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The evolution of artificial intelligence today increasingly resembles the development of urban infrastructure. What was once an innovation, like the water supply, eventually became an invisible yet essential part of daily life. AI is following a similar path – shifting from a standalone tool to an integrated, background service within the digital environment.
A key trend is the shift toward a hybrid model. In water supply, this means combining centralized systems with local solutions, such as rainwater collection and resource reuse. In the context of AI, it involves the integration of public, personal, and corporate intelligence systems. Distributed architectures allow resources to be allocated more efficiently to where they are most needed.
Lenovo is currently focusing on developing this hybrid approach. The model envisions AI that is not confined to the cloud or a single device. Instead, it operates simultaneously across multiple layers – within cloud infrastructure and directly on gadgets. Balancing local computation with cloud services enables a combination of performance, scalability, and privacy. The strategic goal is to make intelligence so seamlessly integrated that its presence is unnoticed until it is genuinely needed.
TABLE OF CONTENTS:
The Concept of Background AI
The term “background artificial intelligence” refers to a system that is not tied to a single application or platform. It operates simultaneously across smartphones, laptops, wearables, and other devices, synchronizing context between them. Local computation ensures responsiveness and data protection, while cloud services provide scale and additional capabilities. At the same time, users retain control over their own data.
At Lenovo, this model is referred to as a personal digital twin – a system that gradually learns an individual’s behavior, habits, and needs. A similar principle applies in business environments: a corporate digital twin operates based on internal company data and policies, acting in alignment with established objectives.
Five Interaction Scenarios
Lenovo identifies five behavioral modes for this type of AI:
Proactive – anticipates needs. The system operates in the background, analyzing tasks, helping prioritize, and reminding users of important events. For example, it might flag an unanswered call and suggest brief talking points.
Reactive – responds immediately. AI works in real time, taking into account the current context – camera images or on-screen information – and provides relevant data on request.
- Interactive – assists in executing intentions. File transfers, reminder creation, or device synchronization occur without requiring the user to engage with technical details.
Retrospective – acts as an analyst. It can summarize missed messages, prepare a concise report on project updates, or recap key points from a meeting.
- Immersive – supports focus. The system minimizes distractions and optimizes the digital environment for work or relaxation.
In this model, AI accompanies the user throughout the day, seamlessly integrating across all devices and usage scenarios.
From Concept to Implementation: The Superagent
Lenovo believes that the foundation for ubiquitous AI is already in place. Solutions such as Moto AI, Lenovo AI Now, and Smart Connect illustrate an approach in which intelligence is directly integrated into devices and operates in a hybrid mode, combining cloud and edge computing.
The next stage is the integration of these components into a unified intelligence layer across all of a user’s devices. This can be seen as a “cognitive operating system” that coordinates the activity of specialized AI agents. Lenovo views this transition – from standalone tools to a continuous, nearly invisible presence – as the true potential of future artificial intelligence.
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