Not having any actual, real, true friends nor a significant other seems like a tragedy. And yet, it's all my fault, a natural state of affairs given my personality. I end up making people get bored. I've nothing deep, interesting, insightful, fun, or amusing to tell anyone.
My existence is particularly uneventful. I'm in my late 30s in my 4th year in a Computer Science major. I feel I merely exist by inertia or momentum, not really having a will to live at all. I've considered plans for the future, like pursuing a Master's and even a PhD degree in Computer Science, while teaching undergrad courses.
However, I don't feel particularly excited about anything at all. If I were to die today, it would be just as uneventful as my existence. Suicide is a recurrent leitmotiv in my thoughts, but I just can't make myself do it. I tried once in August-September 2005, but not seriously. About any suicide procedure is prone to be extremely painful and to fail somehow.
Indeed, I know I deserve to be alone for the rest of my existence. I can't operate like a fully functioning human. I'm more like a pseudohuman, devoid of a sense of self-dignity.
Existing like this is mentally painful and exhausting. But no therapy has ever worked well for me.
I started my Computer Science degree at University of Costa Rica in 2006, after a 1-year stint in technical support (in German, by email) at an American corporation. Before that, I graduated from a German-Costa Rican school and planned to study Computer Science in Germany. RWTH Aachen seemed like a great idea back then, but I didn't have the necessary funds nor a scholarship.
I was never a bright student. I especially regret not being able to excel in mathematics. It's a subject I deeply respect, as I consider the physical and abstract realms as inherently mathematical structures, which no sentient entity will ever fully understand (due to Gödel's incompleteness and such).
However, my appreciation for mathematics lead me to enroll in a Mathematics major, a few years after I started Computer Science. Academically, it seemed like a poor choice, but I deeply wanted to know what mathematics was really about, beyond engineering applications without much proof.
It was a most hopeless, sterile period of courses dropped and retaken. But I was able to confront myself in new ways. I lost against myself time and again, as I was bound to fail in that major from the onset. I didn't have the required stamina, focus, study discipline, insight, and other characteristics a math major would need.
I went back to Computer Science, but I was disillusioned from the beginning. Courses were challenging, but not in ways I expected. It was more about hard, dull work (e.g., debugging Java and C++ exercises) than deep computational problems.
Thus, I got bored and moved full-time to industry for about 4 years. I got the required experience in parallel to my studies. During all that time at uni, I was somehow involved in technical work. Like installing and maintaining Linux server infrastructures all over the uni, either as sole sysadmin or as an assistant to a senior sysadmin.
However, I got burned out from industry, quit in 2019, and came back to Computer Science at the uni. Just in time for the pandemic, I resumed my degree. Still, I'll graduate from a BSc degree in my late 30s. Getting back to industry doesn't seem like an option to me. Making money for others by maintaining computing systems isn't appealing to me, even when the technical challenges might be interesting.
Academia seems interesting, but I have deep and serious doubts about my skills as a Computer Science professor. A respectable professor doesn't just present topics. They challenge students with questions worth pondering about. Is there a more suitable algorithm for the problem at hand? Why would a given OS kernel or network routing configuration become troublesome at scale? Why is a given implementation of a protocol insecure with certain settings? They ought to be able to come up with such questions, by thinking on their feet during the timespan of a lesson.
In theory, human rights are universal and inalienable to all human beings. But, in practice in a late-stage capitalist society, human rights become commodities with a price tag. Justice never works the same for the rich and the poor, the economic elites and the excluded minorities.
The whole experiment with democracy, human rights, and rule of law in the Western world seems to be coming to an end. Large populations can be controlled and exploited with violence in many forms and shapes: physical and psychological, explicit and implicit, political and economic.
Production systems works the same in failed states and authoritarian regimes, as in "full democracies" and "free societies". There was never a real democracy or real freedom to begin with, as whole societies end up serving elites. "Free market" is an oxymoron: elites end up rigging any production system, by means of economic influence.
