You'll find these in reverse chronological order because I'm not insane
Sup Fam, it’s Dan (a lil slant rhyme for those of you keeping score). Whilst perusing mine blog, I couldn’t help but notice I have a bunch of hanging projects. It just so happens that most of them flopped, so I thought I’d take some time and take out the garbage, if you will. Do some bloggular pruning, if you won’t. And to that end, let me tell you why I no longer study hot bois.
First of all, by hot bois, I of course mean quarks and gluons (duh). This particular post probably should have been written several months ago because I stopped doing “research” at LBNL around April, and you’ll notice it’s currently… let me check… oh yes! November. Whatever, you don’t care, and neither do I.
What you do care about is why I say “no” to hot bois. The simple answer is that almost every single moment I spent “studying” quark gluon plasma felt like a raging waste of time. That’s your ol’ tl;dr in case you don’t want to read the next 37.3 pages I’m probably going to write.
Now, before I go on a religious rant about why my research experience was dumb and stupid, I should say a couple things. First of all, the Professor in charge of my old research group is simply fantastic. Her name is Barbara Jacak, and she’s simply one of the best faculty members with which I interacted at Berkeley. Barbara was incredibly kind, generous, and made every effort to help me find meaningful research. And it’s not like she wasn’t already incredibly busy. Last I checked, she was working two full-time positions. Not only was she a full-time professor, but she’s also the director of the Nuclear research department at lbnl. So yeah, she’s fantastic. Basically, if for some reason someone reads this who’s looking to study hot bois at Berkeley, try to be friends with Barbara, and while you’re at it, congratulate her on being a genius and incredibly kind. Actually maybe don’t. That’d make her uncomfortable.
I also liked most people in the research group. I didn’t really get to know anyone super well, but a couple of the grad students were really nice to me, and super helpful.
Unfortunately, the research kinda sucked. Let me tell you why.
My first “project” with the group was to try to learn how to use this particular software that reconstructed particle trajectories from collision data. To use more approachable language, I was using some nerd code to find where and when hot bois be. I’ll spare you the physics lesson on how the hot bois came to be in the first place, mostly because you don’t care and it’d be boring.
On paper, this is a fine project. Readers of the ol’ bloggerino know I’m a sucker for learning new software tools that do cool things. Unfortunately, there were a couple inherent issues. The first is that physicists write some of the most disgusting, unintelligible, bug ridden garbage on the face of the planet. And to make matters worse, everyone working on CERN typically insists on using the insidious language of C++.
As a brief side note, I should mention that C++ has absolutely changed the world. A huge portion of your digital life is probably powered by C++ code. It has a lot of great things going for it. It’s super-fast, it has classes, a great standard library, all that jazz. And, it’s not C, which means it’s a gift from the heavenly dieties. So why do I hate it? The stupid, stupid physicists who abuse C++ magic to write disgusting code that manages to still run pretty well.
Also, C++ isn’t memory safe, and I don’t think it’s strongly typed. Gross. Nothing worse in the world than a piece of code crashing because “Segmentation fault. Core dumped.” I’m filled with a deep rage even writing those words.
Anyway, the piece of software I was supposed to be learning was gross, and it wasn’t built to run on Windows. That’s an issue because my lil beasty of a computer happens to be an XPS 15, and you best believe I’m rocking Windows 10. I’ve toyed with fully switching to Linux, but I really just don’t want to. That’s all. You happy??
So anyway, at the end of the day, the software I was learning really just didn’t want to download on my computer. And that’s not fun.
But that’s not what was really painful. It’s not unusual for experimental software to require a 1-2 hour battle to properly download and run smoothly on a non-linux computer. (I’m fairly certain that last sentence was a grammatical catastrophe. Keep your eye out for those, cause I’m sure as frack not going to change them). However, blessed, blessed reader, this particular physics software took a bit longer to download than 1-2 hours. How long did it take, you ask? …well… THREE WEEKS. I SPENT THREE WEEKS DOWNLOADING A PIECE OF $&^#%*@ SOFTWARE.
