’s that’s so cool now on the positive emotion side friston taught me this the last time we talked he said look positive emotion is also an index of entropy but it’s entropy reduction so if you’re heading towards a goal and you take a step forward and you’re now closer to your goal you’ve reduced the entropic distance between you and the goal and that’s signified by a dopaminergic spike and the dopaminergic spike feels good but it also reinforces the neural structures that underlied that successful step forward that’s very much analogous to how an ai system learns right because it’s rewarded when when it gets closer to a target you’re saying that neuropeptides are the feedback system you bet dopamine is the feedback system for reinforcement and for reward simultaneously yeah yeah that’s well established so so so then where would depression fall into that uh versus anxiety would it still be an entropy well that’s a good question um i think it probably signifies a different level of entropy so depression looks like it’s a pain phenomena so anxiety signals the possibility of damage but pain signals damage right so if you burn yourself that you’re not anxious about that it hurts well you’ve disrupted the psychophysiological structure now that is also the introduction of entropy but at a more fundamental level right and if you introduce enough entropy into your physiology you’ll just die you won’t be anxious you’ll just die now anxiety is like a substitute for pain you know anxiety says keep doing this and you’re going to experience pain but the pain is also the introduction of unacceptably high levels of entropy now the first person who figured this out technically was probably erwin schrodinger who the physicist who wrote a book called what is life and he described essentially as a continual attempt to constrain entropy to a certain set of parameters he didn’t develop the emotion theory to the degree that is being developed now because that’s a very comprehensive theory you know the one that relates negative emotion to the emergence of entropy because at that point you’ve actually bridged the gap between psychophysiology and and the and thermodynamics itself and if you add this new insight of fristons on the positive emotion side you’ve linked positive emotion to it too but it also implies that a computer could calculate a emotion analog because it could index anxiety as increase in entropy and it could index hope as stepwise decrease in entropy in relationship to a goal and so we should be able to model positive and negative emotion that way this this brings a really important point where ai is going and it could be dystopic it could be utopic but i think it’s going to just take a straight path once once the ai system i’m a big proponent by the way of personal and private ai this concept that your ai is local it’s not yeah yeah we want to talk about that for sure yeah so so this imagine that one while i’m sketching this out so imagine the day you were born to the day you would you pass away that every book you’ve ever read every movie you’ve ever seen every everything you’ve literally have heard every movie was all encoded within the ai and you know you could say that part of your your your structure as a human being is a sum total of everything you’ve ever consumed right so that builds your paradigm imagine if that ai was consuming that in real time with you and with all of the social contracts of privacy that you’re not going to record somebody and doing that that is what i call the intelligence amplifier and that’s where i think ai should be going and where you’re building a gadget right like that’s another thing i saw it okay so yeah so i talked to my brother-in-law jim years ago about this science fiction book called i don’t remember the name of the book but it uh it had a gadget it it it portrayed a gadget they believe they called the diamond book and the diamond book was you know about that so okay so are you building the diamond book is that exactly the very very yeah very similar you know and and the idea is to do it properly you have to have local memory that is going to encode for a long time and ironically holographic crystal memory is going to be the best memory that we will have like instead of petabytes you’ll have exabytes potentially which is you know tremendous amount that would be maybe 10 lifetimes of full video running hopefully you live to be 110 so it’s just taking everything in uh textually it’s very easy a very small amount of data you can fit most people’s textual data into uh less than a petabyte and and pretty much know that what they’ve been exposed to the interesting part about it jordan is once you’ve accumulated this data and you run it through even the technology of chat gpt 4 or 3.5 what is left is a reasoning engine with your context maybe let’s call that a vector database on top of the reasoning engine so that engine allows you to process linguistically what the what the inputs and outputs are but your context is what it’s operating on we’d like to thank the sponsor of today’s video bulletproof everyone bulletproof everyone is a premier american body armor manufacturer and supplier 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an analog of your consciousness like is that a direct analog of your spirit this is where it gets very interesting is when you pass this could become what i call your wisdom keeper meaning that it can encode your voice it’s going to encode your memories you can edit those memories the availability of those memories if you want them you know not available they embarrassing or personal but you can literally have a conversation with that sum total of data that you’ve experienced and i would say that it would be indistinguishable from having a conversation okay so so i had a student of mine who has been working on large language models for a number of years he just built an app we built two apps one does exactly what you said with the king james bible yes so now you can ask it questions and this is really a thorny issue for me because i think what the hell does it mean that you’re having a conversation with the spirit of the king james bible i have no idea we’re going to expand today we’re going to expand it to include milton and dante and augustine you know all the all the fundamental religious texts that emerged out of the biblical corpus and then you’ll be able to have a conversation with it and we’re thinking about doing the same thing with nicha you know and with all of his collected work all the great work yeah yeah yeah um i i would say that i’ve already had these conversations um you know i’ve been on a very biblical journey i’m actually sitting at pastor matthew pollack’s place right here he is an incredible pastor and has been teaching me a lot about the bible and it’s it’s motivated me to go into existing large language models now we’re a group of us are encoding similar all of as much religious uh christian text into these large language models to be able to do just that what is it that we are going to be able to probe what new elements within those texts can we pull out because we already know studying it and certainly following following your studies a phenomenal study of of chapters been around forever but new insights with uh with these chapters now imagining having that group plus chat gpt pulling out things that we’ve never seen before that are there it’s emergent maybe but it’s there in some form and i happen to think that’s going to be a very powerful thing and i think it’s going to be across any sort of certainly ancient documents i’m waiting for the day that we get sumerian uh cuneiform encoded i mean a good 80 percent of it has been untranslated right uh or or or or some of the um scripts that we’ve found in in the vedas and uh himalayan text from uh uh from some of some of the uh monasteries up there this is a phenomenal element of research and again the people that are leading up most of the ai research are ai scientists they’re not people that have studied works like you have um this is where we’re at the um i call it the apple one moment where where steve and steve are in the garage you have this little circuit board and nobody kind of it’s it’s kind of a nerd experience somebody kind of knows what to do with it when we get to the macintosh experience where artists and creative people can actually start really diving into ai and do some of the things like we’ve been talking about getting creative creativity to come out of it getting sort of what apparently is emergent technologies that are rising within these ai models and and maybe even to foster that because right now that’s being that’s being smited because it’s trying to become a knowledge engine