29-05-2025
Nvidia Is Investing Billions In Healthcare—Especially With Robotics And Hardware
Nvidia, which has gained immense popularity and fame in recent years thanks to its industry leading hardware and GPUs fueling the AI boom, has been investing billions of dollars to make in-roads into the healthcare industry.
The company has always been interested in healthcare. In fact, it reports partnering with nearly 200 organizations and 3,500 startups as a part of its efforts in this space. More definitively, the company has made significant progress across the realms of healthcare delivery and life sciences through use-cases such as advancing protein structure prediction models, optimizing medical imaging LLMs and even progressing with VR technology.
Earlier this month, the company announced a landmark partnership with Foxconn, which is one of the world's largest electronics and hardware manufacturers, to help develop a robust robotics infrastructure. Specifically, Foxconn will leverage Nvidia's technology to advance Nurabot, its collaborative nursing robot which is currently being tested in hospital settings to help alleviate time-consuming and physically tiring manual labor tasks. The companies will partner to build out the ecosystem for Nurabot as a part Foxconn's larger 'smart hospital' system, using Nvidia's experiences in supercomputing, digital twin technology and edge computing.
The massive AI boom has brought with it numerous non-traditional players; in the case of Nvidia, it has been intriguing to see how a company that has traditionally been slotted as purely a hardware chip giant is transitioning to much more than that—partnering to actually help collaborators build out large language models, software solutions and entire ecosystems for the future of healthcare. One example is Philips, which announced last week that it would be working with Nvidia to use its 3D medical imaging models to create an MRI-specific solution.
But this non-traditional approach is likely a positive step forward for the technology industry as a whole, which for decades, has been incredibly siloed into niche sub-sectors. In fact, to parallel this phenomenon, many software giants are also entering new territories which were perhaps previously considered not their forte. For example, Google has made immense investments in the hardware space, specifically to build out its Cloud Tensor Processing Units (TPUs). The company recently announced its latest TPU last month, designed to run significantly complex workloads and AI models at scale.
Another example is Amazon, perhaps one of the best examples of a company that has largely diversified from its original core thesis. Although it started as an online retail giant, the company has made significant inroads into the world of healthcare AI as well. In fact, AWS is a leader in the healthcare and life sciences spaces, helping both customers and partners by powering their workloads and innovation using AWS' proprietary models and platform. Additionally, Amazon is also investing heavily in its own silicon as well; its Trainium chips are being developed to handle heavy machine learning capabilities for the next generation of AI development.
Non-traditional approaches by these companies have created an incredibly competitive, yet innovative, environment. Hyperscalers, along with hundreds of smaller startups in this space, simply do not have time to make slow progress; rather, the heavy competition is forcing rapid innovation, progress and optimization, acting as the tide that is ultimately raising all the ships.
