[China Pharmaceutical Network Technology News] NVIDIA has recently achieved cooperation with the medical system. NVIDIA recently said that the company is committed to the new drug development partner benevolent.ai, through the built-in GPU training system of artificial intelligence computers, in just one month, to find two models of Alzheimer's disease drugs.
Research firm IDC pointed out that by 2020, 80% of big data and analytics deployments will require decentralized micro-analysis, while 40% of company analytics software will include standard-based analysis based on cognitive computing capabilities. All of the above trends require a dramatic breakthrough in existing computing power, and it is likely to be driven by the GPU.
NVIDIA's solution engineering architecture manager, Kang Shengyu, said that NVIDIA began to invest in deep learning five years ago to let the computer learn how to judge things and scenes through the process of deep learning through videos, pictures and texts. However, these judgments depend on good computing performance. Therefore, NVIDIA uses GPU technology to accelerate the deep learning.
Kang Shengyu said that the hospital has a lot of images, such as X-ray films and various images after scanning. In the past, these images were given to doctors for interpretation. If there is a system that can help doctors make more accurate interpretations, It is possible to find the cause early, so the introduction of deep learning has led developers to start research.
Not only that, but Kang Shengyi also pointed out the case of the British startup Benevolent.ai. In the past, the development of new drugs took a very long time, about 12 to 14 years, and huge funds. Among them, it is very important to find out the model of the new drug. By automating the identification model in large-scale data, scientists are able to set assumptions and find conclusions faster, and automation is faster than any human researcher. With artificial intelligence computers with built-in GPU training systems, scientists are now looking for models of two Alzheimer's drugs in just one month.
In the part of breast cancer testing, genetic testing is needed to determine if it is suitable for treatment, but the cost of this test is quite high. Case Western Reserve University in the United States has developed an automated evaluation mechanism for breast cancer detection using deep learning, and its detection cost is only 1/20 of the existing method. Kang Shengyu further stated that when the artificial wisdom Go program AlphaGo can make chess decisions and execute in a few seconds, we found that there are still many things in life that can help humans achieve better through deep learning training. development of.
For example, the Tesla self-driving system is also an important product of the deep learning architecture. Through the built-in GPU computer, the back-end system is trained to let the car have the ability to judge where obstacles need to be avoided, where the line painting on the road is, and how to go to avoid when there is an emergency. To achieve the function of automatic driving.
(Artificial wisdom quickly find new drug medical system and add momentum. Image source: Baidu picture)
Research firm IDC pointed out that by 2020, 80% of big data and analytics deployments will require decentralized micro-analysis, while 40% of company analytics software will include standard-based analysis based on cognitive computing capabilities. All of the above trends require a dramatic breakthrough in existing computing power, and it is likely to be driven by the GPU.
NVIDIA's solution engineering architecture manager, Kang Shengyu, said that NVIDIA began to invest in deep learning five years ago to let the computer learn how to judge things and scenes through the process of deep learning through videos, pictures and texts. However, these judgments depend on good computing performance. Therefore, NVIDIA uses GPU technology to accelerate the deep learning.
Kang Shengyu said that the hospital has a lot of images, such as X-ray films and various images after scanning. In the past, these images were given to doctors for interpretation. If there is a system that can help doctors make more accurate interpretations, It is possible to find the cause early, so the introduction of deep learning has led developers to start research.
Not only that, but Kang Shengyi also pointed out the case of the British startup Benevolent.ai. In the past, the development of new drugs took a very long time, about 12 to 14 years, and huge funds. Among them, it is very important to find out the model of the new drug. By automating the identification model in large-scale data, scientists are able to set assumptions and find conclusions faster, and automation is faster than any human researcher. With artificial intelligence computers with built-in GPU training systems, scientists are now looking for models of two Alzheimer's drugs in just one month.
In the part of breast cancer testing, genetic testing is needed to determine if it is suitable for treatment, but the cost of this test is quite high. Case Western Reserve University in the United States has developed an automated evaluation mechanism for breast cancer detection using deep learning, and its detection cost is only 1/20 of the existing method. Kang Shengyu further stated that when the artificial wisdom Go program AlphaGo can make chess decisions and execute in a few seconds, we found that there are still many things in life that can help humans achieve better through deep learning training. development of.
For example, the Tesla self-driving system is also an important product of the deep learning architecture. Through the built-in GPU computer, the back-end system is trained to let the car have the ability to judge where obstacles need to be avoided, where the line painting on the road is, and how to go to avoid when there is an emergency. To achieve the function of automatic driving.
Wet Chemical Portable Fire Extinguisher
Wet Chemical Portable Fire Extinguisher,Red Wet-Chemical 9L Portable Fire Extinguisher,9L Wet-Chemical Portable Fire Extinguisher,Red Wet-Chemical 6L Portable Fire Extinguisher
JIANGSU NEW FIRE FIGHTING TECHNOLOGY CO.,LTD , https://www.newayfire.com