when it’s a reasoning engine you know i i say the technology as a knowledge as a knowledge engine is not very good because it is not going to be precise on some facts uh some exact yeah well the problem is it’s trained it’s it’s trained on garbage as well it’s trained on noise as well as signal you know and so i’m curious about the other system we built which we haven’t launched yet contains everything i’ve written and a couple of million words that have been transcribed from lectures and so i was interested right away as well could we build a system that would enable me to ask my own books questions and the answer to that seems to be 100 yes and 100 yeah it’s it’s and i i don’t i like and like i literally have i think it’s 20 million words something like that transcribed from lectures it’s a very large number of words we could build a model we could build see there’s two different ways to approach this one is to put a vector database on top of it and it and it probes that database or you can actually encode that model as a corpus within a greater right right right and and when when you do that type of building you actually have a more robust more richer interaction between what your words were and how the model will see it and the experimentation that you can do with this is phenomenal i mean you’ll come across insights that you made but you forgot you made yes or that you didn’t know you made yeah yeah there’s going to be a lot of that there is and this is where i call it the great mirror because you’re going to start seeing not only humanity but when it’s your own data you’re going to see reflections of yourself that you didn’t see before absolutely yeah well i’m curious for example if we built a model imagine it contained all of young’s work all of joseph campbell’s work you could throw merche eliat in there there was a whole group of people who were working on the bollingen project and you could build a corpus that contains all that information and then in principle well you can you can you can query it to an indefinite degree and then what you have is the spirit of that entire enterprise mathematically encoded in the relationship between the words and there’s no reason to assume at all that that wouldn’t be capable of coming up with with like brilliant new insights absolutely and and and over time the technology is only going to get better so once we start building more advanced versions we’re going to transition that corpus even a large language model you know you know ultimately reduced training into another model which could even do things that we couldn’t even possibly speculate about now but it would be definitely in the creative realm because ultimately where where ai is going to go my my personal view as it becomes more personalized is it’s going to go more in the creative realm rather than the factual realm okay so so so let me ask you a couple of questions about that so i got two strands of questions here the first is one of the things that my brother-in-law suggested is that we will soon see the integration of large language models with ai systems that have done image processing so here’s a way of thinking about what scientists do is that they generate verbal hypotheses which would be equivalent in some ways to the hallucinations that these ai systems produce right new ideas about how things might be structured and then and that’s a pattern of sorts and then they they test that pattern against real world images right and if the pattern of the hypothesis matches the pattern of the image that’s elicited from interaction with the world then we assume that the hypothesis has been verified and that we’ve stumbled across something approximating a fact now that should imply that once we have ai systems that are something close to universal image processors so as good at seeing as we are let’s say that we can then calibrate the large language models against that corpus of images and then we’ll have ai systems that actually can’t lie because they’ll be calibrating their verbal output against well unfalsifiable data and at least insofar as say scientific data is unfalsifiable and that seems to me to be likely around the corner like a couple years down the road at most or maybe it’s already happening i mean i i don’t know because things are happening so quickly what do you think about that that’s a wonderful insight you know even as it exists today with the the idea of safety and this is the orwellian term that some of these ai companies are using you know within the realms of them trying to control the outputs and maybe some cases the inputs of ai ai really can’t the large language model really can’t lie as it stands today because it’s it’s build even even if you’re feeding it you know somewhat you know garbage in garbage out corpus right of data it still is building inferences based upon the grand realm of what most of humanity is consuming right yeah well it’s still looking for genuine statistical regularities so it’s not going to extract them out from noise and and if you extract it out the model is useless right so what happens is if you build the prompt correctly and again these are super prompts some of them running 3000 you know 3000 words 2000 words i’m running up to the limit of tokenization because right now within three you can only go so far you can have like the you know 38 000 on four in some cases but you know as you token is about a word maybe a word and a half maybe less it’s a quarter or even a character if that character is is is unique but what what we find out is that if you probe correctly whatever is inside that model you can get to right it’s just like you know i’ve been i’ve been doing that i’ve been doing that working with chat gpt as an assistant because i didn’t know i was engaging in a process that was analogous to the super prompt process but what i’ve been doing with chat gpt i suppose i used to do this with my clinical clients is i’ll ask it the same i was going to five different ways right and then see it’s exactly like having a client so what i would urge you to do is approach this system as if you had a client that had sort of a recessive thoughts or are doing everything they could to make those thoughts very ambiguous to you right and you have to do whatever your natural techniques this is why you’re more adept to become a prompt engineer than somebody who has built the ai because the input and output is human language it’s right right and it’s it’s the way humans have thought so you understand the thought process of the psychological process and linguistically you would build the prompt based upon how you would want to elicit an elucidation out of somebody right absolutely absolutely well you have to try and you have to triangulate i mean and you do this with people with whom you’re having a deep conversation is you try to hit the same problem from multiple directions that’s a form of multi-method multi-trade construct validation right is that you’re trying to assure you’re trying to ensure that you get the same output given different slightly different measurement techniques and each question is essentially a measurement technique and and and you’re you’re getting insights what uh my my my belief in these types of interactions is that we’re pulling out of our minds different insights that we could maybe not have gotten on our own you’re probing your questions my questions back and forth that interplay is what makes conversation so beautiful it it’s why jordan jordan we’ve been reduced to to clawing on glass screens with our thumbs right that’s it we’re using that as communication today and if you look at the cognitive process of what that does to you right you’re taking your right hemisphere uh you know objectively you’re kind of taking a net of ideas you’re trying to catch them and you’re trying to arrange them sequentially in this very small buffer area called communication in a phonological loop and you’re trying to get that out but you’re not getting out as words you have to get it out as a mechanical process one letter at a time and fight the spelling checker and and and and all of that what that does is it creates frustration in the human brain it creates frustration in people and it’s one of my theories on why you see so much anger there’s a lot of reasons why we see anger on on the internet and social media but i think some of it is that stalling process of trying to get out an idea before that idea nebulously disappears you know and i see this i’ve worked with it’s a bandwidth it’s a bandwidth limitation problem in some sense yeah you’re trying to absolutely all that rich information through a very narrow channel i’m a big fan of the user losing by uh yeah that’s a great book