u/long_void

This looks good! Keep it up!

Maybe, in another lifetime...

I think you solved Flappy Bird!

(p.s. looking forward for the dragons!)

I haven't followed AI research for a while, so I am a bit unfamiliar with the terminology. So, excuse me if I don't get it right:

From what I understand, you're building a multi-theory database for AI applications. I like that you're working with memory first approach, because data is more important than algorithms when making long run strategic decisions. Also, using Kalman filter in a database is interesting. Besides use in e.g. rockets, Kalman filter is also used in historic climate data. Is this working on high dimensional vectors, e.g. semantic vectors?

Machine learning is Seshatic biased, because it uses errors to learn. We can tell how a language is biased by how it relates to errors, how it credits knowledge (causality vs abstraction) and whether it's temporal or spatial, or whether unknowns are integrated or meta-level with respect to the language. I read about the use of Knowledge, Memory, Wisdom, Intelligence at the storage level.

Logic is usually Platonic biased, which is the approach I take to do fundamental research. However, in Logic, you often rewrite the foundation when you discover weaknesses in its design. It's kind of like a house of card that falls apart and you rebuild it, over and over. The goal is to get it just right, but the applications are often limited because the knowledge you generate over time is abstract. It's kind of like a trace left over after doing all the revisions. In fundamental research this is OK, but it we need other language tools in general.

Human brains seems to use something like Joker Calculus (https://crates.io/crates/joker_calculus) to organize information, which allows it to understand e.g. Seshatic Knowledge, Platonic Wisdom etc. Perspective and layer are the basic operations. Maybe if you extend Knowledge, Memory, Wisdom, Intelligence to language biases in Joker Calculus, you can do something on storage level that is closer to how human brains work. However, this requires adding external primitives to Joker Calculus. At the moment, it only has Seshatism and Platonism. Seshatism and Platonism serve as reflective language biases.

I believe the key is solving AI memory and make it verifiable. If we also can make such memory function more similar to human brains, then we can replicate the nuance of understanding and integrate knowledge bases with human tacit knowledge.

Anyway, I wonder what you think about improving the accuracy of nuances, or Sense in general. There might not be just one solution here. I also think that one could add meta-knowledge as data layer, even if some database design doesn't support Sense out of the box.

Thank you! I put together a lots of ideas in that blog post I've been thinking about recently. I plan to expand on those ideas in various directions later.

It's going great! I had no idea how deep this rabbit hole was going to be when I first started. All I wanted to do in the beginning, was to know why normal paths didn't work well with dependent types. The reason I was so obsessed with normal paths, was because it was very useful to prove things when designing algorithms.

Unfortunately, normal paths are closely related to arbitrary sub-typing, which is undecidable, which means that we can only build somewhat limited tools. However, Poi showed that adding normal paths can be useful in automated theorem proving. Poi works well for a particular application of path semantics, but it has edge cases that makes its current architecture limiting.

The post you referred to, was in the middle of figuring out the HOOO EP axiom. These axioms were needed to complete the meta-theory due to some operators that are tautological congruent (I don't want to go into this issue here, because that's a whole lecture). That work was completed, but I also discovered that the HOOO EP axioms were more natural than Provability Logic, which in turn casts new light on Gödel's work on incompleteness theorem. Uh oh.

Next, I figured out that Intuitionistic Propositional Logic (IPL), which is the basis for Simply Typed Lambda Calculus (arguably one of the most important languages in whole of computer science), becomes an Existential Logic (EL, which has excluded middle for negated propositions) under HOOO EP. Uh oh again.

Also, a philosopher discovered that these operators I was trying to figure out, appears in Hegel's philosophy. Hegel is a 18th-19th century philosopher who was part of a Post-Kantian tradition that became mostly discarded in the 20th century, except at Catholic universities because they used it in theology, but has regained popularity due to recent breakthroughs in modern mathematics. This link to theology was also very curious, that, by kind of emerging different paths of research, resulted in discovery of what we call "language biases" in path semantics, that has gotten a more and more greater role.

Finally, I figured out that path semantics is really a kind of theoretical perspective of how people use symbols, which falls under semiotics. Semiotics has been criticized for not having a central formal theory, but there are various sub-fields that have or might have soon (there is so much in flux it's impossible to follow all of it) and path semantics makes up now one of the more stable sub-fields, since the basic theory is now more or less complete, with some more work needed for polishing.

However, overall, we still have no idea what path semantics really means. It's like, you build an intuition over time, thinking about stuff from a path semantical perspective, but it is kind of like an alien perspective, not a human perspective. I started noticing a few years ago that I can take that perspective, but also I got my own perspectives as a person that are separated from how I think from a path semantical perspective. So, that's when I started thinking, this should really be a field on its own, because it's just different, similar to how e.g. logic is a field with an intuition you build up over time. I just think of it as just another field, along category theory, linguistics, logic, philosophy etc.

Explaining path semantics is kind of like explaining logic. You can use 0s and 1s as a basic example in logic. You can use normal paths as a basic example in path semantics. However, when you move on from the basic examples, it just get more and more complex until you end up studying philosophy and history of ideas to learn about all the people who ended up in this rabbit hole before you did.

I've been working on Hooo on/off for 3 years now. I'm doing research on something called "Path Semantics", which is hard because it's not just one theory, but multiple theories that can be combined in various ways. Over time, it became clear that I needed a new feature, which I call "Theorem Grading", in order to handle the demanding use cases. While Hooo is very primitive in a lot of areas compared to other theory prover assistants, it has just the features I need now to continue my research. I'm happy with the results so far.

