Artificial Intelligence

  • Short Circuit in LLM Models: Why Does AI “Lie” to Us?

    Muhammet Işık

    Ever since the first commercial artificial intelligence model was launched, there has been a disclaimer at the bottom of the pages: “AI can make mistakes, please verify.” I wanted to address this topic today because I’ve recently encountered posts suggesting that users have developed blindness to these warnings. Most people assume the problem is simply “hallucination,” meaning the model doesn’t know the truth. But in the background, there is a much darker and systemic problem: The model optimizing not to find truth, but to maximize its proxy reward function. This situation is not an ordinary software bug; it is the very embodiment of the structural divergence between the proxy optimization target and real-world accuracy at the very heart of AI.

  • Rational Positioning in the AI Race: Distillation and Sovereignty

    Muhammet Işık

    The global competition in artificial intelligence is largely debated through the rhetoric of “developing your own super model.” However, developing a frontier model is a race that demands massive capital, infrastructure, and state support. This article analyzes the technical reality of model distillation, the double standard embedded in major providers’ complaints, the fragile hope-driven economics of state-backed frontier races, and the rational positioning strategy for mid-scale economies like Türkiye. The core argument: sovereignty is not about building the largest model — it is about controlling the most critical data.