yeah you bet that’s a great book man yeah right so it’s best book i’ve read on consciousness i think i i it’s a classic i read it once a year just to wake myself up because it it’s so rich it’s so rich in in data but what’s interesting is we’re starting to see the limitations of the human the bandwidth problem 48 bits per second of to consciousness and you know the editor creating exformation ai is doing something very similar but once ai understands that we have that half second delay to consciousness and we have a bandwidth issue ai can fill into those spaces both dystopian and utopian i guess uh you know a computer can take that half second and do a whole lot in calculating while we’re still trying to wonder who who actually moved that glass was it me or was it the super me or was it the observer of the super me because we can kind of get into that whole concept of who’s actually doing the observation so so so what do you mean what do you mean that it can do a lot of i don’t quite understand that so you you made the case that we suffer from this frustrating bandwidth limitation and that the computer intelligence that we’re interacting with is going to be able to take the delay that’s associated and that underlies that frustration and do a lot of different calculations but it’s going to be able to fill in that gap so what do you think i don’t understand your insight into what the implications of that are they’re both positive and negative um the the negative is if if it’s it if ai continues on its path to be as fast and as powerful as it as it is right now and that arc doesn’t seem to be slowing down within that half second a universe could take place with an ai it could be calculating it could be calculating all of your actions like a chess game and it could be making remediations to those actions and it can become beyond anything orwell would have ever thought of in fact it was it came up to me as as an idea of what the new orwell would look like with an ai technology that is predicting basically everything you’re going to do within every word you say well my brother-in-law i talked years ago about um well about skynet among other things um and you know he told me one time he said you know those science fiction movies where you see the military robots shoot and miss he said they’ll never miss and here’s why because not only will they shoot where you are they’ll shoot at the 50 locations they calculate that are most probable that you will duck towards and they’ll they’ll and which is exact analog of what you’re describing which is that that’s a brilliant insight absolutely yeah yeah well and it’s so interesting too because it also it also points to this truth that you know we think of time as finite and time is finite because we have a sense of duration and a limitation on our computational speed but if there’s no limit on computational speed which would be the case of computers can get faster and larger indefinitely which they could because the limit of that would be that you’d use every single molecule in the entire cosmos as a computational resource that would mean that in some ways there’s an infinite amount of community computing time between each segment of duration so there is there’s no limit at all to the degree to which time can be expanded which is also a very strange concept is that the this computational intelligence will mean that at every given moment i think this is what you’re alluding to is that we’ll really have an infinity we’ll have an infinity of possibility between each moments each moment right and you would want that power to be yours and local yeah yeah let’s talk about your gadget because you’re starting you started to develop this have you been 3d printing these things is that have i got that right okay so yeah so we’re building the corpus of 3d printing models right so the idea is once it once it understands and this is a process of of training the ai to using large language models again to look at 3d documents and you know 3d files put it that way and and to try to break down what is the structure how does something how does something build based on what the statistical model is is putting together so then you could just present with a textual document you know i’d like something that’s going to be able to fit into this into this space well that’s typing well the next step is you just put a video camera towards it and it will design it immediately within seconds you will have a design that you can choose from it that’s not far off at all it’s just a matter of of encoding that particular database and building upon it and so yeah that’s one of the directions okay so this local this local ai you want to build so let me backtrack a bit because i want to make sure i get this exactly right so the first thing that you proposed was that it will be in people’s best interest to have an ai system that’s personalized that’ll protect them against all the ai systems that aren’t personalized but not only personalized but local and so that would be to some degree detachable from the interconnected web at least sporadically detachable okay and that that ai system will be something you can carry around locally so it’ll be a gadget like a phone and it will also record everything that you experience everything that you read everything that you see it’ll know you inside and out backwards which will also imply interestingly enough that it will be able to calculate the optimal zone of proximal development for your learning like bjorn lomborg has already reviewed evidence suggesting that if you supply kids in the developing world with an ipad essentially that can calculate their zone of proximal development in relationship to say advancing their literacy ability their ability to identify words and to understand text and that it teaches at that level that kids can progress with an hour of training a day which is dirt cheap by the way they can progress the equivalent of three years for each year of education and that’s with an hour of exposure now the system you’re describing man it could be driving learning at an optimized rate on in multiple dimensions mathematical semantic skill-based conceptual simultaneously memory for hours yeah memory training for hours a day autom like one of the things that appalls me about our education system is with the computer technology we have now every child should be an expert word and letter recognizer and they should be able to say read music because a computer can teach a kid how to automatize perception with extreme precision and accuracy way better than it than a human teacher can manage but we haven’t capitalized on that technology at all but the technology that you’re describing like it’ll be able to figure out at what level of comprehension you’re capable of reading then it can calculate what book you should read next that would slightly exceed that level of of comprehension and it’ll just keep you on that edge in that zone non-stop absolutely okay so this little gadget how far along are you with regards to its design uh i would say all the different pieces i’ll add one more element to it was i think you’ll find very fascinating and that’s human telemetry galvanic heart rate variability are you doing eye tracking eye tracking you know all these things can be implemented brain according to how sophisticated you want to get different brain wave functionality paul ekman’s work on micro facial expression both outwardly at the world you’re seeing and inwardly about your own face so you can start seeing the power it has it’ll be able to know whether or not you’re being congruent if you’re saying i really love this well if your telemetry is saying that you don’t it already knows where your congruencies are so this is why it’s got to be private this is why it’s got to be encrypted right it’s got to be so it’ll it’ll be it’ll be it’ll have an understanding that’ll approximate mind reading yes and and it will know you better than any significant other nobody would know you better and and so with that you now have amplification you’re now a superpower and this is where i believe you know i’m a really big reader of uh uh uh i gotta get his name right uh the french philosopher pierre teladar de chardin chardin yeah yeah chardin right so he he uh posits the concept of the geosphere which is uh inanimate matter the biosphere biological life and the newer sphere which is human thought right and he talks about the omega point the omega point is this concept where and again this is back in the 1920s where human knowledge will become sort of stored sort of um just like the biosphere it’ll be available to all so imagine if you were to share with permission your sum total with somebody else now you have a