Lads and lasses, I didn’t enjoy that. But you know what the worst part was? After those three weeks, after I finally got it to compile on my WSL, after I finally wrassled the CMAKE file to submission, after I re-configured ROOT (different physics software) for the fourth time, it crashed. You want to know what the error was? “SEGMENTATION FAULT, CORE DUMPED.”
If you’ve worked with C++ or C at all, you understand that in that moment, I was barely a man. My soul was so crushed and weak I barely had the will to live. And typically when you get a memory bug, you’ve written all the code and you at least know where to look. I hadn’t written a single line of the probably 10,000+ line codebase.
Anyway, suffice it to say that I waltzed on over to Barbara’s office not too long afterwards, and I got a new project.
While I was writing this, I realized I think I already told this story in my last post about this research. Eh, whatever.
Anyway, that all probably happened in February or March. I thought I was home free after I got my new project. I was not.
I’m not even going to attempt to describe what my next research project was supposed to be. Instead let me tell you the gist of why I quit.
First, I could never really tell what anyone was trying to accomplish. Sure Barbara had explained what the group’s short term goals were, but I’m talking big picture goals. Basically I kept on reading academia propaganda about how this research could help us understand more about the Big Bang, and the early universe. BUT HOW? HOW?? I’ve heard researchers talk amongst themselves about or write in papers this sort of sentence over and over again. You know, the sort of “My research is important because it helps us understand X topic better.”
Every time I see something like that, I want to scream, “HOW does it help us understand X better? And why the @#$% does that even matter at all??” (My irritating resolve against the use of expletives when blogging is really starting to bite me in the butt. You’re welcome, mom).
Anyway, I never really found answers to those two questions with regards to research about quark gluon plasmas. To get uber utilitarian with it, I guess you could say that researching these physical systems could potentially allow us to find new, efficient, and stable processes that could power new technological movements, but aside from that, it seems kinda pointless. If you wanted to get super trattagarian with it, you could say the knowledge is intrinsically valuable and beautiful and worth pursuing in and of itself, but I kinda hate that argument, and it seems incredibly emotionally driven and kinda dumb. Take that. I might write a post dissecting this sentiment a bit more because I think it’s actually super important.
To put it in the simplest terms possible, deep down, I don’t care about hot bois. I really don’t. And I don’t want to pour my time into something that seems kinda meaningless. I imagine you understand. Some of you more STEM-inclined readers might take issue with my saying studying hot bois is meaningless, and I don’t actually mean it, but I don’t want to take the time to clarify my position, so you can go shuck a duck.
However, not only did it seem like my research was kinda pointless, but I couldn’t figure out why anyone else was studying it either. People didn’t seem passionate about hot bois at all (except for Barbara and a couple grad students, bless their souls). After talking with the group members, it kinda seemed like they were doing it just because the Berkeley culture makes it seems like the thing to do. That statement is obviously a major oversimplification of the complexity that is someone else’s lifestyle and life choices, but that was my main impression.
Anyway, I’m out of that life now. Wow a lot has happened since then. Back in April, I wanted to start businesses and build apps. Man, stuff has changed.
To put a bit of a bow on this post, when I quit Barbara’s group back in April, I thought I was done with research. It seemed stupid and dumb. Ironic that’s basically what I’m doing now. Except no physics and no hot bois. I’m done with those. The end.
Sup people. Ex fizz, back at it again, trying to understand reality. So as I mentioned a couple posts ago, I’ve been working a bit more on Orchid, because I’m pretty sure it’s the only way. However, in bathing myself repeatedly in the hot, soupy stew that is fundamental mathematics, I’ve been forced to think a bit harder about certain things than I normally would. Like, for instance, “what is information?” Now all you information theory nerds can go wallop some cows for all I care, because typically discussions pertaining to information theory disintegrate into nonsense about entropy and other such jazz. And, allow me to be vulnerable for a sec, I don’t care enough about entropy to have studied it enough to know what the frack information theorists even care about. So maybe I’m just dealing with the same problems as them.