Ethics of people in power have a price tag, like everything in the human world. Elites frequently pay for it by means of bonuses, gifts, stock options, and many other means. Markets can't regulate themselves: market players rule over each other until a hierarchy emerges. Balance in matters involving large sums of money cannot exist. A dominant set of players ends up taking everything.
The only way out is not to believe in money, but it's infeasible. Money should be considered a toxic waste, like hydrogen cyanide, a substance that is odious to handle and store. A substance that corrodes, burns, and poisons. But our means of exchanging goods and services is precisely through that toxic waste.
I think I finally found my way in computer science, in the sense that I know I want to do research in theory of computation. Specifically, continuous or analog models of computation.
For instance, is it possible to design and implement sufficiently secure cryptography (e.g., post-quantum) using differential equations?
It seems like a road that leads nowhere, a dead trail of research (vs. AI and all the fancy trends). But it's computer science (and the very core of it) all the same.
I've been pondering about alternative models of computation for years. But I didn't have the necessary foundations to make sense of what I was looking for.
I took an introductory course to computability and complexity, which at least provided me with the basic concepts. But being able to do research in continuous models of computability is a different matter altogether.
Funding for such foundational research in theoretical computer science is almost nonexistent worldwide, except in very specific institutions under very specific conditions for very specific kinds of researchers.
However, I hardly expect anyone in computer science in my country to be able to appreciate the importance of research in continuous models of computation.
My country is socially falling apart due to down-to-earth threats (e.g., an alarming murder rate due to organized crime), and academia is supposed to be providing practical solutions.
What if we were able to build a rock-solid theoretical computer science research community, which supported strong applied research, which translates to local companies that created well-paid jobs?
That long-term vision is discouraged in my country. It's considered delusional at best, even when countries like Singapore and South Korea achieved that level of development. They have other kinds of social issues, though.
My major has 3 concentrations: Software Engineering, Computer Science, and Information Technology. Naturally, I chose the Computer Science one. But there's a caveat: differential equations (for future engineers) is a graduation requirement.
While they own their place in many engineering fields (mechanical, civil, electrical, etc.), they seem totally out of place in computer science. Computing is considered a realm of discrete math: combinatorics, Boolean logic, etc.
My professor gave a very particular assignment: we have to write a research paper about applications of differential equations in our major.
Applications like signal processing (cf. Fourier series) and microprocessor thermal management (cf. heat equation) are reasonable choices. But I really wanted to find an application of differential equations in the very core of computer science. It turns out that continuous models of computation, a novel and unconventional (even esoteric) area of research, is that application. A research paper on the main findings in that area might do for the assignment.
Nevertheless, it turns out that my professor accidentally opened a whole can of worms with that nondescript assignment: what if we could make differential equations a fundamental pillar of computing, like representing concrete programs as differential equations, and computational systems as systems of differential equations? For instance, how does Dijkstra's shortest path algorithm look like as a differential equation (e.g., a linear PDE)?
Years ago, I wrote to Leslie Lamport about the idea of representing programs as matrix operations. He advised making up some small, concrete example and building up from that. Even if I hit a wall, I would learn something new. But I neglected the advise and shelved my idea.
However, that idea of programs as differential equations, which has been studied in theory by Olivier Bournez (https://hal.science/hal-03668008), might well work in practice. That is, at least a respectable professional researcher (from the Computer Science Laboratory at École Polytechnique) has investigated on that line of research.
Which is far more reassuring than a dubious idea of "programs as matrix operations" by such a sketchy character like me.
Given my academic mishaps, as in failing (or dropping) and retaking courses from the math and computer science majors, I'm fully aware I'll never be in a legitimate position to lead any kind of research program in continuous models of computation (or anything at all in computer science).
And yet, I don't personally know of anyone who might be deeply interested in the field of continuous models of computation. Indeed, there are some at the École Polytechnique, Oxford, etc. (cf. several members of the Association Computability in Europe). But probably not at my computer science department.
My years as a math undergrad student shaped that interest. Initially, I assumed it was enough to discretize and approximate phenomena. But the (late) professor I consider my academic mentor, a nonstandard analyst, observed that a lot of relevant information was destroyed when discretizing processes.
