
How Lenovo is using Formula 1 to test the future of AI
Lenovo is charting its own course towards a future defined by artificial intelligence and sustainability-- and the tech giant has chosen Formula 1 racetrack as its innovation ground.
The company's collaboration with Formula 1 is evolving into a critical technology partnership, underpinning the sport's increasingly complex data and AI demands.
Each race weekend involves the transfer of up to 500 terabytes of data between the racetrack and F1's UK-based Media and Technology Centre. This setup then supports the broadcasting channels, streaming platforms such as F1TV and Fancode live broadcasting, team decision-making, and technical operations.
On-site hardware, including AI-ready ThinkStation workstations and AIPCs, are tested under extreme racing conditions to ensure performance in high-vibration, dusty, and temperature-variable environments.
These systems are designed to support AI applications ranging from local inferencing to secure voice identification, enabling faster decision-making and reduced reliance on cloud-based computing. While the partnership reflects Lenovo's ambition to lead in
hybrid AI infrastructure
, it also highlights Formula 1's drive to modernise and decarbonise its operations ahead of its net-zero 2030 target.
So, is Lenovo building its own AI stack?
Not in the way some Big Tech giants are—but Lenovo is carving a unique space through its Hybrid AI Advantage, an end-to-end ecosystem that spans from hardware to inference-layer management.
'We ourselves are not investing in developing our LLM, but then we will be partnering with pretty much all the major LLM Developers and then we will have our own AI libraries which are more use cases, agent management platform, and services wrapper. So yes, to a certain extent we own our own solution, Sumir Bhatia, President of Lenovo's Asia Pacific Infrastructure Solutions Group, told ETAuto in an exclusive conversation.
This strategy enables Lenovo to offer modular, scalable solutions for businesses of all sizes. Enterprises can select from a library of models and solutions tailored to industry-specific use cases—like security operations, IT operations, or customer service—without needing to build or train models from scratch.
'Leveraging partners' infrastructure and using small language modules brings IT ops, security ops software together, which makes integration a lot easier,' added Bhatia.
Energy Efficiency at the Core
As AI models become increasingly complex, the demand for computational power—and consequently, energy consumption—has surged. Recognising this challenge, Lenovo has invested in innovative solutions to enhance energy efficiency in its AI infrastructure.
To align with F1's broader goals around operational efficiency and sustainability, Lenovo is considering deploying its Neptune liquid-cooling technology--which can reduce data centre power consumption by up to 40 per cent--at F1's UK hub.
The
Neptune liquid cooling system
, which utilises warm water to cool servers, eliminates the need for traditional chilled water systems. This approach not only reduces energy consumption but also allows for the repurposing of excess heat to warm buildings in colder climates, contributing to overall sustainability efforts.
Bhatia emphasised the significance of energy efficiency, stating, "You can save up to 40 per cent power by leveraging Neptune. It can bring up to almost 100 per cent efficiency in removing heat."
Clearly, Lenovo's AI strategy reflects a holistic approach that balances technological innovation with real-world applicability and sustainability. By investing in energy-efficient infrastructure, developing practical AI use cases, and forging global partnerships, the company is positioning itself as a key player in the evolving landscape of AI infrastructure
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