00:00There's a couple times that you've referred to like sort of the centralization of the generative models as either Iris, or I would say definitely active inference model generative models applied to this as well, that you know they're sort of run by one set of people. One thing that, you know, we haven't gotten a chance to talk about, and we'll probably have to talk about more in a future conversation, is the notion of how do you decentralize the compressions of, uh, the knowledge that is integrated by those models into, you know, some sort of distributed data store.
00:34Because I've always viewed it more as that there would be many many different Irises, people often ask me why there isn't just one, and I mean, I think you know exactly why there shouldn't be just one, and that there would be some energy bound, uh, distributed data store that is taking these compressed tensors or compressed representations of knowledge as they are evaluated by or used by many different models, and stored in a secured way, uh, that many future models can build the representations from.
01:16I, I, I, I view it more like like there is a DNA strand that is the collective cultural ethos and world observations, and that these models are more like the molecules that do the correction when there is the replication of a DNA strand. And that ultimately is sort of the model that, you know, even you and I have not gotten much work into and really needs to develop, is that there needs to be sort of an evolution or a merging of these blockchain structures or just distributed data stores and the knowledge in its very dense form into that, beyond just, you know, like saving a copy of it, you know, something more fundamental.
02:02Yeah, I mean, that, like, literally so the conversation I mentioned earlier that I had yesterday, uh, like that exact idea, you, that was something that I was, I was, I was speaking with, um, you know, uh, Jordan Hall stuff about when we were discussing, you know, especially the role of something like blockchains, uh, the role of something like Bitcoin, when it comes to, and not Bitcoin specifically but proof of work, having something that is highly resilient that ends up being a kind of centralized repository for highly compressed encodings, uh, that can represent as a kind of, um, DNA over the space of emergent systems that have models, right?
02:39Because DNA itself was the way in which, like you're saying, these molecular mechanisms and all of the emergent structure above them, in its exploration of function space, yeah, created a feedback process that compressed down into molecular space representations of what works that can then be unpacked again and experimented with into function space. That's this DNA function, right?
03:14But that was all in the in the being a model world, but in the having a model world, we have to actually, because all of this becomes explicit, we have to become self sufficiently self-aware that we actually create, uh, or steer the creation of, a similar kind of, um, and this is weird because there's this duality here. It's a, if you did it on a blockchain, like like something like a Bitcoin, you want it to be capture-resistant so it could be highly centralized, but because it's capture-resistant, that centralization actually can become a tool that increases the capacity for decentralized coordination.
03:48Because if every decentralized system can contribute to it and take away from it to some extent, then it, they could focus on their attention on it without having to necessarily be tightly coupled with it except when they want to contribute to it, or or or, you know, decode from it, right? Because the decoding can always happen for free, the encoding comes with a cost if you want to inscribe. Yeah, but to the extent that anyone can benefit from decoding, like think about like what would happen if an advanced model were basically leaked and its weights were put onto the blockchain, right?
04:19Like now this may or may not be desirable at this point, like we might argue that we need a better container for that before it actually makes sense or could be advantageous, and that leaking a powerful model and and making it irreversibly accessible on something like a blockchain with respect to its weights or a compressed version of its weights, um, or a program that could generate those weights if that was a valid compression, um, you know, it's unclear whether that's desirable or not desirable right now.
04:52But my point is that these kind of mechanisms are almost with 100% certainty going to be the kind of, um, places where we encode these highly compressed distillations of our collective experimentation over over this space of of of computation, AI, and also complex coordination via systems, um, such as, uh, the entire other world of like proof of stake and exploration of distributing governance, decentralized economics, all of that kind of, uh, you know, that space where we're seeing a massive amount of experimentation right now.
05:33Um, we're seeing a lot of failure, we're seeing a lot of parasitism, we're seeing a lot of craziness, but we're also seeing the seeds of of potentially interesting or useful patterns, you know, to the extent that, you know, much like, uh, mutations, to the extent that those come into the world and actually provide value, um, how do you re-encode them into a space where anyone can then replicate those patterns in the world?
