Keysight and SAMEER Partner for 6G and Healthcare Innovation

Keysight Technologies and the Society for Applied Microwave Electronics Engineering & Research (SAMEER), headquartered in Mumbai, have signed a Memorandum of Understanding (MoU) to advance 6G and healthcare innovation in India. 

The collaboration involves creating a healthcare center of excellence and a research lab for 6G communication. This partnership is part of the ‘Make in India’ initiative, aiming to boost local growth and development. 

P. Hanumantha Rao, director general at SAMEER (an autonomous R&D institute under MeitY), noted that the collaboration will enhance their ongoing 6G research efforts following the successful demonstration of their end-to-end 5G stack with IIT Madras.

The partnership will enable SAMEER to develop fully functional labs supporting 6G research across Indian institutions. Keysight will provide the necessary infrastructure and technology. 

Sudhir Tangri, VP of Asia Pacific sales and country GM of India at Keysight, stated, “Establishing a center of excellence and building 6G research areas is a critical step towards driving innovation in India.” 

The collaboration also includes establishing a healthcare center that advances magnetic resonance imaging (MRI) technologies. It aims to address the need for strong expertise and an ecosystem in India for 6G and medical electronics. 

SAMEER has made significant contributions to healthcare through indigenous developments such as the Linear Accelerator (LINAC) for cancer therapy and an affordable 1.5T MRI. 

Through this collaboration, Keysight will leverage these products to further democratise access across India. The collaboration is set to enhance innovation in both strategic and civilian applications, aligning with India’s vision for technological advancement.

Keysight recently introduced its AI Data Center Builder, a software suite designed to validate and optimise AI infrastructure by emulating real-world workloads. According to the company, this tool evaluated how new algorithms, components, and protocols impact AI training performance.

This enabled customers to access a library of LLM workloads, such as GPT and Llama, along with popular model partitioning schemas.