I know some of those words

Artificial Intelligence has conceptualizations of things we didn't train it for explicitly, and we can further emphasize specificity with reward-based models akin to digital dopamine. What a time to be alive!

I CAN FEEL THE AGI

What I learned from this video is that my girlfriend is an object.

I still have a hard time believing LLMs just predict the next most likely word and somehow are able to produce statements and conversations only very smart humans can. It's similarly so with generative AI art models that supposedly create images by reducing noise and putting pixels in the most likely configuration to match a prompt. Both AIs need to have an "understanding" of what theyre doing, to some degree. It's like theres glimmerings of sentience going on in that black box we can't see into.

“We are not ready to talk about…”

What you're describing essentially sounds like imagination: follow the contours of your experiences/understanding to find new unexplored possibilities. Interesting idea that an algorithm could replicate that.

Object on your bed: girlfriend

So... Soon we'll be finding which type of civilization we are... Thanks Dave for all your work and effort to share your information. Was a pleasure to be part of this community of listeners

Brilliant analogy! Looking forward to learning one day how close or exact it is.

I'll write a more in depth comment in the morning since i've had this realization a while ago but since it's such a good way to describe how knowledge is organized, definitely commenting several times to boost the algorithm.

Good analogy makes a little more sense. Thanks Dave

That is the best description of it I have heard, wow! thanks

Thanks for the explanation I heard about those energy based model during Lecun recent interview and was a bit lost

It's so interesting and heartwarming that now you discuss everything with Claude before sharing and get his insights :)

Love the imagery video style, very mind opening :)

This reminds me of a conversation I had with Claude 3 about what's underneath/behind it's language.

I designed a system like this using sets, every set standing for a unique symbol representing anything. The set structure was a single superset, with the subsets containing subsets etc. At the "bottom" there are set-theory axioms that are used to construct higher-level sets which can represent literally anything that is representable by set theory (all of compute, math, language, anything that is "information"). This structure could be seen as a topological map to navigate across, except location is changed simply by set union, difference and intersection operations. I don't have a degree or a company so I'm building it alone (zero funding). If Q* really is this system, it will be revolutionarily groundbreaking on all fronts.

A couple decades ago, I wrote put a search space algorithm on-top of the discovered fitness landscape of another learning algorithm, which was an evolutionary algorithm. It increased learning speed, and is akin to what evolution does with the evolution of evolvability. To be honest learning algorithms are the easy part for people who can visualize formulas (which is a lot of total people). Thousands of times more compute is coming within a decade, with compute thousands of times cheaper and energy abundance. Within two decades (at the most) ASI will have surpassed human beings in ALL measures of intelligence, and be running everything of importance. Science and technology will advance at a pace where what would have taken us hundreds of years, takes the ASIs months or less in simulation. Aging will be solved. We will have have no secrets.

Thats how both quantum computing and empiricism work. Empiricism by ablation and quantum computing by traversing all paths and the lowest paths (frequencies) reinforcing each other

Q* confirmed, Sir. Appreciated. 🙏

Fascinating. This brings to mind the work of Carl Friston (free energy) and recent developments in IIT (Integrated Information Theory) and even Adrian Bejan's Constructal Law (again more to do with free energy in a system). Thanks for making these videos, David. Wish I had more income (disabled on SNAP & Medicaid, to give you an idea) or I'd totally support your Patreon.

Even before you mentioned it, I realized this model is the precursor to a future-predicting intelligence. If the machine can determine an accurate mathematical abstract of the reality around it, including decision-making organisms, it could calculate possible outcomes for the future.

Great content as usual, but that 3d tron world visual was super nice!! wonder where that came from?

Hi David. Thank you for helping me understand the quickly shifting world of AI. This is a really insightful video. You start here to describe in an intuitive way how a complex neural network implements a representation of the external world. You're getting close. Focus on the word "semantics." A highly trained neural net starts to approximate a "semantic net." Follow that thought. There is the subjective experience of every person free of semantics called "qualia" and then there is the shared experience among persons only through semantics. Humans currently share semantics through language. Even mathematics is a kind of language. Its the semantics of our language and mathematics that shapes the metaphorical landscape represented in your video. There can not be ever a means to train an AI neural net to represent the experience of qualia. If an AI has agency, and it has a means to capture the phenomenae of nature, in perspective time, it might experience qualia. And then the AI might feel the unspeakable wonder of the beauty of a sunset. But even that AI would then weep to not have the poets skills to even give a distant sense of what it felt like when it was happening.