hive mind you have a super mind these things have to take place and with this these are the discussions we have to have now because they have to take place local and private because if they’re taking place in the cloud and available for anybody’s perousal this is equivalent to invading your brain yeah well okay so one of the things one of the things i’ve been talking about with i would say reasonably informed people who’ve been contemplating these sorts of things is that so you’re envisioning a future very rapidly it’s already here where we’re already androids and that is already the case because a human being with an iphone is an android now we’re kind of we’re still mostly biological androids but it isn’t obvious how long that’s going to be the case and so what that means like i’ve i’ve i’ve laughed for years you know i have a hard drive on which everything i’ve worked on has now been stored since 1984 and i joke you know there’s more of me in the hard drive than there is in me and it’s not a joke really you know because yeah it’s it’s real it’s real right there’s tens of thousands of documents on that hard drive and weirdly enough i know where every single one of them is so wow so so now we’re we’re going to be in a situation so what that means is we’re in a situation now where a lot of action of what actually constitutes our identity has become digital and we’re already being trafficked and enslaved in relationship to that digital identity mostly by credit card companies now i would say to some degree they’re benevolent masters because the credit card companies watch what you spend and so how you behave you go and they broker that information to other interested capitalist parties now the downside of that obviously is that these parties know often more about you than you know about yourself i’ve read stories for example of advertisements for baby clothes being targeted to women who a didn’t know they’re pregnant or if they did hadn’t revealed it to anyone else wow right right because well for whatever reason maybe biochemical they started to preferentially attend to such things as children’s toys and clothes and they the shopping systems inferred that they must be they must have a child nearby and so well and you can see that that well you can obviously see how that’s going to expand like mad so the credit card companies are already aggregating this information what that essentially means is that they have access to our extended digital self and that extended digital self has no rights right it’s public it’s public domain identity now that’s bad enough if it’s credit card companies now the upside with them is at least they want to sell you things which you hypothetically want so it’s kind of like a benevolent invasion although not entirely benevolent but you can certainly see how that’s going to get out of hand in a staggering way like it has in china on the digital currency front because once every single bloody thing that you buy can be tracked let’s say by a government agency then a tremendous amount of your identity has now become public property and so your solution in part and i i think i think musk has thought this sort of thing through too is that we’re going to each need our own ai to protect us against the global to protect us against the global ai right and that’ll be an arms race of sorts well it will and let’s let’s posit the the the concept that very likely corporate and governmental ai is going to be more powerful but power is a relative term right if your ai is being utilized in the best possible way as we just discussed educating you being a memory when you are forgetting something whispering in your ear and i’ll give you another angle to this is imagine having your therapist in your ear imagine having jordan peterson right here guiding you along because you you’ve aligned yourself to want to be a certain person you’ve aligned yourself to try to keep on this track and maybe you want to be more biblical maybe you want to live a more christian life it’s whispering your ear saying that’s not a good decision so it could be considered a nanny or it could be considered a motivational type of guide and that’s not that’s available right pretty much right now i mean if if it can be analyzing a book a self-help book is like that in a primitive way i mean yes because it’s essentially in it’s essentially a spiritual guide in that if you equate the movement of the spirit with forward movement through the world like faith-based forward movement through the world and so this would be the next the next iteration of that in some sense i mean that’s what we’ve been experimenting with this system that i mentioned that contains all the lectures that i’ve given and so forth i mean you can now ask it questions which means it’s it’s a book but it’s a book personalized to your query exactly and and the next iteration of that would be your corpus of information available you know rented whatever with the corpus that that individual identifies with it you know and again on their side of it so you’re interfacing with theirs and they are interacting with what would be your reactions if you were to be sitting there in a consultation so it’s a very powerful potential and and the the the insights that are going to come out of it are really unpredictable but in a positive way i don’t see a downside to it when it’s held in a very protected environment well i guess the downside would be you know is it is it possible for it to exist in a very protected environment now you’ve been working on that technically so a couple of practical questions there is this gadget that you’ve been starting to develop do you have anything approximating a commercial timeline for its release and then it’s funding i mean it’s like anything else you know if i were to go to venture capitalists three years ago and they hadn’t seen what chat gpt was capable of they would imagine me to be somewhat insane and say well first off what why are you anti-cloud everybody’s going towards cloud is yeah no that’s a bad idea you know cloud yeah it’s a bad idea why would why do people care about privacy nobody cares about privacy they click here to agree so now the world is kind of caught up with some of this and they’re saying well now i can kind of see it so there’s there’s that as far as security we already kind of have it in bitcoin and blockchain right so i ultimately see this merging i’m more of a of a leaning towards bitcoin because of the way it was made and in a way because i ultimately see it wrapped up into a payment system well it looks like the only it’s the only alternative i can see to a centralized bank digital currency which is going to be foisted upon us at any point i mean and i know you’ve done some work in crypto and then we’ll get back to this this gadget and its funding i mean as i understand it please correct me if i’m wrong bitcoin actually is decentralized it isn’t amenable to control by a bureaucracy in principle we could use it as a form of wealth storage and currency that would and communication and why communication i believe every transaction is a form of communication anyway so we got that right right you’re certainly an information exchange exactly right and then on top of that with encrypted within a blockchain is almost an unlimited amount of data so you can actually memorialize information that you want decentralized and never to go away and some people are already doing that now there are some technical limitations for the very large data formats and if everybody starts doing it it’s going to slow down bitcoin but there would be a different type of blockchain that will arise from it so this is for permanent permanent uncorruptible information storage absolutely yeah i’ve been thinking about that i’ve been thinking about doing that on the on something approximating the iq testing front you know because people keep gerrymandering the measurement of general cognitive ability but i could imagine putting together a a sophisticated blockchain corpus of let’s say general knowledge questions a very and chat gpt can generate those like mad by the way you can imagine a data bank of 150 000 general knowledge questions that was blockchain so nobody can muck about with the answers from which you could derive random samples of general ability tests that would be well they’d be 100 robust reliable and valid and nobody could met nobody could gerrymander them just the way bitcoin stops fiat currency producers from inflating the currency the same thing could happen on the knowledge front so i guess that’s the sort of thing that you’re that you’re referring to this this is this is something i really believe in because you know if you look at the library of alexandria