Today, you will see NVIDIA inside of all of your modern medical devices, including CT, MRI, ultrasound, genomic sequencers, and microscopes.Īrtificial intelligence is becoming the computational workhorse for medical device innovation. All these improvements in the sensor technology put this huge strain on the downstream processing and the human interpretation of all of that data. We are taking these computational approaches that NVIDIA has pioneered from computer graphics to accelerated computing and artificial intelligence and putting them in the hands of the healthcare industry.īack 14 years ago, when I started the healthcare practice for NVIDIA, we were getting all these early indicators saying that this sensor technology that was being invented needed a step function in terms of its computing power. That is what we are doing in the healthcare industry. There is a reason why doctors go to school and practice for decades before they are considered a specialist because it’s very domain-specific. If you think about AI and the notion of intelligence, it means that it’s domain-specific. Now the mission statement of NVIDIA Healthcare is to bring that capability of artificial intelligence to the healthcare industry. It is the biggest technology force of the current time. AI is going beyond graphics in terms of what it’s doing for our company. Now, in 2022, the biggest and fastest-growing application area is artificial intelligence. We always engage at that whole ecosystem level, starting at research, so that we can be at the bleeding edge of what our industry is going to look like in 5 to 10 years. This is the tip of the spear of what you could imagine industries like the pharmaceutical industry taking on. At NVIDIA, we do that through very large-scale bioinformatics, molecular modeling, and simulation. One of the greatest challenges of humanity is to understand disease. One of the most important application areas of supercomputing centers globally is Life Sciences. NVIDIA is powering over 70% of supercomputers, which is pretty incredible. Supercomputing is an area that we are still heavily involved in today. GPU acceleration was paramount for the world’s supercomputers. We wanted to be able to see things in more and more detail, with advanced imaging like in 3D MRI.Ībout fifteen years ago, NVIDIA expanded beyond computer graphics into an accelerated computing company. Radiology is a field where we use devices to see inside the human body. In fact, our first application in healthcare was for computer graphics and radiology.
The first killer application of GPUs was computer graphics. This type of invention creates paradigm shifts in industries. The GPU is what really got me excited about joining the company when I did about 14 years ago. The GPU’s purpose is a very high-level, parallel processing unit to run certain applications at orders of magnitude faster than CPUs or other architectures. NVIDIA’s foundational invention was the graphics processing unit ( GPU). When I started, NVIDIA was primarily known for computer graphics, and over time, NVIDIA has expanded into other areas, including supercomputing and artificial intelligence. Kimberly: My journey at NVIDIA started 14 years ago in the medical devices sector. How has the advent of the NVIDIA GPU transformed the application of AI in healthcare? Kimberly Powell, VP and General Manager of NVIDIA Healthcare Q1.