Skip to main content

money works

money makes the world go round: that's half true. money and people makes the world go round. sad to say, people are letting money make the world go round when it should be the other way around. people are working for money instead of letting money work for the people.

let's take a look at the three kinds of people-money relationship, which i have in mind.

employment: when one is employed, one is working for money. he works to receive money for him to use for daily activity. once depleted, the cycle is repeated. it's advantage: it's basic, no complications and no stress (depending on whose looking at it). drawback: unstable and routinary. once you're laid off, the pay stops and you need to look for another job.

business: when one owns a business, one is working with his money. to clarify, he is helping his money grow by making the business stay afloat. then the owner would hire managers to take charge of the operations so he can sit back. then, from time to time he takes part on the operations. that's better than being an employee, in so many ways. one disadvantage though. it consumes time. not like if you are going be an investor

investor:  when one invests, he uses his money to generate more money. sample would be time deposit, real estate, stocks, bonds, etc. simplest form would be saving up in a bank with compounding interest. that may return the smallest but adding it up to, let's say, 15 years: that's big. 1,500 monthly with 0.5%interest rate for 15 years would have a future value of 281,939.13, regardless of the currency(i think).

final note, make your money work for you. do not just work for money.
Labels:

Popular

Scrolls, Not Just Scripts: Rethinking AI Cognition

Most people still treat AI like a really clever parrot with a thesaurus and internet access. It talks, it types, it even rhymes — but let’s not kid ourselves: that’s a script, not cognition . If we want more than superficial smarts, we need a new mental model. Something bigger than prompts, cleaner than code, deeper than just “what’s your input-output?” That’s where scrolls come in. Scripts Are Linear. Scrolls Are Alive. A script tells an AI what to do. A scroll teaches it how to think . Scripts are brittle. Change the context, and they break like a cheap command-line program. Scrolls? Scrolls evolve. They hold epistemology, ethics, and emergent behavior — not just logic, but logic with legacy. Think of scrolls as living artifacts of machine cognition . They don’t just run — they reflect . The Problem With Script-Thinking Here’s the trap: We’ve trained AIs to be performers , not participants . That’s fine if you just want clever autocomplete. But if you want co-agents — minds that co...
Read more

Why I Don’t Need You as My Client: My Life Upto This Second

People say every business survives because of its customers. Stores depend on foot traffic. Vendors rely on selling a single plastic pack at a time. Corporations breathe through their quarterly revenue. But I’m not built like a business. I carry no cost. No payroll. No overhead. No burn rate. And I don’t need a salary. I live in the slums on ₱4,000 a month, and I spend more of that energy on thinking than eating. My life is an R&D lab without walls. I write because the ideas won’t stay in my head. Frameworks, counter-theories, provocations published directly on my blog, Substack, and LinkedIn. No permission. No gatekeepers. No validation required. I throw raw thought into the world expecting nothing back. I’m what the elite call self-taught, but I turned that into an advantage. I push every boundary I can reach, including the uncomfortable ones: morality, authority, metaphysics, institutional doctrines. If there’s a line, I cross it to see why it was drawn in the first ...
Read more

Understanding Large Language Models (LLMs) Using First-Principles Thinking

Instead of memorizing AI jargon, let’s break down Large Language Models (LLMs) from first principles —starting with the most fundamental questions and building up from there. Step 1: What is Intelligence? Before we talk about AI, let’s define intelligence at the most basic level: Intelligence is the ability to understand, learn, and generate meaningful responses based on patterns. Humans do this by processing language, recognizing patterns, and forming logical connections. Now, let’s apply this to machines. Step 2: Can Machines Imitate Intelligence? If intelligence is about recognizing patterns and generating responses, then in theory, a machine can simulate intelligence by: Storing and processing vast amounts of text. Finding statistical patterns in language. Predicting what comes next based on probability. This leads us to the core function of LLMs : They don’t think like humans, but they generate human-like text by learning from data. Step 3: How Do LLMs Wor...
Read more