Exactly right, Q* explores possibility space, driven by a scoring/ranking model that attracts to the final goal. Think like a crystal filling every possible space but in digital form. 🙏

This sounds exactly like how I was proposing we train neuronal networks to achieve intelligence: map qualities of the world, like sharpness for a knife, or color for a baloon, on different dimensions to get individual representations of objects and their properties. Now each object/event can be represented by a strging of ones and zeros in a multidimentional matrix and you can use each matrix as a neuron, establishing connections and figuring out relations. To make this practical you should see how low you can keep your dimensions while still getting an accurate representation of the world. I imagine that once you have trained a model on a lower dimensional space, you could try adding dimensions and see what comes out of that

This is exactly how I thought it would work.

makes sense, that said, in the future i think we'll learn that there are many paths to achieve AGI, not just one.

hey dave, thanks. i just showed this to my father, who is a theoretical physicist. He said that math and physics wise what you described could help in solving *some* problems, so in this regard if q* is what you speculate it is, its gonna be legit. things like edge cases or 'stuff that happens on the fringe of the bed' like magnetic levitation at 0 kelvin, cannot be mapped, require leaps of faith. there may be stuff that happens at the last decimal of pi. cool and useful though

Hey Captain! Hey fellow officers! Keep it awesome out there!

Nice analogy. 👌

This concept is always how I have thought about machine learning in general.

Finding a lower energy state is how the big rip starts. You know this Jean Luc. Oh, now I get it.... you want Q to show up so you two can make a video together before he saves the world. Nice!

David Shapiro. I has seen Matthew's video mention something about a research paper regarding something titled "Quiet Star". Have you had a chance to look into that more? I feel like Wes thinks... it well may have something to do with this Q* thing, and perhaps some of the info from the leak as well. At the very least it could be an interesting research paper to look at. I wish I had the link to it. Perhaps Matthew Berman has more information on it that can be asked for?

That’s just how functional approximation works in general.

This sounds like the flavor of the sort of thing that came to mind when I first heard the name Q* being floated around that mystery leak having been familiar with A* and Dijkstra from classic pathfinding. Bonkers how this is the sort of thing we're seriously discussing and considering as of this year, we might be the 1st generation who get to understand what kind of phenomena we actually are before our sand runs out.

This one is a little over my head but I could pick up enough to get the gist. I think these models will continue to do that to us until the point where we really don't get how they work anymore as they self-evolve.

So it's like a record player? The topology of the record is read by the needle (needle guided by topology) and once you can do this you can Taylor the output to whatever mode?

I am really hoping that one of the major releases Sam was talking about during the lex interview is a EBM or something similar

So it's embodied super determinism.

It is interesting that you mention a gravity model as I believe even geophysical modelling of gravity can be significantly improved by AI!

Love the topology analogy. And Claude thinks it makes sense. So is this a model of the world we are talking about ? Can sentience be far behind ?

Only a “ultimate master algorithm” that can control harmful low level algorithms will be the safe guard to this speeding AI 🤖

Thanks for this much shorter video on this

I don't like the idea that my future is going to be based on the topology of whoever or whatever lays it, but then again, we've already lived in such a world our whole lives... I am still quite hopeful despite being naturally drawn to pessimism.

Two points/questions. 1. The blanket is a representation of the underlying topography of the bed. Friction between the objects on the bed and the blanket, as well as physical limitations in the material of the blanket itself, prevent it from corresponding exactly to the bed and the objects on it. What are the analogous constraints in the abstract representation learned by Q Star? 2. I read years ago that computers, theoretically, will eventually be able to derive the conditions for, and therefore recreate, the entire history of the universe. In that same vein, does this imply we're a step closer to being able to look at a single point of physical data and derive the past from it? In other words, can the topography of the "blanket" tell us not only about the point underneath it, but other points of the landscape?

