Could a network be trained to transform physics state directly into the latent state and back?
Having a direct transformation would enable some interesting experiments.
How is the latent state different when everything else stays the same, but you change one physics value, like player one velocity? Is there a cyclical pattern of activation that correlates strongly with the seconds digit of the clock? Can you decode the latent state, give players full boost, and then re-encode it for infinite boost, without losing continuity?
Edit: There sure are a lot of papers on interpretability.
I really think that a genAI picture book is like a microwave dinner. You can try to pick out a good one, but a corporation has done most of the deciding for you. Ultimately, it will not be as wholesome as something homemade, or as good as something made by an expert, and it will always taste like plastic.
AlphaGo, through self-play, found new strategies to beat the best human players. But now that anyone can play against AlphaGo, humans are learning these strategies.
Deepmind is saying people are learning from the algorithms AlphaEvolve is generating. They say the programs tend to be short.
You don't need to check the proof. A regular proof is written to convince other mathematicians. A regular proof can skip details and contain mistakes. A formal proof cannot skip details or contain mistakes.
A lean proof is a sequence of instructions that starts with a list of facts, and combines them into new facts until a target fact is produced. Each instruction in the sequence is one of a few allowed tactics provided by lean that always produce correct facts from correct facts.
IF (1) you agree with the starting facts, (2) you are sure the target fact is what you're actually trying to prove and (3) the lean compiler says "yep, this is a valid sequence of instructions" THEN you can be sure the target fact is true.
You can be sure the final fact is true, even if you don't understand all the steps, because it's written in lean, and lean only allows steps that are free from omissions or errors
When I write like I talk, I use a lot of commas. Replacing some of my commas with em dashies, so long as it was done judiciously, would probably make things easier to chunk.
I really look forward to the day AI-driven algorithm design + formal verification becomes the norm for performance critical computing.
A programmer translates a natural-language spec into a machine-readable spec, feeds it to an AI-assisted compiler, and out pops an implementation that's more optimized than any human could ever hope to write, along with a lean proof of its correctness.
Most textbooks sold are bought by students because they were required for a course. Students are not choosing a textbook by cover because they're not choosing a textbook at all. Professors choosing which textbook to assign are doing so based on the content, because that's what they'll be teaching. Professors also get a lot of free sample copies, and are probably choosing between those instead of purchasing their own set of candidates based on the cover.
In one of the essays posted here, which was, ironically, about AI in education, a sentence, that an AI could not possibly write, that I could possibly write, because of its length and unusual structure, before finally reaching the verb, went on for 25 words.
I don't know if it was written that way to show trust in the reader's intelligence, show disregard for reaching a wide audience, show a demonstration of skill, or was artifact of someone just thinking at that level.
A sudden switch to depreciation makes housing more expensive, even though prices are going down.
Say you buy a house with a loan, and sell it after x years. The total cost of ownership is interest paid to the bank + buy price - sell price. If you bought a house at $600k expecting to sell it in a few years at $700k, but it'll actually sell for $500k, your TCO went up by $200k. The sudden switch to depreciation made the same house much more expensive to own. Prices have to slowly go from rising to steady and then to falling, otherwisw everyone is suddenly living way beyond their means.
A cleaning station is a location where aquatic wildlife congregate to be cleaned by smaller organisms. Such stations exist in both freshwater and marine environments, and are used by animals including fish, sea turtles and hippopotamuses.
Nobody cares that a browser's navigation buttons, address bar, tabs, or window controls
don't match the current website. Probably because these things are obviously outside the extents of the web page.
However, scrollbars, context menus, modal windows, and date pickers are rendered within the extents of the web page, and get replaced all the time.
It is my opinion that these controls don't need to be styled to match the website, because they're not part of the website. They're part of the browser. Non-diegetic. Outside the fourth wall.
I found joy making sdf2stl.saej.in. It's similar to a bunch of things that already exist, but I was able to make a set of requirements that made mine technically unique.
It was too complex for me to create when I started, so I learned as I went.
In personal projects, I only use LLMs for when I don't care and I don't want to learn. For example, all the WebGL APIs. I am perfectly fine not knowing how to allocate, initialize, and bind a shaderbufferindexobjectstoragehandlepointerarray. But I'll do the fun parts, the interface design and algorithms, by myself.
I'm a big fan of the fact that the following quoted sentence has 25 words before the verb. An LLM would never. I probably wouldn't.
> Whatever your conception of the modern university, whether grand or grim, understanding the current landscape of campus-wide AI use, much less its intensification, should destroy it.
I once wrote about inherent, irreducible complexity and how we try to deal with it. The draft has sections on how complexity can be hidden, spread out, localized, passed off, or recreated from scratch. Unfortunately, people are now using LLMs to pile complexity on the simplest of tasks, and my essay isn't really worth finishing.