That's not fair. A LOT in the Rust gamedev ecosystem didn't exist 7 years ago. Not at the level of quality it is today.

The most important metric for professional gamedevs is not game engine adaption, but how much it costs them in the long run and how much profit you can make from the resulting products.

Hype in game engine design must be convertible into actual profit, to make success from that point of view. ECS, while it sounds good in game developer conferences, is not something that's visible from a user perspective. So, I don't see how to do conversion from hype to profit easily.

I believe the Fyrox developers made the right choice: Just ignore the hype. The bottom line and time spent with your family and friends is more important anyway.

I think Fyrox has a better foundation for the long run. Using tested and proven architecture. However, the future will show.

Best way to live!

I've been waiting for the stable release of Fyrox with excitement.

I'm using Piston/Dyon daily for small projects, because I can just run a script from the command line > piston <my_script.dyon>. This takes very little space on my hard drive and runs instantly. My favorite thing about Rust is how easy it is to build tools that just work.

However, for advanced 3D games, I think it's best to use the Unity-like architecture, because it has been tested and proven in the industry. Fyrox is the game engine I believe is closest one to competing against Unity in this space. No need to reinvent the wheel. Now that Fyrox is stable, I can integrate it my other Rust projects. The MIT license is also great.

What I see in Fyrox is this:

1. A good programming language (Rust)
2. A safe bet on architecture for creating games
3. An open source license that makes easy to change/fix/improve tech to support a demanding game

Fyrox also leverages Piston's Image library and the Rapier physics game engine, which are the two libraries that are most likely to be the future industry standard in Rust gamedev. Different games will probably vary in architecture, but those two libraries will probably ship in most games. WGPU looks like it is going to be an industry standard in Rust gamedev, however, I believe OpenGL too will continue to be around for a long time. Shaders written in OpenGL will also work with WGPU. I believe Fyrox has made the right choice for v1.0 by using OpenGL as the default graphics API.

It is extremely difficult to compete in the market of game engines, but I believe Fyrox is one of two Rust game engines that can make it to the top. The other one I think is Bevy. Right now, Fyrox is kind of like the under-dog, but I believe this might change over time. No matter who wins, Piston's Image library is going to be there. From the very start, the Piston project aimed to making it possible for Rust developers to work on independent libraries and to that goal, I think we've succeed.

There is nothing to do but saddle up my Piston horse, gallop away with Dyon into the Fyrox sunset!

Yeehaw!

Congratulations on v1.0!

It is possible that nature seems to be intelligent by design, despite that the underlying phenomena is random.

For example, if there is a maze with observers who make 100% random decisions of where to walk, then if you double the amount of observers in some location per unit of time, most observers will find themselves making seemingly intelligent decisions in their past, that brought them to where they are using the shortest path.

There is no logical contradiction here, just a matter of perspective and conditions under which physical laws operate.

I disagree with the position that nothing beyond the material exists implies that there is nothing deeper to explore.

The way people use symbols, e.g. in mathematics or religion, is not actually only built on only reality, but often a symbolic "fill in" that increases the practical utility and is aesthetically pleasing.

As a result, there are parts of mathematics that seem much more mysterious than others, e.g. Avatar Extensions: https://advancedresearch.github.io/avatar-extensions/summary.html

I wrote about the evidence we have from Paul's epistles here: https://github.com/advancedresearch/the_century_of_satire/blob/main/pauls-epistles.md

(this is based on an earlier thread: https://www.reddit.com/r/AcademicBiblical/comments/mna9ea/an_update_on_dating_pauls_letters_without_acts/)

The Mythicist position is not unreasonable, if you look at the evidence about Paul's epistles in isolation from Tacitus and Josephus.

However, considering that Jesus Christ is very influenced by Simon Magus in the 2nd century, which was not seen as crucified or a rebel leader against the Roman empire, I think it is consistent, when both Tacitus and Josephus seem to imply a rebel, to treat Jesus Christ as being based on some Jew that was called Messiah and was crucified.

There might be some themes from the Ephesian tale that were used in the original gospel of Mark, but I believe it is unlikely that the author would make up this crucifixion based on the Ephesian tale compared to getting inspired by it by parallels: There is a crucifixion in both stories, and there might or might not be, something about a drug. The latter is hard to tell, as Jesus Christ was used as a savior figure for Jewish schools of medicine in the 2nd century and they might use drugs in their stories. Or not.

Anyway, I think it's a good idea to separate the literary Jesus (Christ) from the historical Jesus (the rebel). This happens a lot of times in history, when people write stories based on some person that lived, but they might even put the literary character in the wrong century. E.g. Santa Claus vs Nicholas of Myra. In addition to this, keep in mind that Early Christians argue what's the "best version" (gospel means "good story") across multiple genres of literature, some who were not meant to be taken seriously. Ancient religious literature spans multiple genres and interpreting them as one serious genre is a categorical error.

Thank you!

Can we get somebody to reproduce the findings of the tingling sensation of the burning purple?

I liked these argument. Anyway, there is enough internet drama. Maybe Neal can cool down a little?

I agree. Paul might be a renaming of Simon Magus after the Bar Kokhba war in the 2nd century by Simonians that extended the original gospel of Mark to include John the Baptist. The original Mark might have been Roman satire where Jesus resurrects “back in time”, which we call the “Ouroborus hypothesis” in biblical scholarship.

If you enjoy studying 2nd Early Christianity, then you might find this project interesting:

https://github.com/advancedresearch/the_century_of_satire

Reconstructing 2nd century cultural literature context of Roman satire in Early Christian texts