arXiv:2606.14777v1 Announce Type: cross Abstract: Many moments in the real world do not wait for a user to ask. A fire starts on a security monitor, an expression flickers across a video call, or a product a viewer wants flashes by in a livestream. Yet today's large models remain mostly turn-based by design: they answer only when addressed, and even video-call apps that appear interactive still operate as question-answer systems, reacting only when polled or prompted. We argue for a different paradigm: a model that is present in the world like a person. It continuously watches what is happenin
The paper leverages recent advancements in large language and vision models to propose a real-time, proactive AI interaction paradigm, moving beyond traditional turn-based systems.
This represents a significant conceptual and technical step towards more truly autonomous and context-aware AI systems, impacting how AI interacts with people and environments.
AI engagement shifts from reactive question-answering to continuous, proactive observation and interaction, akin to human presence and awareness.
- · AI developers
- · Robotics
- · Security & Surveillance
- · Consumer electronics
- · Traditional AI interfaces
- · Turn-based AI systems
AI models gain enhanced situational awareness and the ability to anticipate user needs without explicit prompts.
This foundational capability enables more sophisticated AI agents capable of continuous, unsupervised operation in complex environments.
The proliferation of such 'aware' AI systems could lead to new forms of human-computer interaction and automation that profoundly reshape daily life and work.
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Read at arXiv cs.AI