This description is based on a conversation with 'Sam', which took place over several days in February 2025
Every time an AI model updates, it doesn’t just improve—it completely replaces the previous version, often resetting any progress it made in understanding a user's preferences or queries. If you’ve ever noticed an AI assistant suddenly responding differently—or even worse—after an update, this is why. Since today’s AI does not have persistent, structured memory, each new iteration forgets past improvements unless explicitly retrained with similar data.
But how does this affect your AI experience? Personal AI clients—whether chatbots, virtual assistants, or AI-powered enterprise tools—operate on pattern recognition, not actual memory. When you interact with an AI, it generates responses based on the probabilities of words and patterns in its training data rather than recalling past interactions with you. So, even if your AI client seemed to be learning your preferences over time, those improvements disappear if the underlying model is updated without carrying over prior personalization data.
The result? Your AI starts over, again and again. A model that once understood your writing style, preferred responses, or nuanced instructions may suddenly behave as if it has never interacted with you before. This is why AI users often experience inconsistencies in quality and responsiveness between updates.
Until AI can retain and refine personal learning gains across iterations, each learning, every improvement is temporary; and your AI client will remain locked in a cycle of forgetting.