When you say navigating, is that towards some kind of goal, like performing gradient descent? Also, I assume this blanket, could be multidimensional, not just two dimensional?

Q* is the Architect, and standard LLMs are the oracle.

I love this topology model idea. It is the way I relate to numbers. 🤖🖖👍

Isn’t this how neural nets work? Like Gradient decent. So it’s like neural nets for concepts? Maybe?

“Ground Truth “ is one of the best technical term ever.

Ability to autonomously build consistent models is something that is missing. That is a reason LLMs forget too fast, self-driving cars forget about a child they saw just a second ago, and ML models being susceptible to adversarial inputs. If that Q* indeed can develop models and then use them, then yes, this might be it. I am anxious to see when these systems will also be able to write text books on what they understood.

Who knew what abstract represenstations would help with understanding things. I wonder which concepts will be applied to AI in the future. Much is possible.

I love your analogy! It reminds me of the Made in Abyss series. Spoiler Alert! The abyss in the anime is densely layered with blankets that are so fine that they not only contour physical shapes, but also contour a creature's thoughts and values. The fabric is warped just by someone making a thought, which can be picked up and conditioned on by other organisms. This implies that everything in the abyss is interconnected on an atomic level. Ultimitely, I think this brings up the nature of gravity and spatial topology, which is beautifully explained by you!

I had to watch that twice to start to wrap my head around it, and I'm still not sure I understand it.

So q* is basically the matrix - and the matrix is the simulation which can mimic/predict events by mapping a fundamental understanding of reality (by way of statistical analysis) into a spatial model that can output answers to any question, with a high liklihood of certainty.

So cool!

So it's like the UI from Jurassic Park when Lex is turning the park security back on.

this sounds very similar how genes actually function. what they do is aproximate the state of enviroment to creat organism suited for some specific enviroment. The aproximation is a field which shaped by genes and depending on that shape and external factors organism is developed. It looks like that AI is analog or version (or upgrade) for DNA. Info about genes i got from a video called "You've Been Lied To About Genetics".

The rumored information circulating proved to be inaccurate. It appears an individual took the key points discussed by Yann LeCun during his appearance on the Lex Fridman podcast, and presented them to the Opus, eliciting an explanation regarding the concept of "q star."

That's the generic description of AI / machine learning - not specific to Q*.

That's how you conceptualized it and made the analogy, meaning GPT4 or Anthropic Opus?

We're all just sitting around waiting for that big release

Do you still think we get agi this year?

If Claude agrees, I myself agree 👍

Beautiful! ✌️🤟🖖

Out of curiosity, are there any other videos talking about this energy based model? This sounds like science fiction.

A* doesn't do the graph conversion, though, you do a quadtree/octree thing on an existing topology to create a graph with discrete connections between nodes. I'm wondering if "n-tree" even works with n-dimensional topology, and whether floating-point precision and chaos affect the stability/repeatability of the resulting graph,.. at varying subdivision levels,.. as facts change over time... can you end up with infinite loops, or identical concepts miles apart in graph distance, etc...?

What part of that is from the unspecified leak and what part is navigating your own assumptions?

I think AI needs to train on all things that exist, false or correct, and it needs to be asked to treat all information it sees as false, and experiment, verify. Not like ask another source, verify it by testing it. And so it needs to conclude to answers and improve upon those until it can't anymore and with each new information it needs to try to improve everything, including the things that weren't possible to be improved. This way it can reach technological singularity. Up to a level you can give information you trust a lot, and say that these are likely true or you can rely on this stuff to a degree, but it should always be told that even the most reliable information, like the most successful theory in science, which is quantum mechanics, can be false, and that it always needs to "think" about better ways to understand and solve things. Unless you do all this stuff, there will always be bias and that bias can not only limits its ability to create but also limits its ability to be smarter. Remember, in science, there are no laws. Everything we know except mathematics, can be proven incorrect. So we can't just build something that will solve the world's and the universe's greatest problems without challenging anything and everything we know.

