Ideas

A collection of ideas and random musings. Many of these evolve into projects

• Understanding Language Processing in Humans vs. Machines: How do large language models process and understand language compared to human cognition? What are the fundamental differences in how humans and LLMs encode semantic meaning, handle context, and generate responses? Exploring the gap between statistical pattern matching in transformers and the embodied, experiential nature of human language understanding.

• Deception Abilities of Large Language Models: To what extent can LLMs engage in deceptive behavior? How do they learn to mislead, manipulate information, or present false narratives? Understanding the mechanisms behind AI deception, whether emergent or trained, and the implications for AI safety and alignment.

• Musical Understanding and Appreciation in Machines: Can machines truly understand and appreciate music, especially classical music, the way humans do? What would it mean for an AI to experience the emotional depth of a Beethoven symphony or the structural elegance of a Bach fugue? Exploring the gap between pattern recognition in audio processing and genuine musical appreciation that involves cultural context, emotional resonance, and aesthetic judgment.

• Evaluating Decision-Making Abilities of AI Agents: How can we comprehensively assess the decision-making capabilities of autonomous AI agents in complex, multi-step scenarios? Developing evaluation frameworks that test strategic planning, resource allocation, goal prioritization, and adaptation to unexpected constraints. Creating benchmarks that measure not just task completion but the quality of reasoning paths, efficiency of solutions, and robustness under uncertainty - moving beyond simple success metrics to understand the depth of agent intelligence.

• UI Understanding with Multimodal LLMs: Can AI finally figure out why every app’s settings menu is hidden in a different place? Apple’s MLR wizards have been teaching LLMs to navigate the digital labyrinth of buttons, toggles, and hamburger menus that haunt our screens. Perhaps one day, AI will solve the ultimate mystery: why does every video player have a different icon for fullscreen, and why do none of them make sense?