06:02Right, so if a particular DAO finds a set of configurations and weights over their mechanisms that actually gives rise to really positive capacity for a group to collaborate, coordinate, and and and be generative, as opposed to parasitic or extractive, um, that's a kind of pattern that should be encoded and shared, right? And it should be accessible with very low cost if not free, um, in something like a blockchain that cannot be easily captured or corrupted, uh, for for local interests of of any other entity on earth.
06:38So yeah, I mean I think exactly like the the degree to which something like an Iris is is centralized or decentralized, you know, it's an interesting question, because to some extent it's a question of, you know, adoption and evolution and and how all these different threads of that, um, system, um, come into usage locally, right? I mean obviously you you want to spread it far and wide and have those, um, sort of seeds cast upon the winds of potential throughout human, uh, interest and experimentation, such that, you know, they land and take root and grow in fertile soil.
07:13Um, obviously because we're humans people will try to use it for abuse as well and all these other things that we do, um, but but yeah, I mean, it's again, I really do see it as this recapitulation of this natural process at the level of having models as opposed to being models. And we are trying to figure out how to, you know, what it looks like to create the kind of social mechanism that is the analog of of DNA, right?
07:51Yeah, and there I I would add just in summary to try to link it all back together that, um, there definitely needs to be, this could very easily go wrong where it's it's trending towards reducing that uncertainty in our knowledge representations, right? I I've already seen over like two years years with GPT, first there was a very wide space where you could explore the long tail, you could talk about things that aren't well established, and more and more it's like there's a regulation into this is the way things are, and because they are controlling when that update happens it's harder and harder to do research to that.
08:21So whatever compression goes into that distributed data store, it needs to have that preference towards the exploration of the uncertain uncertainty, like you were you were speaking of, to, um, variational free energy versus what was it, expected free energy, expected free energy. Like there needs to be, uh, a tendency, not in our compression of knowledge to say well this represents truth in its totality, and rather this is a representation that is inherently mutating and changing over time, um, and something that is existing to expand our capacity over time, um, to exist and thrive, where our neural mechanisms of encoding memory of encoding models, um, are just a little bit too lossy for long-term.
09:10Yeah, and then there's kind of like a sedimentary dynamic there as well, where you, to some extent, the more, the longer that certain aspects of that model have remained stable, the more they kind of migrate down to a more, you know, a deeper and more stable structure. That doesn't mean that that layer can't be changed, it does, it does get more difficult to change, the more energetic constraints on that.
09:44Yeah, yeah, the more that you have energetic constraints, the more that you have dependencies, the more that you have a history of the world, uh, being congruent with that representation, it does get more difficult to change as it migrates down that, uh, stack. But uh, but the understanding is that the entire stack, all the sedimentary layers, even though proportional to their level they will be like, the top layers will be more volatile proportionately than the the bottom layers, but they are all subject to change if you have a, uh, you know, observations or empirical, uh, experiences of sufficient surprise, right?
10:18And we, you know, and that reflects what we are like as well, right, like we have, you know, we we can be shocked to such an extent that our entire world models, uh, it is revealed to us that our entire world models down to their core need to be recalibrated, uh, if we encounter experiences that are sufficiently outside of our model. Although unfortunately we increasingly are leaning into the tendency to to lean into confirmation bias and to try to say, you know, you know, I'm going to ignore the signals the world is giving to me, I'm going to try to force my model on the world.
10:53Again, it's like there's always a certain element of interplay between like whether it's beneficial to try to like put your model onto the world or allow the world to transform your model, but it always has to be in dialogue, and it becomes inherently totalitarian when you decide that no matter what I'm not going to change my model and I'm going to push all of the responsibility for transformation out onto the world as opposed to taking any of that, uh, in your own model.
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