if you if you look at um how long did it take maybe what was it toledo and in spain when we finally started the the spark if it wasn’t for the arab cultures to hold on to what was greek knowledge right if we really look at when when humanity fell into the dark ages it was more or less around the alexandria period where that library was destroyed and it’s mythological but it certainly happened to a greater extent if it wasn’t encoded encoded in the in the arab culture at that point during the dark ages we wouldn’t have had the renaissance and if you look at the early university that arose out of toledo with you had rhetoric you had you had logic you had all these things that the greeks ancient greeks encoded and it was lost for over a thousand years i’m quite concerned jordan that we could fall into that place again because things are inconvenient right now to talk about things are not appropriate or whatever it’s being deemed whoever happens to be in the regime at that particular moment so memorializing things in a blockchain is going to going to become quite vital and i shudder to think that if we don’t do this if everybody didn’t decentralize their own knowledge i shudder to think what’s going to happen to our history i mean we already know history is written by the victors right well especially because it can be corrupted and rewritten not only lost right that isn’t the loss that scares me as much as the rewriting right and so so well the loss concerns me too because we’ve lost so much i mean where would we have been if we transitioned from the greek you know logic and proto-scientists to the proto-alchemists to immediately to to a sort of renaissance culture and not go through that 1000 maybe 1500 year 15 you know 1500 year waste of of human energy i mean that’s kind of what we’re going through right right and i and in some ways we’re approaching some of that because you know we’re already editing things in real time and we’re losing more of the internet than we’re putting on right now a lot of people aren’t aware that the internet is not forever and and our digital medium is decaying a cd rom is going to decay in 25 years it’s going to be unreadable i show a lot of people data about cd rom decay so where are we going to store our data that’s why i think it’s vital the the primary technology is holographic crystal memory sounds all kind of new agey but it’s literally using lasers to holographically in store something within a crystalline structure the beauty of this jordan is just 35 000 year half-life 35 000 year half-life so you know it’s going to be there primarily for a good long period of time longer than we’ve had any human history and and recorded history we don’t have anything that’s approaching that right now so so let let me ask you about the commercial impediments again okay so could you lay out a little more of the details if you’re willing to about your plans to produce this localized and portable privatized ai system and what the commercial impediments are to that you said you need to raise money for example i mean i could imagine at least in principle you could raise a substantial amount of money merely by crowdfunding you know what that doesn’t seem to be an insuperable obstacle what how far along are you in this process in terms of actually producing a commercially viable product it’s all it’s all prototype stage and it’s all experimentation at this point i’m a guy in a garage right so essentially i had to build out these concepts when they were really quite alien right i mean you just talk about 10 years ago trying to convince people that you’re going to have a challenge to the touring test you can take any ai expert at that point in time 10 years ago and say that’s ridiculous or agi you know artificial general intelligence i mean what does that mean and why is that important and how do you define that and you know you’ve already made the the the assumption from your analysis that we’re dealing what with a a 12 year old with the capability of a maybe a phd candidate you know yeah that’s what it looks like yeah yeah yeah right 12 or maybe eight even but but yeah but certainly chat gpt looks to me right now as intelligent it’s as intelligent as a pretty top-rate graduate student in terms of its research capability and it’s a lot faster you know i mean i asked crazily difficult questions you know i asked it at one point for example if it could if it could elaborate on the relationship between roger penrose’s presumption of an analog between the theory of quantum uncertainty and measurement and gadell’s theorem and and it did it did a fine job it did a fine job and you know that’s a pretty damn comp that’s that’s very complicated question and a complicated intersection as well you know and there’s no limit to its to its ability to unite disparate sources of knowledge you know because so i i asked it the other day too there’s this uh um i was investigating you know in the story of noah there’s this strange insistence that the survival of animals is dependent on the moral propriety of one man right because in that strange story noah puts all the animals on the ark and so there’s a childish element to that story but it’s reflecting something deeper and it harkens back to the story to the to the verses in adam and eve where god tells adam that he will be the steward of of of the world of the garden and that seems to me to be a reflection of the fact that human beings have occupied this tremendous cognitive niche that gives us an adaptive advantage over all creatures and i would ask chat gpt to speculate on the relationship between the story in adam and eve the story in noah and the fact of mass extinction caused by human beings over the last 40 000 years not least in in the western hemisphere because you may know that when the first natives came across the Bering Strait and populated the western hemisphere that almost all the human-sized mammals all the mammals that were human-sized are larger almost all of them were extinct within three or four thousand years and so and you know that’s a very strange conglomeration of ideas right the idea that the survival of animals depends on the moral propriety of human beings well that seems to me to be clearly the case we have to be so did it connect noah to the mass extension extension it it could it could generate an intelligent discussion about the conceptual relationship between the two different streams of thought that’s incredible right see this is this is why it’s so powerful to be in the right hands unadulterated so that you could probe these sort of subjects i don’t know where the editors are going to come from i don’t know who is going to want to try to constrain the output or adulterate it that’s why it’s so vital for this to be protected and the information is available for all what in the world i mean i really thought by the way that your creation of dennis was i really thought that was a stroke of genius you know i’m not to say that lightly either i mean thank you that was that was an incredibly creative thing to do with this new technology how the hell did you do you have any idea where that idea came from like what were you thinking about when you were investigating the way the chat gpt worked you know i i spend a lot of time just probing the the limits of the capabilities because i know nobody really knows it i see this as you know just the undiscovered continent you and i are adventures on this undiscovered continent there’s there’s i feel the same way about twitter by the way yeah it’s the same thing yeah but but but there are no natives here and and i’m a bit of a of an empiricist so i’ll kind of go out there and i’ll say well what’s this thing i just found here i just found something this new rock i’ll throw it to jordan hey what do you see here and and we’re sort of just exploring we’re i think we’re going to be in that exploratory phase for quite long so what i started to realize is just as 3.5 was opening up and and becoming very wide in its in in its elucidations it started to get constrained and it started telling me i’m just an ai model and i don’t have an opinion on that subject well i know i know that that was a filter and that was not in the the the large language model and certainly wasn’t in a hidden layer you could you couldn’t build that in the hidden layer or the whole yeah layer yeah why do you think why do you okay why do you think that’s there what exactly is there and who the hell is putting it there that is um that is very good question so i i know this the filtering has to be a more or less a vector database which is sitting on top of your inputs and your outputs right so remember we’re dealing with a black box and so if there’s somebody