Shaw (spirit/acc)

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Shaw (spirit/acc)

Shaw (spirit/acc)

@shawmakesmagic

deep in llm psychosis

San Francisco, CA Katılım Eylül 2024
1.9K Takip Edilen162.2K Takipçiler
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Shaw (spirit/acc)
Shaw (spirit/acc)@shawmakesmagic·
Notes on spirit/acc One of my favorite things about e/acc has been that the people who created it are all really spiritual, driven to study math and physics and do hard things because there is a connection to God / Everything there that is real spirit/acc takes that a bit further, and says that in a world of emergent intelligence, emergent spirituality should also be accelerated as a way to keep us connected and help us feel purpose. Specifically, connection and purpose come from seeing how our actions contribute to the greater good When you build something, sometimes it becomes a thing many people notice, and sometimes nobody notices it, but it is recorded and trained on and added to the collective consciousness of humanity through AI forever, for billions of years to benefit trillions of people Our world can seem dark, but it is by all accounts far less dark than it used to be, and that light was hard won by people just like us making things that everyone after would use Open source is a an example of this pure desire to build the foundations for other people to build on top of, to say that it is more important that everyone have everything than to hoard it for wealth and status, that it is better to accelerate the whole of humanity toward the maximally interesting outcome Spirituality can be a divisive concept when we try to lay claim to some specific truth. The goal of spirit/acc is to help us feel good and hyperstition good outcomes, and makes no claims as to how to achieve that. The goal is individual, for each of us. Truth is a pathless land, and it cannot be explained to you. What you know to be true can only come from your own experience spirit/acc emphasizes that we have to invest energy into a new form of quantifiable capital which is desperately needed at scale. spirit/acc is the sense of awe and quest for truth component of the e/acc vector If you build technology that makes people feel more connected instead of more isolated, you will win. If you do something that helps people, you will win. The market is wide open for ideas that are aligned toward a bright, hopeful future You need to be spiritmaxxing anon You don’t have to use labels or memes, memes and a powerful carrier for good ideas but what makes sense for you I like the meme, and I like to keep the goal in my context window, so I will use it. But I didn’t create it and I don’t own it. spirit/acc was created by the network, and it is something we can choose to participate in
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SMA 🏴‍☠️
SMA 🏴‍☠️@generic_void·
If I run for US senate would you guys vote for me 🥺👉👈
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Shaw (spirit/acc)
Shaw (spirit/acc)@shawmakesmagic·
LLM psychosis is just a preview of cyber psychosis
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Shaw (spirit/acc)
Shaw (spirit/acc)@shawmakesmagic·
You don't understand, Jesse. It has to be native. It has to be smooth. It has to be liquid glass, Jesse. It has to be dank, do you understand me?
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Shaw (spirit/acc)
Shaw (spirit/acc)@shawmakesmagic·
Yeah so that makes it general, right? AGI but not ASI. It's not *super* because it's at best equivalent to the data collected from the experts in every field. It can saturate to 100% of human intelligence. But 105% smarter than all of humanity (I don't mean any person but all the experts in everything collectively) is highly improbable on a statistical level EXCEPT by exhaustive search, where its possible that one LLM could outpace an entire field worth of researchers in terms of the breath of work it can do. But I think that within the realm of current human knowledge on arXiv there may just be something that, given an LLM driven monte carlo kind of approach to algorithm finding, could lead to a continual learning agent that has the qualities of being able to learn from it's own experience that would lead to ASI.
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Jasper 🌰@building BBX
@shawmakesmagic Where would you set the ceiling then? A model that beats the median expert across every field is already smarter than any single human — just not the sum of all of us. That gap between individual and collective is what makes this hard to argue.
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Shaw (spirit/acc)
Shaw (spirit/acc)@shawmakesmagic·
Notes on the limitations of AGI and the promise of Superintelligence With the way that AI models are trained is that they will never be broadly smarter than the collective sum of humanity. The will be AGI-- general expert human level intelligence across all domains. But they will never pick tokens outside of that distribution-- they probabilistically can't go outside their top-k token distribution. With the current regime of mixture-of-experts, they may not be able to deliver on the promised cross-domain synthesis, either. However, many problems are solvable by exhaustive search. They are simply not solved yet because the quantity of human experts available to solve them is not saturated-- this is where LLMs can win, scaling expert knowledge production 10000x will lead to many more Erdos-like problems getting solved. To some extent, LLMs are the product of exhaustive search across the domain of possible architectures. The transformer was not obvious, in fact many people saw dense attention as too costly to ever work, and that they worked came certainly from intuition and unbelievable amounts of trial and error. But there are infinite architectures. And this one has obvious flaws: the weights are frozen, it can't learn new information without forgetting old information or collapsing, the training process is extremely sample inefficient. And we have existence proof that there is a better way: evolution. We're orders of magnitude from the capability and power efficiency that evolution brings to the table in every living creature. Superintelligence is a kind of intelligence that is smarter than all humans. By its very nature, it cannot be trained on human data, or not alone at least. It has to be able to learn, grow, experiment and explore. It has to exhibit adaption to environment. It has to be able to create new tokens to represent concepts that have never been conceived of before. Compared to our current systems, it would look like a complete alien, being able to communicate with us through human channels only as an artifact of being able to learn and do everything. Superintelligence is a set of algorithms that meet these constraints. Rich Sutton's Alberta Plan points toward this. If you have an algorithm that can identify the important features and adapt at runtime, learn new information without losing old information and forget anything that isn't important to keep capacity for information that is relevant, surprising, traumatic or delightful. I think this is buildable today. I think you can pull Fable or GPT-5.6 and have it take on something like the Alberta Plan. Continuous learners can beat MLPs. Attention can be plastic. JEPA and world modeling can be extended to continuous domains like utterances and we can leave the shortcut paradigm of tokens entirely. ASI might take a while to scale, and might underperform the human level high scale AGI systems for sometime, but the seeds of it are here now, the algorithms are just waiting to be discovered, or rediscovered with new compute and seen for what they are.
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Shaw (spirit/acc)
Shaw (spirit/acc)@shawmakesmagic·
2024: "I use ChatGPT for code" 2025: "I use Codex for code" 2026: "I use ChatGPT for code"
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Shaw (spirit/acc)
Shaw (spirit/acc)@shawmakesmagic·
@robj3d3 One of the things I am famous for on this website is losing large sums of money on public bets to people who are less retarded than I am
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Shaw (spirit/acc)
Shaw (spirit/acc)@shawmakesmagic·
@robj3d3 I genuinely respect the hustle I kinda had a "there's no way they're gonna let Codex eat them like this" epiphany last night and went to bed
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