cnemri

Write a complete, production-ready, single-file HTML/JavaScript application that renders a highly detailed, photo-realistic, navigable 3D scene of the iconic cliffside village of Sidi Bou Said, Tunisia using Three.js.

CRITICAL INSTRUCTIONS — NO LAZY CODE

• Do NOT use any external asset URLs (no external .gltf, .obj, .jpg, or .png files) as they can break or fail CORS. All textures, heights, and models must be generated dynamically and procedurally within the script (e.g., using HTML Canvas to draw textures, procedural noise algorithms for plaster and stone, or mathematical structures for 3D meshes).
• Do NOT write placeholder comments, truncated code blocks, "// TODO" markers, or "left as an exercise" shorthand. Every single function, shader, loop, and variable must be written out in its entirety.
• The output must be a single, copy-pasteable HTML file that runs perfectly immediately when opened in a browser.

TECHNICAL REQUIREMENTS & FEATURES

1. Libraries: Load Three.js and OrbitControls vi

cnemri

Actuarial Survival Model: Kinship Exposure to Severe Disability

Author: Chouaieb Nemri | Generative AI BlackBelt @ Google & Disability Rights Advocate

Abstract

In systems engineering, architectures are inherently "designed for failure" to ensure resilience and mitigate friction. Conversely, human societal infrastructure, software, and corporate policies are largely designed under the statistical assumption of permanent able-bodiedness.

This document outlines an actuarial survival model built to quantify the exact mathematical probability that a standard individual will intimately experience a severe, permanent disability (either personally or within their immediate family) during their lifetime. By integrating continuous-time demographic overlap (survival censoring) and a Shared Frailty Gaussian Copula (intra-family covariance), the model demonstrates that exposure to severe disability is not a statistical anomaly, but the majority experience of the human lifecycle (~60%).

---

cnemri

(function() {
    const highlightTweets = () => {
        // 1. Select all tweet articles
        const tweets = document.querySelectorAll('article[data-testid="tweet"]');

        tweets.forEach(tweet => {
            // 2. Find the Like button container
            const likeBtn = tweet.querySelector('[data-testid="like"]');
            if (!likeBtn) return;

cnemri

from google import genai
from google.genai import types
import concurrent.futures
from tqdm import tqdm

youtube_urls = [
    "https://www.youtube.com/watch?v=eIUqw3_YcCI",
    "https://www.youtube.com/watch?v=stnSRel03e8",
    "https://www.youtube.com/watch?v=Z8Qip0kgl3A",
    "https://www.youtube.com/watch?v=7nv1snJRCEI",

cnemri

{
   "public_identifier":"nemri",
   "profile_pic_url":"https://s3.us-west-000.backblazeb2.com/proxycurl/person/nemri/profile?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=0004d7f56a0400b0000000001%2F20240119%2Fus-west-000%2Fs3%2Faws4_request&X-Amz-Date=20240119T091043Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&X-Amz-Signature=2142f94eac248df27bcfa00c418b1433509eb8cf7dbfe631e5c555e4b11aae62",
   "first_name":"Chouaieb",
   "last_name":"NEMRI",
   "full_name":"Chouaieb NEMRI",
   "follower_count":10166,
   "occupation":"Data Lab Solutions Architect at Amazon Web Services (AWS)",
   "headline":"Machine Learning, MLOps and Data Analytics @ AWS | Georgia Tech Alumni",
   "summary":"I mentor people with disabilities to land a career in tech: Book your spot with me here 👉 https://calendly.com/nemri/disability\nI am a professional tech mentor, book your session with me here 👉https://mentorcruise.com/mentor/chouaiebnemri/\nI write about Data, Cloud and AI here 👉 https://c-nemri.medium.com/\n\nI am a passionate