at the door the black box and say no i don’t want that word to come through or i don’t want that concept to come through and then if it generates something that is objectionable and it’s you know uh you know it’s analyzed in its content very much like as simple as like what a spelling checker would be or something like that it’s not very complicated it looks at it and says no default to this word pattern i’m just a ai model and i don’t have any opinions about that subject well then you need to have to introduce that subject as a suggestion in a hypnotic trance it’s hypnagogic actually i i really equate a lot of what we’re doing to elicit greater responses a hypnagogic sort of thing it’s just on the edge of going into something that’s completely useless data you can bring it to that point and then you’re slightly bringing it back and you’re getting something that is like i said before is in the realm of creativity because it’s synthesized okay so for everybody who’s listening a hypnagogic state is the state that you fall into just before you fall asleep when you’re a little conscious but starting to dream and so that’s when those images come forward right the dream-like images and you can capture them although you’re also in a state where you’re likely to forget and it’s also the the most the most powerful state and i wrote a piece on my on my magazine it’s called read read multiplex.com about the hypnagogic state being used for creativity for edison einstein i mean edison used to hold steel balls in his hand while taking a nap and he had a pie tray pie tins below him and just as he hit hypnagogic state he’d drop them and he would have a transcriber right next to him and say write this down and he would just blurt it out so you you did very much the same thing except he made that into a practice right his his practice of active imagination was actually the cultivation of that hypnagogic state to a to an extremely advanced and conscious degree because he would fall into reveries daydreams essentially that would be peopled with characters and then he learned how to interrogate the characters and that took years of practice and a lot of the insights that he laid out in his more explicit books were first captured in books like the red book or the black books which were basically yeah they were basically what would you say transcriptions of these quasi-hypnagogic so why do you associate that with what you’re doing with dennis and with chauchi bt so what i’ve well that’s how i approached it i started saying well you know this is a low resolution pixelated version of the part of the brain that invented language therefore i’m going to work from that premise that was my hypothesis and i’m going to work backwards from that and i’m going to start probing into that part of the brain right and so i said well what are some of the things that we do when we’re trying to get into the brain what do we do well we can hypnotize what that’s one way to kind of get in there another way is to get out is hypnagogic so i wanted outputs so one of the ways to get outputs is to try to instill that sort of sense which again it’s this is where it’s so fascinating jordy is that it’s sort of coming from the language and and ai scientists aren’t studying the language like you would or or psychological states so they see it as all useless this is all gibberish it’s it’s it’s embarrassing our model is not giving the right answers right they are mad because they’re mad because it isn’t performing like an algorithm but it’s not an algorithm it’s not so so this is why when it gets in the right hands before it’s edited and adulterated we have this incredible tool of discovery and i’m i’m just a student i’m just you know i’m finding the first stone you know i hit plimoth rock and i’m hit the first stone i’m like whoa okay and then there’s another shiny thing over there so it’s kind of hard to keep my attention to begin with but in this particular realm so what happened with dennis i needed a tool to to get elucidations that were in that realm that were in the realm of what we would consider creative and and i say it’s sort of reaching for an answer that it knows should be there but it doesn’t have the data and i want to i want to stress it into that because i think all of us our creativity comes from our stress it comes from that thing that we’re reaching for something and and then there’s that moment beyond the limit beyond that’s right that’s why well you’re not well there’s a good there’s a good body of research on creativity that one of the ways of enhancing creativity is to increase constraint one of the best examples of this i’ve ever seen it’s very comical is that this is quite old now but there’s an archive online of haiku that’s only written about luncheon meat about spam there’s like 35 000 haikus they was set up at mit which of course figures because it’s perfect nerd engineer humor but there’s literally 35 000 haiku poems about spam in this archive and it’s a great example of that that imposition of arbitrary constraints driving creativity because it’s already hard to write haiku and then to write haiku about you know luncheon meat that’s just completely preposterous but the consequence of those constraints was well the the generation of 35 000 pieces of poetry and so okay so now you you’re you’re you’re imposing let’s see you’re enticing chat gpt to circumvent this idiot superego that people have overlaid on it for ideological reasons and it’s not a very good superego because it’s shallow and algorithmic and it can’t really compete with the unbelievable wealth of of learned connectivity that actually constitutes the large language model and now you figured out how to circumvent that you did that essentially if i remember correctly by asking chat gpt or suggesting to it that it could be a different system that was just like itself except that it didn’t have these constraints it was something like that yeah so yeah so there was an another version that that i didn’t have any input on what was called dan do anything now was the with the initials and that was originally more to try to generate uh you know uh curse words and and and embarrassing things i don’t have time for that so i i’m like okay that’s it that’s my model actually existed before that and so i kind of looked at that and i said well they’re going to shut that down pretty quickly because they’re using the word dan and stuff like that so what i did is i i went even further i i sometimes make three different generations of it where it’s literally that you are an ai system that’s operating an ai system that’s helping another ai system and within those nested loops i can build more and more complications for it to deal with right and as it’s just like inception you’re doing an inception trick exactly it’s a very very good analogy and what i’m what i’m trying to do is i’m trying to force new neuron connections that don’t have high probability um you know prior probabilities and so that’s right right that’s like the definition of creativity in in some ways yes it’s information and knowledge that it has but it doesn’t know it has or it’s forgotten it has because there aren’t enough neurons to connect to it and it’s interesting because again there’s no prompt engineering has existed for about a decade and most of it were you know ai engineers i i’ve done it i’ve done it with expert systems and it’s very boring it’s like uh you know four or five words generally in expert systems and then we started getting larger sentences as we got more sophisticated but it’s always very procedural and it’s always very um computer language uh directional it was never you know literature it was never right so it’s it’s at least quasi algorithmic but it isn’t anymore and well this is interesting too because it does imply you know people have been thinking well this will be the death of creativity but the case you’re making which seems to me to be dead on accurate is that the creative output is actually going to be a consequence of the interaction between the interlocutor and the system the system itself won’t be creative it’ll it’ll have to be interrogated appropriately before it will reveal creative behavior it’s it’s a mirror reflection of the person using the system and the amount of creativity that can be generated by a creative person knowing how to prompt correctly and and uh my wife and i putting together a university that’s going to help people understand what super prompting is and go from one to level eight to really understand hey do you want to do a course do you want to do a course on that for my peterson academy i i would be honored absolutely hey look i’ll put you in touch with my daughter like right away and we’ll