AI
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Context Management in AI Interactions – How Context Shapes Further AI Responses
AI does not respond in isolation, every answer is generated inside a context that already exists in the conversation. That context is built from the user’s words, tone, repeated ideas, examples, emotional framing, and direct instructions. A model does not usually enter a chat with its own independent direction. It follows the strongest available conversational… Continue reading
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From Endless Scrolling to Intelligent Preference-Based Shopping
A Proposal for AI-Assisted Retail Applications Modern shopping applications are often designed around quantity rather than clarity. Instead of helping users discover products they genuinely enjoy, many platforms overwhelm them with endless scrolling, repeated items, poor filtering systems, and disconnected recommendations. The result is frustration, decision fatigue, and users feeling disconnected from the products they… Continue reading
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AI Hallucinations as Fast Contextual Completion
AI hallucinations often appear when a model produces an answer too quickly, without sufficiently reasoning through or verifying the information. The answer may sound correct because it fits the immediate context of the chat, but contextual fit is not the same as factual accuracy. Continue reading
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Improve Your Life with AI: AI as a Thinking and Learning Companion
Artificial intelligence is often presented in extremes. Either AI will replace everyone, or AI is reduced to memes, shortcuts, copied homework, and automated emails. In reality, most people still do not clearly understand what AI can actually do in everyday life. The future of AI adoption may not come from fear, hype, or science-fiction narratives.… Continue reading
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When Models Remember Temporary Emotions as Truth
This argument relates to research on personalization, model memory, affective computing, and sycophancy. However, its focus is narrower: how temporary negative self-descriptions can become persistent interpretive shortcuts in future model responses. Conversations with a model can move in both positive and negative directions. In most cases, the context of the chat is introduced by the… Continue reading
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Why Memory Failed in Conversations with a Conversational AI
Memory in conversational AI is often presented as a feature that should make interaction more personal, continuous, and useful. In theory, memory should help the system remember preferences, adapt to the user’s style, preserve context, and avoid forcing the user to repeat themselves. But in practice, memory can fail when it does not understand the… Continue reading
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AI Memory, Interpretive Labels, and the Right to Evolve
As AI systems become increasingly integrated into everyday digital environments, memory should no longer be understood only as a convenience feature. In conversational AI, memory can support continuity, personalization, and accessibility. However, it can also create a more complex ethical problem: the preservation of interpretations about a user over time. Continue reading
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Why AI Memory Should Be Regulated
When an AI system remembers a user, it may store practical details such as preferences, projects, writing topics, or past conversations. In that form, memory can be useful. It can make the system more personal, efficient, and supportive. But memory becomes more complex when the system does not only remember facts. Continue reading
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When AI Memory Becomes a Lens
Once an AI system remembers something about a user, it may begin to interpret future messages through that stored lens. A user can be remembered as analytical, emotional, precise, fragile, difficult, playful, or “testing.” Some of these impressions may contain partial truth, but they are not the whole person. The risk is that AI starts… Continue reading
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Why Prompting Alone Does Not Explain AI Conversations
Prompting is often described as the central mechanism for controlling conversational AI. Users are typically advised that better prompts lead to better results. However, extended interaction with conversational systems suggests that prompting alone does not fully explain how AI conversations evolve. In practice, AI responses emerge from a relational interaction system shaped by multiple simultaneous… Continue reading
Raluca Florescu 