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restoring an '86 gt lancer

i decided to restore our car after a year of driving it daily - well, almost. this bone maroon box machine is one mean machine. not that it's faster than the others, but it's definitely tougher. imagine a 100 km travel everyday for 8 months. i bet that would wreck your car.
as of now, this baby will wear motorized fender mirrors, '82 gsr grill and a fresh paint job. nothing ricey, just a back to basic stock car. still hoping to get stock steering wheel ang 13" stock steel rims but they're still hard to find.
i'll be posting more pics of bM(box machine is it's name) in the future, so stay tuned.
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White Paper: The Agile Transportation System (ATS) – AI-Driven, Routeless, and On-Demand Mobility

  Abstract / Executive Summary The Agile Transportation System (ATS) is a next-generation urban mobility solution that leverages Artificial Intelligence (AI) to revolutionize transportation. Unlike traditional public transit with fixed routes and rigid schedules , ATS operates on an AI-powered routeless model that dynamically adapts to commuter demand. It also integrates an intelligent passenger selection system to optimize seating, prevent congestion, and enhance accessibility. Designed initially for Bonifacio Global City (BGC), Philippines , ATS ensures on-demand scheduling, flexible vehicle deployment, and 24/7 availability . By incorporating AI-powered analytics, predictive algorithms, and real-time optimization , ATS offers a truly agile, scalable, and commuter-centric transportation system. Introduction Urban mobility is facing major challenges, including traffic congestion, inefficient public transport, and long waiting times . Traditional public transit operates on pred...
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Retrieval-Augmented Generation (RAG) Using First-Principles Thinking

Instead of just learning how Retrieval-Augmented Generation (RAG) works, let's break it down using First-Principles Thinking (FPT) —understanding the fundamental problem it solves and how we can optimize it. Step 1: What Problem Does RAG Solve? Traditional AI Limitations (Before RAG) Large Language Models (LLMs) like GPT struggle with: ❌ Knowledge Cutoff → They can’t access new information after training. ❌ Fact Inaccuracy (Hallucination) → They generate plausible but false responses. ❌ Context Limits → They can only process a limited amount of information at a time. The RAG Solution Retrieval-Augmented Generation (RAG) improves LLMs by: ✅ Retrieving relevant information from external sources (e.g., databases, search engines). ✅ Feeding this retrieved data into the LLM before generating an answer. ✅ Reducing hallucinations and improving response accuracy. Core Idea: Instead of making the model remember everything, let it look up relevant knowledge when needed....
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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...
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