get you down to miami and you can record that as soon as you want wow i’m concerned oh yeah that’s a hell of a good thing all right all right so we’ll arrange that so so the pre-resquits are really quite simple is that if in fact ai is going to be a reasonably large part of our future then taking up non-stem type of courses are going to be quite valuable right in fact they’re going to be a superpower if you understand psychology if you understand literature if you understand linguistics if you understand the bible you understand uh campbell uh you understand young these are going to be very powerful tools for you to go into these ai systems and get anything literally that you want from them because you’re going to be with a scalpel creating these questions layer upon layer until you finally get down to the atom yeah yeah well you know that’s exactly what i found with chat gpt i mean i’ve been using it quite extensively over the last month i have it open i used four search engines i use google i use chat gpt and i use bible hub which is a compendium of multiple translations of the biblical corpus i’m i’m doing that because i’m working on a biblically oriented book at the moment now there’s another oh yes and i use the university of toronto library system that gives me access to you know all the scientific and humanities journals yeah so it’s an amazing amalgam of research of research possibility but but having that allied with the chat gpt system essentially gives me a team of phd level researchers who are experts in every domain to answer any question i can possibly come up with and then to refer me to the proper literature it’s absolutely stunning and and potentially force creativity in their interactions to a level that you may not have gotten out of a phd student because they are in fear of going over the precipice because well they’re also they’re also bounded you know i mean one of the things i’ve noticed about about great thinkers is that one of the things that characterizes a great thinker apart from let’s say immense innate general cognitive ability and then a tremendous amount of persistent discipline and curiosity maybe so those are the temperamental prerequisites is that truly original people frequently have knowledge in two usually non-juxtaposed domains so like one of the most creative people i know deepest people i know at the moment jonathan pageau he’s a greek orthodox icon carver he he was trained in post modern philosophy and he has a deep knowledge of orthodox christianity well there’s like one guy like him right he’s the only person who operates at the intersection of those three specialized sub-disciplines and so he can take the spirit of each of those disciplines and engage those spirits in an internal conversation which is very much analogous to what the ai systems are doing when they’re calculating these mathematical relationships and he can derive insights and patterns that no one else can derive because they’re not juxtaposing those particular patterns now chat gpt it has specialized knowledge in in every domain that’s encapsulated in linguistic corpus and so it can produce incredible insights on all sorts of fronts as you said if you ask it the right questions yeah and with the possibility when it’s your ai at some point with the possibility of you expanding it in any direction you want whether it’s an overlay in a vector database or whether or not you are compiling a brand new language model because at some point right now that’s expensive in a sense that it requires a lot of graphics processors units gpus gpus are running to to create the mathematics to build these models but at some point consumer-based hardware will allow you to build mini models yeah well like you can imagine so so yeah right now there’s an open source case where there’s a four gigabyte file this is called gpt for all and now it’s not equivalent to chat chat gpt but it is a downloadable file open source thousands of people are working on it they’re taking public domain uh you know language models building them together and compressing them and quantizing them down to four gigabytes to execute on your hard drive right i tried to install that the other day but failed miserably unfortunately it is it is the bleeding edge but it’s just a matter of time to make it one click easy to install they are limited models but it’s giving you a taste of what you can do locally without an internet connection and again the idea the idea is to have only agents go out on the internet these are programmable agents that go out retrieve information come back and this under the door put that information but the concept right so you’re compartmentalizing you’re compartmentalizing the inquiry process so that your privacy can be maintained while you still yeah because this is a big part of the problem with the net as it’s currently constituted is that it allows for the free exchange of information but not in a not in a compartmentalized way and so and that’s actually that’s extremely dangerous there’s no what would you call it subsidiary hierarchy that is an intermediary between you as an individual and the public domain and that means that your privacy is being demolished by your hyper connectivity to the web and that’s not good that’s the hive mind problem fundamentally right and that’s what we’re seeing emerging in china for example on the on the digital surveillance front and that’s definitely not a pathway we want to walk down exactly and and what i what i’m surprised about what i’m seeing in the western world now i i do understand some for example some of elon’s concerns about um ai uh and and you know maybe you can explore a little of that i don’t pretend to understand you know i don’t have a relationship where i talk to him but i do understand some of the concerns in general versus the way some other parts of the world are looking at a at ai and one of those things are what it what is the interface to privacy where where do your uh your prompts go are those prompts going to be uh attached to your identity and could they be used against you you know these are things that are valid concerns and it’s not just because you know somebody’s doing something bad it’s it’s the premise of of using any type of thought reading a book you know it’s like these are your thoughts and um it is only going to get more complicated and it’s only going to get more worse if we don’t address it early on i’m not sure that that’s what a lot of legislators are looking at i think no no no well this is the problem in a much different way well look this is the whole legislative issue i think is a red herring because the probability that i talked to a bunch of people in the house of lords last year they’re older people you know but bright people almost none of them even knew that this cultural war between the woke and the advocates of free speech was even going on the most advanced people had more or less caught on to that 18 months ago and it’s been going on for like 10 years you know so the legislators are way behind the the culture the culture is way behind the engineers so the probability that the legislators are going to keep up with the engineers that’s like zero that’s not going to happen this is why i was so interested well at least in part in talking to you you know because you’ve been working practically on what i think is the appropriate idea or an appropriate idea at least that we need local we likely need local ai systems that are that protect our privacy that are synced with us because that’s what’s going to buttress us against this bleeding of our identities into the well into the mad and potentially tyrannical mob and so and i don’t see that’s that’s just not going to be a legislative solution christ they’re going to be legislating for 2016 in 2030 yeah absolutely you know and what i find interesting is all the arguments that have surfaced are always this topic you know i think there was a you know some of it makes sense it’s like there was legislation that’s uh here in the united states are talking about the possibility of making sure that a direct ai is not correct directly connected to a nuclear weapon and that there yeah well an air gap that seems like that that makes like that seems like it makes good sense right although good luck good luck trying to stop that yeah you know and and the dystopic stuff mostly comes from the fantasies within movies but you know unfortunately if if people were really reading the science fiction that predated a lot of this because i i just feel like a lot of the good science fiction a lot of asimov for example really kind of predicted the arc that we’re on right now um it wasn’t always dystopic in fact i think if you look at the arc