So let’s cast information theorists aside for a moment and return to first principles in these matters. Let me first ask a question: what is information? And now, let me answer it. As best as I can tell, information is a correspondence between the configurations of several (sometimes unrelated) stable systems. I realize that’s not super helpful, so let me give you an example from cave man days, because those are my favorite examples.
Let’s say we have two cave men, Dave and Thnead. Dave and Thnead enjoy being alive, and are therefore wary whenever they are approached by a saber-tooth tiger or an allosaurus. Both of those animals are big red flags to Dave and Thnead and typically spell out a gruesome bloody demise. Let’s say Dave and Thnead keep their best weapons at the back of their cave to protect them from the weather. Now then, Dave and Thnead take turns keeping watch during the night to minimize the chance of gruesome death by wandering saber-tooth tiger or allosaurus.
You know what, Dave and Thnead might as well be gay. How’s that for character building? That helps the analogy because now they have a good reason for wanting each other to stay alive.
This is an egregiously drawn out analogy, but let’s say Dave and Thnead come up with a system. If the boi that is keeping watch during the night sees a mean beasty, then that boi will throw small rocks (the type that float) at the back of the cave to wake the other boi up. Now then, everyone knows that rocks are better than sharp sticks for attacking saber-tooth tigers, and sharp sticks are better than rocks for attacking allosauruses. Because of that, our bois agree to throw one rock to the back of the cave if a long toothed tiger is spotted, and two rocks if a large reptilian fang-lord (allosaurus) is spotted, simply so that our bois are best equipped to fight whichever beasty they may encounter.
Dang that example was way shorter in my head. It’s literally equivalent to “one if by land, two if by sea” but we’ll ignore that for now.
Anyway the whole point of that written charade is to emphasize the correspondence between the number of rocks thrown and the type of beasty strolling by in the night. Even though there doesn’t seem to be any inherent tying the type of beasty to the number of rocks thrown, this system allows information to be passed between our lads.
So then, we get to the question that be-titles this post: what the flip-shack frack is a definition?? You may be wondering why this is important. Well, intellectually endowed reader, the notion of a “definition” is the only reason why the number of rocks thrown to the back of a cave has any correspondence to the nature of the animal that lurks in the darkness. Otherwise, those two systems have absolutely no meaningful connection.
The reason why I care about this is because I’m attempting to determine the extent to which information is fundamental to the universe, and the extent to which information is a human construct. It has become crystal clear to me that in any system within which there exists some notion of forward progressing time, the most fundamental entity is a stable system. The question, then, is whether information as we know it exists on a fundamental level or on the level which is only meaningful to the entities known as humans. And the answer to that question rests on the true nature of a definition.
While I’ve been writing this, I think I’ve stumbled upon something major. A definition is only meaningful if the source of the definition is itself well-defined and perceivable. Ah yes. That’s it. Well I just wrote three pages to answer my own question. I suppose before I wrap this up, I should explain my realization. Definitions are themselves merely characteristics of stable systems. Why does the character sequence “r-e-d” mean anything to you? Because you know that whenever I’m trying to describe an object that’s giving off electromagnetic radiation around 700nm in wavelength, then I will use the character sequence “r-e-d.” Thus even if you aren’t in the room, you now have a clear idea of the nature of the light coming off the object and entering my eyeballs.
So basically definitions and information are just “if, thens.” For example, in the case of our cave men, the following statement describes the stable behavior of one cave man “if [boi] sees allosarus, he will throw two rocks. If [boi] sees tiger, he will throw one rock.” Therefore the presence of a thrown rock immediately yields the other boi information on the nature of the beast outside the cave. Cool!
If you’re wondering why any of this is actually interesting, email me and I’ll do a better job of explaining it. Otherwise, bye bye now!
What is poppin, boys and girls?? It’s your boi, Daniel frikin P. finally back from the dead yet again to give you some sweet, sweet content. Well, I suppose that’s a bit of a lofty claim. If web app forging, or general software corralling falls into your category of sweet, sweet content, then, well…I’m your man.
