Companies want to innovate with AI, but face technical, budgetary and talent barriers. Furthermore, the demand for GPUs far exceeds the deployment capacity of many organizations, which slows down these strategic projects. In response to this problem, Lenovo has introduced GPU Advanced Servicesan initiative that promises to increase workload performance by up to 30% and accelerate the real adoption of artificial intelligence in companies.
The proposal is not limited to the supply of hardware, it is a services-based approach that helps companies plan, deploy and manage GPU infrastructures in a more agile and efficient way. According to Lenovo, the goal is to prevent underutilization of resources and enable organizations to take their AI projects from the lab to production more quickly and reliably.
Complex infrastructure, simpler deployments
“While companies are moving quickly to get AI systems up and running, many still face challenges related to the complexity of deploying GPU infrastructure,” said Steven Dickens, CEO and principal analyst at HyperFRAME Research.
Lenovo has introduced GPU Advanced Servicesan initiative that promises to increase workload performance by up to 30% and accelerate the real adoption of AI in companies
Lenovo seeks to respond to this challenge through a model that combines expert support, strategic planning and managed services. “With our certified experts and extensive platform integration, we help companies deploy GPU infrastructure faster and run workloads more reliably, reducing risk and unlocking the full potential of their AI investments,” said Linda Yao, vice president and general manager of AI and Hybrid Cloud Solutions at Lenovo.
A modular approach for each stage of the AI journey
The program GPU Advanced Services It is articulated in three blocks that organizations can contract independently or jointly, depending on their degree of technological maturity:
1st phase: GPU Plan & Design Services It is designed for companies that are taking their first steps in artificial intelligence
It includes workload assessment, solution sizing, and the architectural planning necessary to establish the foundation for a robust AI environment.
2nd phase: GPU Implementation Services provides architecture documentation, technology configuration, and guidance during deployment, ensuring systems are launched correctly and frictionlessly.
3rd phase: GPU Managed Services is aimed at organizations that already operate productive AI environments.
This module offers continuous optimization, updates, technical support and compliance management in both on-premises and hybrid GPU environments.
To speed up the first steps, Lenovo also offers AI Fast Starta methodology that allows use cases to be quickly identified and validated before scaling to production, reducing trial and error times.
Sectors where the impact is already noticeable
The deployment of optimized GPUs is not an exclusive luxury of technology giants. Lenovo is targeting key sectors where AI is transforming processes with tangible results. In the area of healthFor example, AI-assisted diagnoses allow for real-time conclusions and improved patient care. In automotivemanaged services help optimize AI models at the edge, driving the development of autonomous and connected vehicles.
The industry of media and entertainment also benefits from GPU fine-tuning, which accelerates real-time rendering and content production workflows, while suppliers of cloud services They manage to reduce deployment times by up to 40% thanks to Lenovo’s experience, as demonstrated by the results of Cirrascale Cloud Services.
