The "Live Research" Fallacy: How We Overestimate AI Capabilities
The fascination with generative AI models such as ChatGPT or Gemini often leads to an almost mythical attribution of abilities. We input a complex question and receive a coherent answer that appears to contain current knowledge. From this, many entrepreneurs deduce that the AI is "reading" or "visiting" the web in real-time, much like a human user checking various sources. This assumption, however, is fundamentally flawed. A vast portion of these systems' knowledge comes from their enormous but static training datasets, which were frozen at a specific point in the past. To simulate currency, modern systems use a bridge technology: they access search engine APIs. In effect, they "ask" Google or Bing. What the user perceives as "research" is, in truth, a query of the world already indexed and filtered by the search engine. The AI itself does not "surf" from link to link. It is an interpretation engine, not an explorer. This distinction is not trivial; it is the core of the new strategic challenge.
