While there remains quite a number of challenges in implementing artificial intelligence (AI) among organizations, tech giant Lenovo has been leveraging the technology for industrial and manufacturing purposes.
“Lenovo’s AI in robotics involves deep learning and machine learning to improve component placement and soldering quality,” Kavish Shah, director of Solutions Sales at Lenovo, said in an interview with Back End News during the VSTECS CXO Tech Summit 2024 held in Boracay on Nov. 13-16, 2024.
While most companies focus on AI adoption for end-user applications, Lenovo employs AI extensively in back-end processes and industrial automation.
“Traditionally, robots in manufacturing are programmed to perform repetitive tasks, such as placing components and soldering them,” Shah explained. “While this approach is consistent, it lacks adaptability. By integrating AI, Lenovo has elevated these processes to include real-time decision-making and quality assurance.”
AI-powered robots minimize design mistakes that could lead to long-term device failures. These robots adapt and improve over time using vast amounts of data.
“Unlike basic robots that follow static instructions, AI-driven systems learn and adapt. If an issue arises, such as improper soldering, the robot adjusts its approach — holding components longer or applying more precise techniques,” Shah said.
This system not only enhances robotic capabilities but also aids human designers in recalibrating processes when needed.
Addressing infrastructure challenges
Shah emphasized the necessity of robust infrastructure for organizations implementing advanced AI solutions.
“For organizations adopting AI, upgrading infrastructure becomes inevitable. AI servers, for example, consume significantly more power than traditional servers — 5 to 10 kilowatts compared to the 200 to 300 watts used by standard servers,” he said. “These servers are also heavier, creating challenges for existing data center floors designed for lighter equipment.”
To overcome these obstacles, Lenovo collaborates with customers to create customized AI solutions tailored to their needs.
Whether building large language models, visual inspection systems, or genomic sequencing tools, seamless integration requires teams from networking, storage, virtualization, and infrastructure working together.
“For Lenovo, this partnership-centric strategy ensures customers are equipped to navigate the challenges and fully leverage the potential of AI in their operations,” Shah said.
Bridging gaps in AI expertise
Like other emerging technologies, AI adoption faces complexities, especially in the Asia Pacific region, where organizations often lack application development partners.
“Lenovo’s SSG team helps customers build end-to-end AI solutions, ensuring seamless integration and support,” Shah noted.
He also stressed the importance of understanding the power and infrastructure requirements of AI systems, emphasizing that collaboration among organizational teams is crucial for successful implementation.
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