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Differentiable Logic Cellular Automata

google-research.github.io

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Re: Differentiable Logic Cellular Automata

#51

Post by [deleted] »

thatguysaguy wrote: post #6
owenpalmer wrote: post #5

Earlier quoted context omitted.

Which portion of the text gave you that impression?

> To answer this, we'll start by attacking Conway's Game of Life - perhaps the most iconic cellular automata, having captivated researchers for decades > At the heart of this project lies... > his powerful paradigm, pioneered by Mordvintsev et al., represents a fundamental shift in... (Not only is this clearly LLM-style, I doubt someone working in a group w/ Mordvintsev would write this) > Traditional cellular automa…

[deleted]

Re: Differentiable Logic Cellular Automata

#53

Post by ysofunny »

achille wrote: post #34
ekez wrote: post #11

There’s something compelling about these, especially w.r.t. their ability to generalize. But what is the vision here? What might these be able to do in the future? Or even philosophically speaking, what do these teach us about the world? We know a 1D cellular automata is Turing equivalent, so, at least from one perspective, NCA/these aren’t terribly suprising.

these are going to be the dominant lifeforms on earth exceeding bacteria, plants and humans in terms of energy consumption cellular automata that interact with their environment, ones that interact with low level systems and high level institutions. to some approximation we, humans are just individual cells interacting in these networks. the future of intelligence aint llms, but systems of automata with metabolic asp…

because the goal of life is to maximize metabolic throughput?

or to minimze energetic waste?

Re: Differentiable Logic Cellular Automata

#54

Post by eyvindn »

emmelaich wrote: post #14

The result checkerboard pattern is the opposite (the NOT) of the target pattern. But this is not remarked upon. Is it too unimportant to mention or did I miss something?

thanks for catching this, the figure for the target was inverted when exporting for publication, corrected now.

Re: Differentiable Logic Cellular Automata

#58

Post by 0xfffafaCrash »

K0balt wrote: post #16
kelseyfrog wrote: post #8

Earlier quoted context omitted.

The reason LLMs write like that is, unsurprisingly, that some people write like that. In fact many of them do - it's not uncommon. If you have proof like the logits are statistically significant for LLM output, that would be appreciated - otherwise it's just arguing over style.

Yeah, it’s disheartening that people often think my writing (most of it predates gpt3) is llm, and some of my favourite writers also fall under this wet blanket. LLMs just copy the most common writing style, so now if you write in a common way you are “llm”.

I’ve also had my writing misidentified as being LLM-produced on multiple occasions in the last month. Personally, I don’t really care if some writing is generated by AI if the contents contain solid arguments and reasoning, but when you haven’t used generative AI in the production of something it’s a weird claim to respond to.

Before GPT3 existed, I often received positive feedback about my writing and now it’s quite the opposite.

I’m not sure whether these accusations of AI generation are from genuine belief (and overconfidence) or some bizarre ploy for standing/internet points. Usually these claims of detecting AI generation get bolstered by others who also claim to be more observant than the average person. You can know they’re wrong in cases where you wrote something yourself but it’s not really provable.

Re: Differentiable Logic Cellular Automata

#59

Post by BriggyDwiggs42 »

achille wrote: post #39
ryukoposting wrote: post #35

Earlier quoted context omitted.

I'll have what this guy is smoking. Those visualizations are pretty, though. I can imagine this being useful for implementing classifiers and little baby GenAI-adjacent tech on an extremely tiny scale, on the order of several hundred or several thousand transistors. Example: right now, a lot of the leading-edge biosensors have to pull data from their PPG/ECG/etc chips and run it through big fp32 matrices to get heart…

yes absolutely: current systems are wildly inefficient. the future is one of extreme energy efficiency. re smoking: sorry let me clarify my statement. these things will be the dominant life forms on earth in terms of metabolism, exceeding the energy consumption of biological systems, over 1k petawatt hours per year, dwarfing everything else the lines betwen us may blur metaphorically, we'll be connected to them how w…

Okay so another way to put it is that these are gonna be the software we run on lots of computers in the future. Why this particular model of intelligence and not some other one?

Re: Differentiable Logic Cellular Automata

#60

Post by BriggyDwiggs42 »

alex_abt wrote: post #44

> magine trying to reverse-engineer the complex, often unexpected patterns and behaviors that emerge from simple rules. This challenge has inspired researchers and enthusiasts that work with cellular automata for decades. Can someone shed some light on what makes this a problem worth investigating for decades, if at all?

https://writings.stephenwolfram.com/2024/08/whats-really-goi...

One example is that stephen wolfram argues, I think compellingly, that machine learning “hitches on to” chaotic systems defined by simple rules and rides them for a certain number of steps in order to produce complex behaviors. If this is true, easily going in the reverse direction could give us lots of insight into ML.

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