Let me immediately address the beluga in the room (I feel that the particular topic at hand is more egregious than what is typically correlated with your standard “elephant in the room” cliché, so I have appropriately replaced elephant with a more egregious entity to find in your room, namely the beluga). I, Lord Ex Fizz, have not posted any content in what feels like a decade. I am not sorry, and I don’t repent. If at any point you were invested enough in my postings to care about when I put something new on the ol’ site-erino, then perhaps you feel as though some sort of fizzy apology is in order. I love you dearly, should you find yourself in this category, but frankly, my lack of posting is none of any of our concerns.
As you may have guessed, I haven’t been writing ex-fizzicle content simply because I have been coding. Somewhat non-stop. What have I been coding, you ask? Well that’s the point of this new project, so tighten your belts and shoelaces, and settle on in.
Let me weave you a tale. At the beginning of human existence, before any notion of a social contract, humans essentially existed in a state of anarchy. If I looked over and saw you holding a really cool looking rock, then by golly, I’d go over, smash you in the head with another worse rock, and take that beautiful orb you’re holding right out of your hands.
Smashing other humans in the head is all fine and good, but what happens when a bigger boi comes along and wants my rock? Well, friends, I’m finna get smashed, and that’s a fact, jack. Now, brethren and sisthren, ya boi ex fizz is not in the business of getting smashed, so what do I do to prevent that? Well, I form a social contract with the bois around me. I may not be able to steal whatever I want from weaker human, but there’s a much lower chance of me getting smooshed, and that’s just really fantastic.
If you extend this notion more, you end up with a government. Healthy governments are pretty fantastic because even though not everyone has a perfect moral system that would perpetuate a healthy society, the blessed government provides a series of incredibly potent incentives for acting as though you do. To put it in a less overtly verbose way, if I smash someone in the head, I’m probably going to jail for a long time, so basically, I’m not about to go out on the street and start smashing people.
Now let me weave you another tale about the human experience. Around the turn of the century, humanity was reborn, not of flesh, but of ones and zeros, binary. With the advent of social media, humanity was able to assume a new digital form of being that afforded a set of experiences and abilities previously impossible.
However, much like the early stages humanity, we see in typical social media settings that there are no systems in place (like governments) that incentivize good behaviors. Sure Facebook and Twitter are desperately trying with their moderators and censorship, but that is mostly causing a whole lot of outrages, and the solutions they are implementing typically in no way scale with the size of the user base.
The effect of this, as especially seen on Twitter, is a huge population of humanity that essentially exists in a state of unregulated anarchy. And while the consequences of negative behavior may not threaten a person’s physical well-being (except in some cases – I’m looking at you, cyberbullying) they certainly take a non-trivial toll of people’s emotional well-being.
AT THE SAME FRIKIN TIME, the blessed, blessed internet is simply one of the most fascinating and impactful technologies ever developed. The level and speed of connection it provides is simply staggering. The fact that I can host an API in Ohio that I can access in milliseconds from Colorado, well, it’s simply breathtaking. Put in a more relatable sense, I, Danny boi G, can talk to someone in Singapore with millisecond latency. We take that for granted, but I mean, that’s literal insanity.
Anyway, why do I care, aside from my natural inclination towards juicy, juicy tech? Well, despite the extreme toxicity that something like twitter propagates, my hypothesis is that the absolutely insane level of connection afforded by the internet should be able to be used in a manner that benefits humanity and brings us together, rather than tearing us apart.
Now then, let’s get down and dirty with the Parleya experiment. I’ve identified three fundamental processes that are integral to the continued development of humanity.
Connection – human beings need to be able to cooperate in order to accomplish anything. If you live in America, you’ll notice we’re being torn apart by political and social issues, which introduces a wide variety of barriers to continued progress.
Accessibility, Integrity, and Quantity of Information Transfer – In order for human beings to effectively utilize stable subsystems to build stable and sustainable solutions to problems, they must attain the best possible understanding of both the problems they face and the tools at their disposal to solve said problems. Right now many news and media have strong incentivizes to mischaracterize problems due to political agendas, the desire to produce interesting content, and other things of that nature. In order to move forward, we must create systems that incentivize the propagation of accessible information that accurately characterizes the true nature of the information in question.
