Lenovo CTO: Betting on Multimodal AI Collaboration to Build a Model Factory and Accelerate Intelligent Agent Deployment

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Published inAI News · 4 min read · Mar 31, 2025

At Lenovo's 2025/26 fiscal year kickoff meeting, Chief Technology Officer Tolga Kurtoglu emphasized that current AI applications are still in a rapid iteration stage of technological demonstration, far from truly unleashing the mature capabilities to create value for users. He pointed out that the key to future AI development lies in transforming technology into user-centric solutions, building Lenovo's unique differentiated advantages.

Kurtoglu painted a future user-centric AI landscape: it will no longer be limited to a single model, chip, device, or form, but will be driven by the collaboration of multiple models and agents from the edge, cloud, and on-device, seamlessly providing services to users. The fusion of powerful capabilities and a simple user experience is the true value of AI.

Lenovo

To achieve this vision, Kurtoglu detailed Lenovo's technological roadmap:

First, Lenovo will establish a model factory. Through a professional global team of engineers, the deployment time of new models will be shortened from months to weeks, allowing for rapid model optimization and delivery to R&D teams, ensuring Lenovo's leading position in the application of the latest models.

Second, Lenovo will adopt advanced model orchestration technology to automate model selection. This orchestrator can intelligently decompose user queries or tasks and call the most suitable model (whether located on the device, server, or cloud). For example, "Lenovo Xiaotian" will be able to automatically judge the privacy requirements of a query and assign the task to the most appropriate model network, improving information retrieval efficiency while simplifying the user experience.

Finally, the above capabilities will accelerate the deployment of AI agents through Lenovo's intelligent agent development framework. This framework provides general and specialized building blocks, enabling R&D teams to quickly connect, adjust, and build agents that meet various customer needs without starting from scratch, including core capabilities such as security, self-learning, multi-agent collaboration, and task management.

Kurtoglu concluded that with the rapid model deployment capabilities brought by the model factory, leading model orchestration technology, and the intelligent agent development framework, Lenovo will have the powerful ability to deliver super AI agents to users.

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