Skip to main content

i start to save

In line with my previous post entitled saving money weekly, I start to save. I want to prove that I can do what I preach. So, I got myself an another account aside from the payroll where the funds will be coming from


Nothing special... just a regular saving account from a local bank.

Happy Saving!
Labels:

Popular

Prompt Analysis Using First-Principles Thinking (FPT)

Instead of memorizing existing prompt patterns, let’s break down Prompt Analysis from First-Principles Thinking (FPT) —understanding what makes a prompt effective at its core and how to optimize it for better AI responses. Step 1: What is a Prompt? At its most fundamental level, a prompt is just: An input instruction → What you ask the AI to do. Context or constraints → Additional details that guide the response. Expected output format → Defining how the AI should structure its answer. A well-designed prompt maximizes relevance, clarity, and accuracy while minimizing misunderstandings. Step 2: Why Do Prompts Fail? Prompts fail when: ❌ Ambiguity exists → The model doesn’t know what’s truly being asked. ❌ Lack of context → Missing background information leads to weak responses. ❌ Overloaded instructions → Too many requirements confuse the AI. ❌ Vague output expectations → No clear structure is provided. ❌ Incorrect assumptions about AI behavior → The prompt d...
Read more

Contextual Stratification - Chapter 25: AI and Technology

  Machines at Boundaries In 2016, AlphaGo defeated the world champion at Go, a game so complex that brute-force computation seemed impossible. The victory felt momentous: machines mastering domains requiring intuition, pattern recognition, strategic depth. Then researchers tried applying the same system to StarCraft, a real-time strategy game. It struggled. Same underlying architecture, different domain; and the framework that dominated Go couldn't transfer. This isn't a flaw in AlphaGo. It's a demonstration of contextual stratification in artificial systems. The AI learned F_Go at λ_board-game with M_Go (measurable game states, valid moves, winning positions). That framework produced brilliant Q_Go (optimal strategies, creative plays). But F_Go doesn't apply to F_StarCraft at λ_real-time with different M_StarCraft. The boundary between frameworks isn't crossable by mere scaling. It requires different architecture, different learning, different framework. AI system...
Read more

Agile Transportation System (ATS) Values and Principles

Here’s a draft of the Agile Transportation System (ATS) Values and Principles. ATS Core Values Adaptability Over Rigidity - ATS prioritizes flexible route adjustments and dynamic scheduling based on real-time demand rather than fixed, inefficient routes. Availability Over Scarcity - There should always be an ATS unit available when and where it's needed, reducing wait times and ensuring continuous service. Efficiency Over Redundancy - Every unit must maximize passenger load without compromising speed and convenience, ensuring an optimal balance of utilization. Simplicity Over Complexity - Operations should be straightforward, avoiding unnecessary bureaucracy and ensuring seamless passenger movement. Continuous Improvement Over Static Systems - ATS evolves based on data and feedback, refining operations to enhance reliability and customer satisfaction. Customer Experience Over Just Transportation - The system is not just about moving people; it's about making their journe...
Read more