Maximum Effort

https://maximumeffort.substack.com/ “Some things that aren’t worth doing are worth overdoing.” I write about physics, language, and history, or whatever interests me at the moment, with an overarching theme of spending way too much effort analyzing useless topics. Here’s some of my favorites: https://maximumeffort.substack.com/p/the-tyranny-of-the-wagon-equation I derive an expression for number of donkeys needed to move an army a distance L, and discuss its relationship to the tyranny of the rocket equation. https://maximumeffort.substack.com/p/guinea-pigs-are-fermions-part-1 I postulate that Guinea pigs are fermions, and simulate the quantum dynamics of multi-pig states. https://maximumeffort.substack.com/p/a-statistical-analysis-of-sniffin… I attempt to answer the timeless question of whether the characters in Wheel of Time sniff in disapproval more than average. https://maximumeffort.substack.com/p/i-taught-chatgpt-to-invent-a-lang… ChatGPT and I invent a slime language. https://maximumeffort.substack.com/p/an-offering-for-the-dead I teach you just enough Middle Egyptian to read some of the hieroglyphs on most museum artifacts. https://maximumeffort.substack.com/p/the-great-kings-of-assyria-reply I share my technique for annoying text spammers by pretending to be Assyrian Royalty. Mostly up to date index of posts: https://maximumeffort.substack.com/p/coming-soon Hope you enjoy!

I would love for an RSS reader/HN/Reddit thing to exist. You could get you personal news on one side, and subs/communities whith two columns, one for news from sources curated by the admins/mods of the sub, and other column for news, links and text posts submittes by the users. You could only join by invitation, so as to make F2F social networks in self-hosted instances, or in a Discord-esque "server". I think the value here would be in exchanging opinions, information and new interests with an expanded social network (you woukd probably like and find interesting your friends' friends). Although I admit this model would be a closed community, if it's only one instance then it's not a problem because there are not a lot of people, and if it proves to be successful, it could span a renaissance of blogs or independent content-generation, i.e. these communities would be closed but reinforcing an open Web, instead of mega-silos with captive audience. I think that a limit in size for each community would be essential, the first member/admin can invite, let's say, 80, people, each of those can invite 40 people, and the third "generation" just another 20 people. This way you get at most 64k people to interact with. There was a post here on HN a couple months [0] ago with a back of the envelope calulation of subreddits being hostile when reaching a 300k userbase. [0] https://maximumeffort.substack.com/p/scaling-problems-in-social-contro…

Article is a little light on details with regards to why the author believes this effect exists. I have to imagine that their thinking is that application of force is limited to the distance you can travel one month instead of anything that would relate to the application of soft power (e.g. communication). Supplying a ground based force follows more of a square-cube law. You need to feed your horses to transport your food to feed your soldiers. Going further means more food for the horses to carry the food for the horses to carry the food for the soldiers. There is an excellent post here that explains this far better than I ever could: https://maximumeffort.substack.com/p/the-tyranny-of-the-wagon-equation Any limitations on space based empires, while similar, are going to follow somewhat different rules depending on the tech involved. Unlike horses, once you launch you don't really have an opportunity to resupply a space based force going a long distance without inordinate energy expenditure. I'm not convinced force projection over a galaxy would be a problem for a civilization capable of travel at a significant fraction of the speed of light. Solving one problem (travel) necessarily solves the other (distribution of force). I think the bigger question is more, why bother? What possible reason could a civilization have to go to war at that scale? Human civilization would need to change so much to get to that point that I'm not certain these are questions are explorable…

Here's one: https://szopa.medium.com/teaching-chatgpt-to-speak-my-sons-invented-la… Here's another https://maximumeffort.substack.com/p/i-taught-chatgpt-to-invent-a-lang… both found via google: https://www.google.com/search?q=using+chatgpt+to+invent+a+language&…

Long before there was the tyranny of the rocket equation, there was also the tyranny of the wagon equation [1] that limited how far per-industrialized armies could move with wagons and animals (though the equation wasn't formalized). [1] https://maximumeffort.substack.com/p/the-tyranny-of-the-wagon-equation

You can make it invent a new language: https://maximumeffort.substack.com/p/i-taught-chatgpt-to-invent-a-lang… I am sure you will continue to argue that this is still in line with everything-thats-ever-written prediction but my opinion is that at that point, it's a meaningless distinction. The human brain is also just a machine.