There were also the logicians at the math department, like a professor who worked in bounded arithmetic. That area is the closest I've seen to actual research at the very core of computer science. For instance, they dealt with hierarchies of complexity classes in a principled way.
Math and computer science went their own ways and are bound to stay as distinct, separate academic fields. Including very different scientific approaches on the nature of abstract processes, phenomena, and structures.
Still, I wish the math and the computer science departments could work together in fundamental and foundational research in the theory of computation. They exist in academic silos, though, like development teams at a software company.
The one and only purpose of my existence is to be a cautionary tale to others. A cautionary tale of what someone interested in academic research should never, ever be.
I have no stamina, resilience, grit, ambition, sense of purpose, academic maturity, or emotional or affective coherence. A respectable researcher in computer science cannot make any progress whatsoever without those traits.
Being considerably interested in a topic is no replacement for being actually proficient in effectively solving deep research problems in the topic. Just like exploring papers, books, and thesis about a topic is no replacement for actually mastering the topic.
I totally know I can't ever aspire to become a respectable researcher in theory of computation. If I were to publish, my results would be full of blatant errors of logic from beginning to end.
My preprints would automatically waste the time of journal and conference reviewers at Springer, Elsevier, Wiley, IEEE, ACM, etc. I would merely add lots of disposable noise to valuable signal.
I'm a cautionary tale myself.
Whenever I have a math exam, I feel stranded, as if I were physically removed from my everyday urban environment and landed on an uninhabited South Pacific island.
I perceive an uncanny atmosphere, as I reason about exercises and write procedures to solve them. It's a deeply eerie feeling, writing in constrained ways that are unnatural to me.
I suppose I'd feel more comfortable in an oral math exam. Solving exercises on a whiteboard and verbally explaining my solutions to the professor, perceiving their body language, interacting "online" with the evaluator as I'm evaluated. Not in an "offline" batch of written reasoning.
On the other hand, I'd feel intimidated and inhibited if I perceived the professor as hostile. In contrast, a printed set of standard issue exercises doesn't feel like anything in particular.
Taking a fundamental discrete model of computation and expanding it to the continuous domain is indeed a low-hanging fruit. And a very tasty and nourishing one at that, too.
The implications and applications of that expanded model, though, are indeed deep. In turn, capitalizing and building on that expanded continuous model of computation is a low-hanging fruit.
If I can come up with that idea (i.e., building a research and development pipeline based on continuous models of computation), I think anyone can. World-class students and researchers must have considered that idea early in their studies.
I'm at the rock-bottom level of proficiency and capacity in computer science academia. I was expected to graduate over a decade ago and have a PhD by now. That is, I'm as far as possible from being any kind of genius.
I still remember my (late) math professor, the nonstandard analyst, talking about a computer science professor who was a classmate of him. Back then, the math major and the computer science major shared courses, like real analysis.
The parents of that computer science professor ran a flower shop. My math professor considered that the computer science professor should have continued with the flower business, instead of choosing an academic career path.
My math professor had quite a low opinion of many people around him, either in terms of academic profundity or ethical qualities. He often mentioned some people in uni administration were sociopaths.
Ideologically, my math professor was an atheist and anarchist. That influenced me considerably, but I think of myself as not a complete atheist (there might be some superior entity, but we might not be able to communicate with it) nor a complete anarchist (at scale and in the long term, humans form social hierarchies, which require competent leaders).
He thought of me as someone who might be professionally better suited for computer science instead of mathematics, while taking up math as a hobby. However, he thought of me as a potential future professional in computer science industry, but never in academia.
Given my poor academic profile, as a student and a possible researcher wannabe, he might have considered I should have taken over ownership of my parents' grocery store business (they are now around their 80s), instead of me trying to become a computer science researcher.
After all these years, I still wonder about the general theory of mathematical structures as models of computation. Not only polynomial differential equations, but also nonsingular square matrices, topological vector spaces, algebraic plane curves, etc.
It is especially important to understand how these mathematical objects can be used to represent programs. For instance, it's not about implementing algorithms in C++ or Rust or Julia for calculating multivariable systems of polynomials. Instead, it's about representing those algorithms in multivariable systems of polynomials themselves.
