Shafik Quoraishee

Local Agentic Theory For Mobile Games — Shafik Quoraishee & Joanne Song, The New York Times

Jul 23, 2026 · 18:04

Shafik Quoraishee and Joanne Song of The New York Times argue that on-device AI agents can transform mobile game accessibility by tuning difficulty and assistance in real time as a single continuous dial rather than separate toggles. They demonstrate a Space Invaders agent that perceives, predicts, and dodges entirely on the phone within a 16 ms frame, and a mini crossword solver using constraint backtracking. The pair explains the on-device budget—space for weights, time within refresh cycles, and energy drain—and shows how gaze estimation and tap analysis let the agent resize controls or break keyboard traps dynamically. They ground their approach in WCAG accessibility standards and propose a future where billions of local brains, each personalized to a user, replace centralized cloud AI.

New York Times' Connections: A Case Study on NLP in Word Games — Shafik Quoraishee, NYT Games

Jul 5, 2025 · 18:31

Shafik Quoraishee, a game developer at NYT Games, presents his independent research into applying AI to solve the New York Times Connections word game. He explains that Connections, launched in June 2023 and second only to Wordle with hundreds of millions of plays, challenges AI's abstract reasoning through intentional decoys and overlapping categories. Quoraishee models the game as a graph coloring problem and uses semantic similarity, relational alignment scores across multiple dimensions (orthography, morphology, encyclopedic, etc.), and graph neural networks combined with reinforcement learning to build a solver. His preliminary results show increased solvability for hard puzzles, contrasting with LLMs that may simply recall internet solutions. The work aims to provide a transparent, explainable AI approach for puzzle-solving and potential game development applications.