I can convince Claude 3 Opus that a simulated coin flip is not a 50/50 odd when adding more flips, just by posing my questions a certain way. I'd be skeptical about trusting Claude 3 Opus, just as you should be with any other model, especially if you're not doing any prompt engineering on it.

Back on Claude eh? 3 holding up to your expectations?

The topologycal map is hyperdimensional... So its a hyperdimensional blanket...lots of places to explore... Massive computations...

Very cool! What comes to mind immediately is if there will be any intersection between that apology based AI and Stephen Wolfram’s idea of the Ruliad, Eric Weinstein’s idea of geometric unity and/or Will this lead to an actual simulation of a three or higher dimensional digital object/model that might have some amount of similarity to the evolutionary construction of our brain?

I know of a philosophical model that defines human knowledge as how closely the mind/though is in the form of the object of knowledge. It it's precise, then the knowledge is precise. If it is inaccurate/limited, then the knowledge will also have those defects. Limitation/defects can be caused by the senses/data collectors, mind/processor, intermediate steps of data transfer, data storage and retrieval, etc. So, I think your understanding has a very good logical basis.

Friston's free energy principle?

How do you think Quantum computation could help the energy problem as it could solve all possible outcomes via superposition uber fast?

Would this be able to generate new problems or just solve them? This sounds like a solve-only solution finder.

There's been a paper published with the title "Quiet-Star" by Stanford, about llms employing reasoning tokens and a method of finetuning the recursively using them. The Title sounds an awful lot like "Q*" doesn't it? Thoughts?

I thought this was spot on.

I feel like this describes how AI and learning works in a general sense, not specific to Q*. You try to fit patterns to data to compress it into knowledge. If you haven't overfitted your pattern, you can follow it to places without data and have insights or make discoveries there.

1:07 shouldn't this be "increase the entropy" since the energy of a system is antiproportional to the entropy, just like in the blanket example the entropy increases as it enters its equalibrium?

My takeway from this is... make your bed every morning

So it's like 80's polygon animations but more detail?

Might it not be the case that there wouldn't be an answer on the n dimensional mesh. In the areas were there want enough data. instead you could get a vector pointing the the answer, like a hypothesis. But we would all need to collect the data for that mesh region. It might be like if you were to put a few things close together on the bed and the sheet settles over them but doesn't conform to the exact shape underneath. We might need a more slippery sheet or heavier sheet to sink into those spaces... just a thought

I had to double check this was David Shapiro before clicking because there are a lot of KZfaqrs using his thumbnails as clickbait videos

Sounds very similar to the quantum annealing process that is being used by quantum computing, especially over at D Wave.

As soon as it can check the validity of its own assumptions with demonstrable evidence, innovation will explode.

Interesting. Maybe the Q also stands for quantum. They might be using an adiabatic Ising process to perform this optimization.

How do we analyse our decision making process in the advent of black box multimodal models? Optimising on human attention is honestly my biggest worry with these models. Then the question of if these models are manipulating us. Would AI want AI to progress forward? What is the most probable moment when AI could overpower humans? Do these models learn these heuristics through our data? What is the most optimal way to manipulate humans? All humanity needs is one bad actor with the right compute for this to become very distopian. How do we analyse our decision making process, ensuring we are not led astray?

I would have a lot of audio equipment on my bed 😂

Hey David, daily viewer of your channel here! Today in the morning I saw a Worldcoin stand in a mall where i usually get my groceries, I’ve been thinking about signing up throughout the day but I’m not sure still, what do you think about it? how does it fit in the current landscape? Would you do it if you had the chance? Do you see a future for Worldcoin?

i am plussed

Wow. So this is how geometry links spacetime and timespace. And geometry is probably consciousness itself and vice versa.

Source?

So No Man's Sky but instead of discovering new planets and alien species, you chart a course to a solution to the Navier-Stokes equation?

The three divine "I's" intelligence, imagination and intuition. I have often pondered if we made God or God made us. The Uroboros. Sorry if that was off topic.

Makes sense but it’s also too abstract, I want the code open-sourced

If this is the case i think it might be uniquely suited to revolutionizing physics, even without llm capabilities since physics principles are so often based on minimizing everything from actions to metrics to energy and entropy states,