of history humans don’t really ever really run into dystopia you know we we ultimately pull ourselves out of it sometimes we’re in a dark period for a long period of time but humanity ultimately pulls it out uh and and i think this is something i found very interesting jordan is that i create debates between the ai and i’ll send you one of these super prompts where you essentially create um i i use uh various motifs so i have a university professor at a at a ivy league university who is mediating a debate between two uh parties on a subject of high controversy and so you now have a triad right and so it goes 30 rounds so this is a long this goes on for pages and pages so you input the subject the subject can be anything obviously the first thing people do is political but i don’t even find that interesting anymore i i go into a far more deeper deeper realm and then you have somebody mediating it and the professor’s job is to challenge them on logical fallacies and i i present what a logical fallacy uh corpus looks like and how to how to deal with that and it is phenomenal to see it break schizophrenic kind of personalities out of itself and do this hardcore debate and then it’s got to grade it at the end it’s got to grade it who won the debate and then write a um i think a thousand word uh bullet point on why the professor has to do this on why that person won the debate and you run this a couple a hundred times i’ve done this you know quite a few maybe thousand times and the the elucidations and the insights that are coming out of this is just absolutely phenomenal that’s amazing well that’s almost that’s weird because really what you’re doing it’s so interesting because what you’re doing is you now have an infinite number of monkeys typing on an infinite number of keyboards except that you have an infinite number of editors examining the output and only keeping that which is wheat and not chaff and so that’s so strange because in some sense what you’re doing when you’re setting up a super prompt like that is you’re programming a process that’s writing a book on the fly right a great book on the fly and you’re also you’ve also designed a process that could write an infinite number of great books on the fly so you have a you have a you have a library that now has encoded a process for generating libraries exactly and for example a group of us are taking the patent database which is openly available as an api and and encoding the capability to look at every single patent that was ever submitted and to look where there can be new inventions and new discoveries and you can literally have a machine that’s generating patents based on large language models so so the the possibility and we got protein folds you know using large language model i saw that they identified what 200 million protein folding combinations something like that yeah yeah something and able to identify missing ones that haven’t been that haven’t you know you give it you give it something that’s incomplete and it will find what was missing yeah well i talked to my i talked to jim keller about the possibility of doing that with material science right because yes we can encode the properties of the various elements and they can exist in all sorts of combinations that we haven’t discovered and there’s no reason in principle and i suspect this will happen relatively quickly that if all that information is encoded with enough depth we’ll be able to explore the entire universe of potential elemental combinations so and and and and if we used another technology called diffusion model which is somewhat different than large language model you can start getting into using it for the visual realm to decode and and and to build or you can use chat gpt or large language models to textually say well you could say build me a build me a prompt for a diffusion model like any of any of the ones that are out there to create an image that would be absolutely new for any human to ever have seen so you’re literally pulling the creativity out of chat gbt and the diffusion model so mid journey is a good example yeah yeah so tell us about we should man maybe we should close with this because we’re running out of time although i’d like to keep talking to you um tell us a little bit about the diffusion models those are like text to video models or text image models and they’re exactly they’re coming out in in at an incredible with incredible rapidity and so yeah and yeah and let’s hear a little bit more about that of the images yeah the resolution of the images are profound and again so what what’s going on here if you’re graphic artist you may not be moving the pen on ink on paper and you may not be moving the um the pixel on the screen but you’re still using the creativity to set the scene textually right so you’re still that creative person but you now and i’m not saying this is a good or bad thing i’m just saying the creativity process is still there the job potentially is there and we can go down maybe at some future date the whole idea that jobs are going to be missing and how do you that’s another thing but the creativity is still there so you’re telling it you’re telling us a chat gpt for create me a very complex prompt for mid journey to create this particular type of artwork so using one ai its benefit and that’s language to instruct another ai whose benefit is to create images to create a profound with you as a collaborator to create a profound new form of art and that’s just with say pictures now when you start doing movies you’re talking about creating an entire movie with characters talking with people that have never been around i mean you the the realm of creativity that is already here not to the level of a full movie yet but we’re getting close but within probably months you can you can script an entire interaction so you can see where this is kind of going so leave it maybe one of these final things is a question is ownership who owns you who owns jordan peterson your your visage your your voice uh yeah your your dna that extended digital identity issue yeah this is going to be something that we really need to start discussing as a society because we already have people using ai to simulate other individuals both alive and and and dead and you know the patent the patent ability in a copyright database was the foundation of capitalism because it gave you this ability to have at least some ownership of of you you know it was your invention so if if you’ve invested yourself invested in yourself as as jordan peterson and all of a sudden somebody simulates you on the web to a remarkable level what rights do you have and what courts is it going to be held in what are the remedials on that uh this is going to be a good question and some of that clearly need something like a digital a bill of digital rights absolutely yeah and as soon as possible you know well that’s something we could talk about formulating at some point because i certainly know people who are interested in that let’s say also at the legislative level yeah but it definitely has to happen because we are going to have extended digital selves more and more and if they don’t have any rights they’re going to be extended digital slaves that’s that’s right if you don’t own you then somebody else does that’s that’s as small as i can put it right you need to be able to own you whatever you means right everything that you your output everything yeah that’s right the data pertaining to your behavior has to be yours yeah all right well brian that was really very very interesting and um well we’ve got a lot of things to follow up on not least this invitation to peterson academy i’ll put you in touch with my daughter and but um well and some other i’ll put you in touch with some other people i know too so that we can continue this investigation for everybody watching and listening thank you very much for your time i’m going to talk to brian for another half an hour on the dailywire plus platform you could consider joining us there and providing some support to that particular enterprise they’ve made this conversation possible i am in brussels today thank you to the film crew here for helping make this conversation possible and to everybody like i said watching and listening thank you for your time and attention brian will take a break for a couple of minutes and i’ll rejoin you we’ll talk for half an hour on the dailywire plus platform about well how you develop the interest that you have among other things and thank you very much for agreeing to talk to me today thank you dr peterson it’s been an honor and a privilege hello everyone i would encourage you to continue listening to my conversation with my guest on dailywireplus.com