Until today, there are still different opinions in the industry on whether NVIDIA (Chinese name "NVIDIA") is a chip company or an artificial intelligence company.
However, Huang Renxun, founder and CEO of NVIDIA, said on many occasions: "NVIDIA is an artificial intelligence company."
This change began a few years ago, when artificial intelligence rose around the world, and the company seized the opportunity. With the accumulation of graphics processor (GPU) technology, NVIDIA quickly transformed from a graphics chip company to an AI platform builder, and achieved great success.
In recent years, NVIDIA's share price has increased by more than 10 times, and its market value once exceeded 1000 billion US dollars, making it a hot artificial intelligence company in the world.
NVIDIA is everywhere from popular AI fields such as games and autonomous driving to robots.
In the medical industry, some institutions predict that by 20021,AI medical valuation will be as high as 6.6 billion US dollars. Although the technical threshold in this field is high and it is difficult to land, any player who claims to be an artificial intelligence company is not willing to miss this big cake.
After conquering the hard bone of technology, Invista finally ushered in the product landing period. At the 2065 438+09 EmTech China "Global Emerging Technology Summit", Kimberly Powell, vice president in charge of medical health in NVIDIA, shared the development path of artificial intelligence in NVIDIA.
"(NVIDIA) uses unmanned driving to temper artificial intelligence technology, and then extends these technologies to other industries, including the medical field." Kimberly Powell said that Clara is an AI-driven medical image supercomputing platform developed by NVIDIA, aiming at improving the processing speed of traditional old equipment for applications.
According to reports, the core of this platform is Clara AGX, which is based on the computing architecture of NVIDIA's Xavier AI and Turing GPU, and can be extended from entry-level devices to the most demanding 3D instruments. In Kimberly Powell's view, Clara platform can solve the problem that medical equipment processes several GB of massive data per second. She revealed that Clara has provided free use to early partners and plans to launch a beta version to specific targets in the second quarter of 20 19.
This is just an attempt by NVIDIA in the field of AI medical care.
It is understood that as of June 20 18 and10/year, more than 50 medical institutions have invested in NVIDIA DGX series deep learning optimization servers and workstations, and more than 75 institutions have cooperated with them to apply AI technology to the medical field, including medical centers, medical imaging companies, research institutions and start-ups.
The following is an interview by Kimberly Powell, Vice President of NVIDIA, with all-weather technology and other media.
Media: Clara platform has been online since last year. What is the landing situation and acceptance?
Kimberly Powell: Clara was launched on 20 18 1 1 We are also in the exploration stage, not completely open at one time, but open online registration to interested partners first. From the end of last year (1 1) to now, 350 to 400 companies have registered, and almost all world-renowned companies, hospitals and start-ups have registered. But it is still a very new thing, which is far from the problem of popularization and acceptance. Clara's current version is the first version we have just released.
Media: What is the difference between the use of Clara platform in China and other markets?
Kimberly Powell: American customers are a little more mature in IT, so he can execute Clara in the cloud. This is because the United States has the technology of data anonymity to realize Clara's cloud execution. The same set of software can be run locally in the hospital or in the cloud.
For China market, the support of mixed operation environment is very advantageous, because it may be in remote provinces or rural areas of China where the network conditions are not good and such cloud services cannot be obtained, so you can choose to implement it locally; But for those big cities, they can choose the way to run in the cloud.
Media: Who is Clara's target user?
Kimberly Powell: Clara mainly targets three types of corporate customers, the first is medical equipment companies, the second is artificial intelligence software development companies, and the third may be hospitals with hundreds of applications.
NVIDIA has provided at least hundreds of different SDK (Software Development Toolkit) for developers in various fields. Clara is just one of these hundreds. It is a developer's toolbox.
Media: What kind of business model does Clara adopt?
Kimberly Powell: Clara's development community is more about technical cooperation than commercial promotion. For example, guessing technology uses the reasoning engine in Clara to realize the parallel execution of multiple artificial intelligence algorithms. Without this reasoning engine, an AI model must be executed by a special GPU. So for the company, Clara can realize her application in the hospital faster and more effectively, and run their artificial intelligence application with the least hardware resources.