Analysis of Information – As previously mentioned, forward progress necessitates the use of stable systems to build solutions to problems. In order to build sustainable solutions to problems, we must understand the tools at our disposal, which necessitates a clear understanding of the relevant systems that can be utilized for our benefit.
Yikes that was long winded. Anyway, Parleya aims to address topic number one, ie connecting people. Specifically, the goal of Parleya is to build a platform that incentivizes healthy conversation about traditionally polarizing or controversial topics. If we’re actually good friends in real life, then you’ve heard me talk about Parleya for sure. I just haven’t blogged about it yet because for some reason I didn’t want to.
It has become apparent, however, that I should be providing some level of log to this project, because it’s essentially a scientific experiment. Well, I suppose any startup can be classified as an experiment, but especially this one, because the goal is clear, and the solution is not. Anyway, the purpose of this project is to log my hypotheses, observations, and conclusions with regards to the solutions I try for Parleya.
If you’re wondering what I’ve been coding, it’s Parleya. I’ve been working on it since the end of June, and I just finished the MVP. Shoot me an email if you’re interested in testing out the MVP.
Anyway, as previously mentioned, I’m going to write out my initial hypothesis for the first iteration of the project. Here goes.
As I mentioned, one major problem that I’ve identified with most major social media platforms is the fact that there are essentially no incentives against poor, unproductive behavior. If Kylie Jenner tweets something about her dog, there’s basically nothing stopping me from calling her a selfish whore, just because I’m feeling cranky.
Now, as is somewhat evident, this sort of name-calling behavior, and the ease with which twitter users can mock and dunk on each other does not in any way produce particularly meaningful discussions. Thus the principle goal of Parleya is to find a conversational structure that disincentivizes negative behaviors. Here is my first hypothesis for such a solution.
In a hopefully scientific fashion, I shall lay out the central assumptions I’m making about internet users.
If people are on Parleya, they want to interact with other people. The internet is boring even for trolls if nobody interacts with them.
People typically do not enjoy interacting with people that are obviously extremely aggressive or quick to post personal attacks against other users.
People typically do not enjoy interacting with people who are obviously over-sensitive and unwilling to engage with opinions other than their own. These are the assumptions I’m making. Now let me tell you how Parleya v1 works.
User one posts a conversation about a controversial topic. User two does not agree with user one’s point of view, and therefore posts a mean message with an emotional attack against user one. User one doesn’t like this one bit and decides to block user two’s message. Ok, Danny, I hear you saying. You’re describing social media. What about this is any different from anything else? Well, blessed reader, sit down, hush up, and let me frikin tell you.
The reason why Parleya is different is that conversations and messages are largely anonymous, but three numbers are associated with every message or conversation someone posts on Parleya. Here they are:
The number of times the user has had a message blocked
The number of times the user has blocked someone else’s message
The number of successful conversations of which this user has been a part
You may immediately see why this is useful. If your first number is high, then perhaps you have posted a lot of overly aggressive or offensives messages that people have blocked, which implies you’re not a good conversationalist. If your second number is high, then you have blocked a ton of other people’s messages, which implies you are overly sensitive or triggerable, and therefore not a good conversationalist. Finally, if your last number is high, that implies that you have obviously been a part of many good conversations, and thus are a good conversationalist.
Therefore according to assumptions 1, 2, and 3, people will want to keep their first two number down, and their third number up. Also let me say that explaining this by means of text is probably the worst way to do it, and if you’d like a better demonstration, shoot me an email, and I can demonstrate this app over zoom.
Anyway, as you might be able to see, if assumptions 1, 2, and 3 hold true, then there is a strong incentive to not post offensive messages on this platform, which is essentially what makes the platform different from other existing platforms.
The last part about the app that is cool is that after a successful conversation, you can send friend requests to other users who posted good insightful responses. Thus, even though Parleya conversations are anonymous, after a good conversation, you are able to connect with people from entirely different backgrounds and hear more about them and what informs their opinions.