You are conflating the counting problem with an inability to do anything with data it doesn't have. For its ability to invent new languages and translate to and from them, see https://maximumeffort.substack.com/p/i-taught-chatgpt-to-invent-a-lang… For the reason why LLMs can do this and why they don't necessarily need to have seen the words they read or use, you can look up "BPE tokenization" Could you give me an example that isn't counting-related?

https://maximumeffort.substack.com/p/i-taught-chatgpt-to-invent-a-lang… My bet would be that in ten years GPT would get pretty good at it, but eh, I dunno.

There was an article featured the other day about how some communities on some subreddits become hostile when the community size gets too large [0] [1]. The article estimated that the critical size was Dunbar's number (150) raised to 2.5, which gives about 300k. Mastodon.lol looks to have been around 67k up until recently [2] (which gives an exponent of about 2.2). [0] https://news.ycombinator.com/item?id=34713553 [1] https://maximumeffort.substack.com/p/scaling-problems-in-social-contro… [2] https://web.archive.org/web/20221122205835/https://mastodon.lol/explor…

Adjunct: the tyranny of the wagon equation [1]. [1] https://maximumeffort.substack.com/p/the-tyranny-of-the-wagon-equation

I actually wrote an article about this a couple weeks ago. https://maximumeffort.substack.com/p/is-a-hot-dog-a-sandwich-defining?… My contention is that the definition-first approach to defining sandwich is wrong, and that we should use PCA/unsupervised learning first to cluster sandwich-like objects into distinctive groups, which we can then name.

> Anything that isn't in the training data set will not be produced as an output. Thinking back to some of the examples I have seen, it feels as though this is not so. In particular, I'm thinking of a series where ChatGPT was prompted to invent a toy language with a simple grammar and then translate sentences between that language and English [1]. It seems implausible that the outputs produced here were in the training data set. Furthermore, given that LLMs are probabilistic models and produce their output stochastically, it does not seem surprising that they might produce output not in their training data. I agree that we do not have a good understanding of what reasoning, thought, or awareness is. One of the questions I have been pondering lately is whether, when a possible solution or answer to some question pops into my mind, it is the result of an unconscious LLM-like process, but that can't be all of it; for one thing, I - unlike LLMs - have a limited ability to assess my ideas for plausibility without being prompted to do so. [1] https://maximumeffort.substack.com/p/i-taught-chatgpt-to-invent-a-lang…

> You are conflating the counting problem with an inability to do anything with data it doesn't have. No, I'm answering your question, "Can you explain what you mean by "strictly a combination of its inputs"?" > For its ability to invent new languages and translate to and from them, see https://maximumeffort.substack.com/p/i-taught-chatgpt-to-inv... It's not "inventing" new languages, it's pattern matching from the massive section of its dataset taken from the synthetic languages community. As my other example shows, it can't handle simple languages like "English backwards." > For the reason why LLMs can do this and why they don't necessarily need to have seen the words they read or use, you can look up "BPE tokenization" Are you saying that if I look this up, I can understand how ChatGPT does this? I thought you were trying to argue that we can't understand how ChatGPT works? > Could you give me an example that isn't counting-related? See backwards answers example. And honestly, excluding counting-related answers is pretty arbitrary. It sounds like you've decided on your beliefs here, and are just rejecting answers that don't fit your beliefs.

> When implementing an algorithm as a computer program by means of some kind of formal language (including those based on recursive functional programming paradigms), we must introduce specific data and code structures, their properties and interactions, as well as the set of operations we are allowed to perform on them, in order to represent the objects and relations that are relevant for our computation. In other words, we must provide a precisely defined ontology on which the program can operate deductively, e. g., by drawing inferences or by ordering tasks for solving a given problem. In an algorithmic framework, novelty can only be represented combinatorially: it manifests as new combinations, mergers, and relations between objects in a (potentially vast, but predefined) space of possibilities. This means that an algorithm cannot discover or generate truly novel properties or relations that were not (at least implicitly) considered in its original ontology. Therefore, an algorithm operating in a deductive manner cannot jury-rig, since it cannot find new causal properties of an object that were not already inherent in its logical premises. This argument is not convincing to me. In fact, there seem to be real world counterexamples to their argument. If the AI agent is operating, on say, text, why is that space “potentially vast, but predefined”? A text stream of arbitrary length is arbitrarily vast. An AI agent could, conceivably, define new ontologies textually. As an…