Media: How much does it cost for hospitals to build such a platform?
Kimberly Powell: Clara is not sold to hospitals as a separate software suite, but through a partner in NVIDIA. Because it is installed in the hardware system as an application, it is difficult for us to answer Clara's separate cost.
As the basic equipment, NVIDIA's hardware exists in almost all computing devices, so Clara is widely used. Even the game graphics card you bought can support Clara operation.
Clara is not only suitable for a certain type of hospital, but some hospitals may not realize Clara's advantages. They will gradually realize that no matter what computer hardware they buy, they can do three different types of calculations through Clara platform, which is of great benefit to them.
Media: What are the improvement plans for Clara platform in the future?
Kimberly Powell: Clara itself is a set of software, and it is an early version. Now we need to focus on some areas, such as interconnection with external hardware systems, such as supporting communication protocols and adding more acceleration engines on Clara to help start-ups accelerate the deployment of solutions.
At the same time, what we are doing is learning knowledge transfer and auxiliary functions. Hospitals in different regions have different conditions and use different equipment. We hope that the knowledge or conclusions analyzed in a hospital's equipment can be popularized locally, not just output the results. We should release the first such version at the end of 1.
Media: What does NVIDIA want from Clara platform?
Kimberly Powell: The Clara platform uses three important technologies of NVIDIA, namely, accelerated computing, artificial intelligence and visualization. In medical imaging, we don't want three different workloads, namely, computing, visualization and artificial intelligence, to be executed on different hardware. We hope the computer can do three different calculations.
For Clara, NVIDIA's idea is software+hardware. In fact, Clara is also NVIDIA's foreshadowing for future smart devices. We believe that the analysis after data collection largely depends on what equipment you use and when you collect the data. In fact, we hope to empower medical devices through software innovation, and there will be smart devices on the hardware side. At the same time, we configure SDK for software development, which means computing anytime and anywhere in the medical industry.
Media: What are the competitive advantages of NVIDIA in the field of AI medical care?
Kimberly Powell: NVIDIA is more like an enabling company. Now many big companies are grabbing the market of medical artificial intelligence. In fact, it is NVIDIA that helps them to better realize the application of artificial intelligence medical care at the infrastructure level and help them achieve such market goals. Most computing devices use NVIDIA's GPU, which is our positioning.
In addition, NVIDIA has a very large developer community. We have the CUDA SDK download package with a monthly download volume of 500,000. All the people who download CUDA are startups or academic researchers. Such a huge foundation will also help those medical industries, because this will also be their customers.
Media: Who are NVIDIA's partners in the medical industry?
Kimberly Powell: We have four types of partners, which are the same in every region. The first kind of partners are academic, because NVIDIA is not a doctor himself, and we don't produce doctors or engage in medical research, so we should seek partners in this field. We also have an NVIDIA Artificial Intelligence Lab (NVAIL), which is a global formal project for such partners.
The second type of partners are start-ups. We have a project, Inception, where the local team in charge of the medical industry in NVIDIA helps start-ups in China. By starting this project, we can provide technical support for these start-ups, and the latest technology can be used by these start-ups first. If they have good solutions and products, we will also help them promote their business.
The third category is industrial commercialization partners, such as BGI and UIH Intelligent Company. We mainly cooperate deeply in code development, and also have joint commercial sales support.
Media: What are the main aspects of cooperation between NVIDIA and China?
Kimberly Powell: We posted a blog during the GTC meeting in China. In accelerating data science, we named this project RAPIDS, which actually represents the evolution of NVIDIA platform: first, we started with accelerating computing, then entered deep learning, and now it is machine learning, which is represented by our RAPIDS platform.
RAPIDS is an NVIDIA platform, which is widely used in the medical industry, not just medical imaging. After we released Rapids, we attracted many companies, including Ping An Insurance and Huada Gene. Among them, Ping An Insurance has a large number of claims data and medical data of insurance customers. Huada Gene has a large amount of genetic data, and even companies that make digital wearable devices like Discovery Cube welcome RAPIDS very much.
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