Ugh, I’m on page frikin 9. Aint nobody got time for a post this long. I’ll add one last thing because it’s important. I got about 20 people who were interested in the testing the app, and what I quickly found is that I can’t approach user beta testing with a laissez-faire methodology, and I need to ensure users understand the platform and the flow of conversations before using it. So that’s where I’m at. I think you’re probably as tired reading this as I am writing this. See ya.
Sup readers. Prepare yourselves for another disjointed post. I’m basically using my blog as a repo for and log of my thought processes.
K, so basically a big thing that I’ve learned about myself is that even though I really enjoy learning about pretty much anything technical (math, physics, CS, etc) it’s immensely hard for me to stay motivated to continue working on a project unless I can very easily discern why the project benefits humanity. That’s part of the reason why I’m really enjoying my current project.
Oh wait. I forgot that I haven’t written a single blog post about my current project yet. RIP. I’ll do that soon. Basically, I’m trying to build a social media platform that psychologically incentivizes healthy, non-violent conversations about traditionally controversial and polarizing topics. I’m bringing this up simply because I perceive the goal of this project as being of upmost importance for the future health of the purportedly self-healing super graph that is humanity.
Anyway, back to Orchid. The reason I bring all this up is because in past months, I haven’t really been able to come up with a compelling reason why building Orchid would be beneficial to humanity, which has meant that it’s somewhat difficult to remain motivated to work on it, which in turn means I haven’t prioritized working on it, which means I haven’t worked on it all that much.
Orchid, however, has been dancing around the back of my head for the past couple of months simply because I think it would be super cool if it worked. If nothing else, it would give me a way to work on learning things like QFT without the overwhelming frustration of working with ginormous equations with pencil and paper. While I personally don’t see learning QFT as a particularly meaningful pursuit at this juncture of my life, the equations that govern quantum fields are super, super juicy, and it’s fun to play around with them.
Anyway, in trying to come up with ways that Orchid could benefit the humanity graph, I’ve had a couple ideas. This first one kinda showed its head in my last post, but I’ll flesh it out a bit more here. Basically, if Orchid works as I intend, it will essentially create a method for storing mathematical entities of all varieties in well-defined computer data structures. Neat. Additionally, the rules governing mathematical manipulations of these particular mathematical entities will also be stored in similarly well-defined computer data structures. The reason why this is compelling is because computers would then have the ability to work with and manipulate these structures on their own, without human interference. Obviously, the algorithmic approach the computers would take in manipulating the mathematical structures would be defined by humans, but it would essentially allow computers to perform the same sorts of computations humans do all by themselves.
Why is this potentially cool? Because up until this point, most mathematical software is essentially super-powered calculators. Mathematica, for example, has been built over the last 30 years, and during that time, human beings have translated all varieties of mathematical processes into code. There’s a reason it takes up like 20 GB. It’s gigantic. But if you want to numerically solve erf, like I did back in high school, well then boy is Mathematica for you. How is orchid different? Instead of having a bunch of hard-coded algorithms for solving and manipulating previously defined mathematical expressions, Orchid allows you to define entirely new mathematical entities and the rules that govern them. This, furthermore, allows users to have a central location for creating a manipulating all varieties of mathematical entities.
Not only that, but the computer itself would have a way of creating and manipulating exotic mathematical structures. This means that computers would be able to do what previously could only be done with pencil and paper, or on a blackboard. Instead of slaving away doing a bunch of predefined calculations, computers could actually be “doing the math” in the same way that humans have for the last several centuries.
I imagine it might not be immediately clear why computers doing pencil and paper mathematics would be beneficial to humanity. Let me explain as clearly as I can. Mathematics has provided humanity with perhaps the most robust and effective method for quantitatively understanding the world around us. And when humans better understand the world, they can make better predications about the state of the world. As I’ve discussed in previous posts, whenever a structure exhibits stable characteristics and behaviors, that structure can be effectively utilized in the creation of another, larger stable structure. In this context, that means that whenever humans are able to understand the stable characteristics and behaviors of a system, they are frequently able to use that system in a manner that increases humanity’s overall fitness.