That is, to what extent can a given mathematical structure act or operate or execute over other mathematical structures to produce computations? How can we move from the merely descriptive to the computational without leaving the realm of mathematics?
Writing system software or user applications only using structures from abstract algebra or real analysis or differential geometry isn't why most students currently enroll in computer science. But it might well be in the future.
Perhaps having computer science as a discipline outside mathematics is merely a temporal and convenient measure, while we sort out how to embed computing back into math. It'll probably take centuries, though.
For some reason, I feel abandoned if I move away from math, even when I'm considerably sloppy at doing math.
To me, mathematics is a source of deep joy when everything works, and deep mental pain when nothing works.
Mathematics is the ultimate realm where thought develops, where phenomena are abstracted to their utmost and their underlying fundamental relations can be finally understood.
A part of me wants to reenroll in the math major. But I know I just don't have what it takes to become a mathematician. From the outside, a major in math seems achievable. Once inside, everything becomes an insurmountable challenge to me.
If I'm this interested in computational mathematics, where's my own computer algebra system with my own implementation of Gröbner basis, Wu's method, and Risch algorithm?
I long to have the stamina, resilience, and focus to work on that implementation. Perhaps in OCaml. I barely know it, but I'm aware it's sound enough for mathematical software. Coq is implemented in that language.
But I feel embarrassed when I write code. My logic blunders and blemishes leak through. My design flaws appear to any experienced developer as plain as day.
Not only Dijkstra would be looking over my shoulder and disapproving my design and implementation decisions, but all of ACM Turing Award recipients: Lamport, Knuth, Hoare, Hopcroft, Floyd, etc.
It's painful to create something that nobody will use, that is plain ugly, and that has no real value. I fear writing wasteful software, even when code is cheap (vs. using physical media in material objects).
Being an anarchist means that anything like a position of power over people feels deeply disgusting, either in academia, industry, government, or NGOs.
Socially climbing for the right to rule over people is a waste of human existence. Hierarchies are arbitrary and artificial. The additional pay isn't worth it.
Being remembered for posterity as someone who climbed positions of power doesn't seem like a legacy worth living. Actual work is done by actual workers, not managers or directors or presidents.
To me, theoretical computer science, as in computability, complexity, analysis of algorithms, theoretical cryptography, information theory, and some other fields, are the very raison d'être of computing.
Other computing fields involving systems and applications are important. But they intrinsically depend on the foundations of theoretical computer science.
Despite that fact, fundamental research in computer science is often far less popular (and financially supported) than applied research.
The rationale behind research funding is that some (hopefully successful) market product or service should be the end result, so as to justify the investment in research.
Nevertheless, science is supposed to be studied for its own sake, not to please industrial shareholders. They can get their irrelevant money in many other ways.
Being remembered for eternity as someone who directly helped solve some deep research problem is an honor far greater than being the CEO of a 3 trillion dollar corporation.
No money in this world can solve nature's puzzles in any provable way. It's an incentive to those who work in science and the infrastructure that sustains science and academia. But, by itself, money is worthless.
It's all too easy for me to concoct mental scenarios where I kill myself. In those scenarios, taking place at a company, at the uni, or at home, I slit my throat, stab my heart, and slash my stomach, hoping to bleed enough to render myself unrescuable by paramedics.
Existence is too horrible and painful to find anything that makes it worth it. And I haven't yet experienced the utmost everyday hell of situations like extreme poverty, serious physical disability, or extreme violence by gangs. But I might in the future.
One's death is not to be feared, but to be wished. Especially if it's fast and painless. Nothing in this world is worth existing. Nothing in this world is worth having children, either.
My opinion of humanity as a whole is much too low for appreciating life. Over the years, I became painfully aware of how worthless my own life is. No psychologist or therapist has ever changed my perspective, nor ever will.
That field encompasses a wild, wide variety of areas at the intersection of computation and mathematics. But I'm nowhere near close to be a competent student or researcher in that field. I would have to excel at both computer science and mathematics, as in being mentally sound enough to publish some coherent result in complexity of analog cryptographic circuits, desigining and implementing my own computer algebra system, and other kind of tasks.
