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returning to the scene of the crime

it's been a while since i created a web page. and now im like a returning prodigal son aiming to get back what i lost. getting thru the same process i walked thru back then - studying. i visited few sites ive created and found them to be boring so i wont put their links here. hahaha! then i stumble upon my site(i want to call it that) - http://www.geocities.com/orpheum_ph/ and remembered that i have created something for myself... a tool for web design. something to start with... and i would like to tap my back for that. and so, i decided to get back into blogging and pst this.

hopefully, i would complete my tool and maybe start on a portfolio. wish me luck!
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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...
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Wrestling with an Old Acer Laptop to Install ALBERT—And Winning!

You know that feeling when you take an old, battle-worn laptop and make it do something it was never meant to handle? That’s exactly what we did when we decided to install ALBERT (A Lite BERT) on an aging Acer laptop. If you’ve ever tried deep learning on old hardware, you’ll understand why this was part engineering challenge, part act of stubborn defiance. The Challenge: ALBERT on a Senior Citizen of a Laptop The laptop in question? A dusty old Acer machine (N3450 2.2 GHz, 4gb ram), still running strong (well, kind of) but never meant to handle modern AI workloads. The mission? Get PyTorch, Transformers, and ALBERT running on it—without CUDA, because, let’s be real, this laptop’s GPU is more suited for Minesweeper than machine learning. Step 1: Clearing Space (Because 92% Disk Usage Ain’t It) First order of business: making room. A quick df -h confirmed what we feared—only a few gigabytes of storage left. Old logs, forgotten downloads, and unnecessary packages were sent to digita...
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envelope budgeting

i've always had a hard time saving up for the rainy days. i'm always stuck in the part where i have no idea where the money is going to. and believe me, i hate that part. so i scoured the net to look for ways how to solve this eff-ing problem and googled(i wonder if this verb is already an entry in the dictionary) budgeting . then i thought, why don't i just check its wikipedia entry . unfortunately, all information inside that entry were on a macro-scale of the word itself. and fortunately, except the "see also" part. there lies the phrase envelope system . although there's just a small info about it, the description how the system works gives enough overview on how it works basically: enough to make me save. "Typically, the person will write the name and average cost per month of a bill on the front of an envelope. Then, either once a month or when the person gets paid, he or she will put the amount for that bill in cash on the envelope. When the bi...
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