Theoretical physics, as a field of study, is perhaps the best and most well-established example of what I’m describing. The phone in your pocket, the missile defense system that keeps you safe, and the lightbulb that illuminates your house are each examples of the staggering amount of technologies that fundamentally would not exist without developments in theoretical physics.
And what is theoretical physics? It is the practice of modelling physical systems in terms of well-defined mathematical structures, and then making predictions about the systems themselves using well-defined mathematical manipulations on those structures. In case you are wondering, experimental physics is the practice of designing and carrying out experiments to gather data on physical systems. Analyzing these data sets is what allows theoretical physicists to determine the degree to which their models accurately describe reality. So, if you’ve ever wondered what those nerds up in national labs, universities, or particle accelerators are doing, it’s that.
Physics is all fine and good, but I’ve found that much of what goes on in modern day physics doesn’t actually seem to affect many people. Some of it certainly does, but a good deal of it is documented in papers that 99.99% of humanity can’t understand and don’t really do people any good.
However, there are plenty of other real-world systems that could be analyzed using the aforementioned methodology. Data scientists are basically the people attempt to understand large data sets using machine learning or other statistical methods. From what I understand of current practices in data sciences, there really isn’t a large amount of coming up with novel mathematical models for understanding data sets in a manner similar to theoretical physics. There certainly is some, but nothing compared to physics.
And there’s a very good reason for this: coming up with appropriate mathematical models for different systems requires a huge amount creativity and intellectual capacity. In other words, it’s really, really hard. Ever wonder why everyone thinks Einstein was so smart? It’s because he came up with extremely precise mathematical frameworks for describing relativistic systems. He did a bunch of other stuff too, but he’s celebrated mainly for his ability to create compelling mathematical models for physical systems. And let me tell you, General Relativity is no small pill to swallow. There are a ton of moving parts and different mathematical structures at play, but my gosh, the resulting theory is objectively gorgeous.
Anyway, I could fawn on about GR all day long, but that’s not why we’re here. The reason Orchid is compelling is because it would drastically simplify the process of coming up with mathematical models to describe different systems. Not only that, with the right set of algorithms, the computer could by itself create mathematical models to describe data sets.
That last sentence probably didn’t have the desired effect on you, so let me rephrase. Orchid could potentially allow a computer to do the same thing Einstein did that made him famous as one of the smartest people in history.
IMHO, that’s pretty dank. But even if that last bit doesn’t happen, Orchid would still provide humanity with a framework for easily constructing and manipulating mathematical entities, which could in turn be used to understand the world around it with a degree of precision previously unattainable.
Well, maybe that’s being overly optimistic. We’ll see.
Anyway, when I started this post, I wasn’t going to talk about Orchid, I was going to give the recipe for consistently and efficiently modelling a system mathematically. Here goes.
Just hit page 7, which is about 5 pages longer than I thought this post was going to be, so I’m going to wrap this sucker up. I guess as one last thing, if this stuff interests you, shoot me an email. After leaving Berkeley, I haven’t talked to a lot of people interested in this stuff.
May your socks always come bedecked with cool designs. Peace.
Sup readers. Prepare yourself for a post that will make absolutely no sense. Or it might. I’m not really sure yet. Basically, I’m revisiting Orchid, and I’m attempting to determine how to make it fundamentally useful.
The fundamental shift in my thinking that I just recognized is that in order for a mathematical model to be useful, it must be defined within a particular context. I realized two nights ago that if the entire game of complexity comes down to stable structures with well-defined behaviors, and humans are good at categorizing such structures, then in order to replicate it, you need a machine that is able to meaningfully describe the set of characteristics and structures of a particular stable structure it encounters by means of data. So the goal is basically three steps. One: Develop a universal method for describing the characteristics and behavior of stable structures in terms of computer data structures. This is and has been the entire purpose of Orchid, as mathematical entities are essentially perfected abstractions of perfectly stable structures. Two: Develop a method for extracting a set of characteristics and behaviors about a particular stable structure encountered in a data set into the data structures discussed in step one. Three: Develop an algorithm by which computers can meaningfully interact with these data structures in order to make meaningful and increasingly refined predictions about the structures in question.