If I ever were able to start a Master's or a PhD program related to computational mathematics (e.g., in Linz, Saarbrücken, Aachen, Edinburgh, Toronto, etc.), I know I'd feel totally out of place from the very beginning. I'd perceive myself as an obscenely imbecile outcast, among extremely bright researchers from all over the world.
Even at my home country, I feel out of place at 37 as a BSc student, while the rest of the class is 25 at most. I've wasted my country's and my parents' resources because of lack of focus, stamina, resilience. In other circumstances, it would be totally justified to be extrajudicially executed and buried in a mass grave. I deeply know my very existence is beyond wasteful. I don't want to exist.
I've never had a significant other. And I know I won't, given my personality. Nature is deeply wise in prohibiting me to help bring offspring to this world with my genetics. While there's the eternal nature vs. nurture debate, there's always a nonzero probability that my hypothetical offspring develops my states of severe mental confusion, clinical depression, generalized social anxiety, partial dyscalculia, partial anhedonia, etc.
My hypothetical offspring might well develop a sheer hatred towards me, once they realize the kind of hell the world is. Additionally, I know I wouldn't make a reasonable father. I don't have the stamina to be a responsible and caring parent. I would project my insecurities, fears, and unrealistic expectations onto my offspring.
In my heart of hearts, I generalize my pessimism and personally advocate voluntary human extinction. I tried myself in August-September 2005, but I guess I'll have to wait for an opportunity to become extinct myself. In fact, my very existence might be a threat to other humans, due to my deeply ingrained pessimism and bleak perspective about life and existence.
I felt particularly worthless while waiting for our turn for presenting a project proposal in design of experiments. Suddenly, I perceived the perversion and wickedness of what higher education in computer science actually means.
By themselves, theoretical aspects and practical applications of statistics seem like a reasonable foundation for every future engineer. However, in the real world, an experiment proposal is a high-yield weapon against their creators. Every methodological error, every missing consideration, every mishap, every typo or wrong equation term is a trigger.
Professors often advise that external criticism about one own's academic work is not to be taken personally. But I could perceive raw evil seeping through every observation: an abstract eugenics program to root out potential graduates unsuitable for real-world capitalism.
The suicide crisis in academia is completely understandable to me. Triggering events during a term make me ponder about how to effectively kill myself: what kind of knife to use to stab my heart, how to handle the blade to slit my throat wide open, how to avoid being rescued before my brain runs out of oxygen.
But it's only a collateral damage in the academic-industry complex. Suicides are mourned and promptly forgotten, as the pipeline of suitable graduates must keep running. Humans are merely a disposable tool for industrial production.
In my heart of hearts, I advocate for abortion whenever reasonable, suicide whenever feasible, euthanasia whenever applicable. There's no point in living, really.
People in favor of life are deeply delusional, in that they state that life is worth living. It never ever is. There's absolutely nothing in human existence that is worth the pain and suffering of being conscious.
I'm still alive because I'm too lazy to kill myself properly. Effective suicide in practice is harder than it seems. Disappointingly, there's a myriad of ways a suicide attempt can fail.
Choosing my birthday as the day when I kill myself has a plus side: calculating my age when I died would be easy.
Perhaps I'll kill myself next year, or the next one after that, or some other year. There are emotional constraints that still bind me to this realm of existence.
Choosing to die just because I don't feel I fit in this existence is a reasonable argument in favor of suicide. I was never the kind of person I wanted to become. I always oversold and underdelivered. Or didn't deliver at all.
As for the pain I'd leave in the world due to my physical absence, I know people would promptly forget about me. I wouldn't grief my own death.
I realized the kind of person I wanted to become requires too much endurance and stamina. I never had enough strength of being to want to go through that path.
My peers obviously mistrust me. I would't trust myself either. At 38, I'm too old to be a computer science undergrad. I don't have another degree.
What have I been doing for almost 20 years, whereas my classmates will graduate in less than 10 years since they began their studies?