Rape is not a mistake triggered by lust.
It's an expression of the psychology of someone who wants something they're not permitted to have and is willing to take it by force at the expense of another person.
We don't need those kinds of people running around… apology or not.
Madame Celeste Amarilla,
Vous êtes une femme méprisable et indigne de sa fonction.
Vous ne représentez pas le Paraguay, ce pays qui a transpiré la passion et l’honneur tout au long de la compétition. Par votre inconscience et votre racisme décomplexé, le monde entier a déjà oublié le parcours et l’effort historique que vos joueurs ont réalisés durant cette coupe du monde pour laisser place à une dame incompétente donnant la pire image possible de son pays.
Je ne laisserai jamais aux gens comme elle, la liberté de laisser propager leur haine et leur racisme à travers le monde.
I just built a full stack financial AI assistant that does more than answer basic questions. It provides secure user accounts with password protection and private sessions. The system remembers key details like income, goals, and risk tolerance to give personalized advice. It also connects to live market APIs to deliver real time stock prices.
It also includes interactive charts that show income and spending clearly inside the chat. This makes financial decisions easier to understand at a glance. The project was built with Python using FastAPI, React, SQLite, and Scikit Learn for NLP. It reflects my focus on building practical and user centered AI solutions.
The record books remember that Tunisia won AFCON 2004 on home soil.
Nobody remembers how they cheated from start to finish, especially in the semis against Nigeria.
If you allow your robbery to go unchallenged, people will forget you were robbed and history will be rewritten.
I built a context-aware AI medical triage chatbot from scratch that goes far beyond basic if/else logic by understanding natural language intent, remembering conversation context, and distinguishing between emergency and routine cases in real time. It uses a hybrid intelligence system combining vector embeddings and fuzzy logic to correctly interpret everyday phrases, applies deep medical logic trees with safety checks to separate low-risk symptoms from critical conditions, supports voice input for accessibility, and includes a dynamic React interface with a doctor-facing analytics dashboard for tracking case severity. Built end to end with Python, FastAPI, sentence transformers, and React, the project functions as a fast, reliable first-line triage assistant focused on logic, speed, and patient safety. Let me know what you think about it is the comment below