I’ve already worked out a good deal of the difficulties of step one during my previous efforts with Orchid, but it’s really step two that’s giving me trouble. I presume step three will be the most difficult, but I’ve logically decided not to even consider that yet as to preserve the amount of unpolluted thinking space that currently exists in my brain. Anyway, step two. How do we possibly do this? My first goal is to essentially translate simple statements into mathematical structures that are meaningful. So take this, “If I stack blocks on top of each other, I end up with a taller structure.” Incredibly simple statement, right? Well, how do I translate that statement into a working mathematical entity? That’s a pretty tough question.
I think my mistake for the past day of thinking about this is that I was attempting to match any object or stable structure with a corresponding mathematical entity. Ideally this mathematical entity would be sufficiently robust to fully describe the object in question, including the object’s behaviors. But that’s really tricky. Take me for example. If I jumped off a cliff, a meaningful question might be, “How long is it going to take this boi to hit the ground?” Good question, reader. I certainly would like to know how many seconds of life I have remaining. However, imagine I insulted a friend of mine, causing them to be angry (purely hypothetical, (hehe)). Based on my previous method of description, I would have come up with a mathematical entity that described Danny Geisz and used that object to model the two previous situations I described. But what sort of object would I be? Like, for real? Should I be modelled as a mapping from my environment to a particular phrase, which would in turn be modelled as a mapping from my friend’s previous emotional state to his/her final emotional state? What about the first situation? Should I simply be approximated as massive object as traditionally used in kinematics? If that were the case, then I would be a simple scalar: mass.
I’d like to think that there’s a bit more to me than my mass, so that’s clearly not the way to go. Maybe a slightly better method for modelling myself would be as a cartesian product of a variety of sets that together describe my characteristics and interaction with reality. Still, though, that seems insufficient and highly disorganized.
What I’m realizing even as I write this is the importance of context. The context of me jumping off a cliff ought to be modelled differently than the context of insulting a friend. Specifically, (and now I’m really going stream of consciousness) a particular question should be posed, and a particular quantity studied. More specifically, the characteristics and behavior of the entity being studied should be described in as great a depth as reasonable by mathematical language, and everything else ought to center around that main model. For the example of me jumping off a cliff, the two important quantities are time and my height off the ground. When my height reaches 0, we measured the time elapsed, and wala! We found an accurate prediction of the time I have left to live. (Congrats, Danny, you’ve done basic kinematics).
The situation of the emotional state is a bit less traditional. I think in this situation, the important quantity is the friend’s emotional state. Then we can regard my insult as a mathematical mapping of the previous emotional state to the final emotional state. Furthermore, we could model me, Danny Geisz, as a mapping from my current emotional state, to the words I said to my friend, which affected his/her emotional state.
In Quantum Mechanics, a particle is described as a wave vector. Why? Because simple mathematical manipulations on a wave vector yield interesting quantities like a particles position or momentum (specifically the probability that a particle will have a specific position or momentum). So basically, the interesting quantities of a particle (within the context of QM) are modelled as a wavevector, and any other entities that interact with the particle are modelled as transformations on the wavevector. Neato.
I suppose my goal, however, is to build a computational system that’s capable of analyzing a set of data and generating mathematical models that describe the data. These mathematical models could then be used to make a more cohesive and robust set of predictions about the world than the models traditionally associated with machine learning. If I’m trying to build a computer that beats a human, I need it to be able to replicate the human experience and do it in a manner superior to humans. Humans are really quite good at classifying objects and using logic to make predictions based on their “modelled” view of particular stable structures. So I want Orchid to do this, but better.
After writing this, I’m realizing that simply regressively generating mathematical models isn’t sufficient for the level of classification I require. I think I need to do some more thinking about the relationship between a structure and a mathematical context, because that’s the space where computers could excel relative to humans. Ok, that’s all for now.