AI晶片

Infertility is a serious globe issue, especially in the developed countries, over 20infertile male has sperm problems, that include instance immotile, abnormal morphologylow sperm quantity. Therefore, how to isolate high quality sperm for clinical use is extremely required. Up to date, activity sperm sorting is usually using Swiming-upDensity gradient centrifugation approaches. Unfortunately, both methods are detrimental to the sperm viabilityelicits production of reactive oxygen species. Separation sperm by microfluidics has been put emphasis onstudied however, it faced some challenge such as low throughputan unacceptable recover rate.

With the rapid advancement of artificial intelligence and IoT, many solutions have been successfully implemented. However, for very large biomedical image computations, such as MRI’s, the deep learning/ training will be a lot more time consuming. At the moment, GPU’s are considered the baby of the AI world, Google has also developed a TPU to expedite AI procedures. Both GPU and TPU make the process swift. Prof. Darsen Lu’s Research Team has built an open simulation platform called (simNemo) to enable design exploration by academic and industry users in Taiwan on both the AI platform and AI application fronts.

With the rapid advancement of artificial intelligenceIoT, many solutions have been successfully implemented. However, for very large biomedical image computations, such as MRI’s, the deep learning/ training will be a lot more time consuming.

Infertility is a serious globe issue, especially in the developed countries, over 20infertile male has sperm problems, that include instance immotile, abnormal morphologylow sperm quantity. Therefore, how to isolate high quality sperm for clinical use is extremely required. Up to date, activity sperm sorting is usually using Swiming-upDensity gradient centrifugation approaches. Unfortunately, both methods are detrimental to the sperm viabilityelicits production of reactive oxygen species. Separation sperm by microfluidics has been put emphasis onstudied however, it faced some challenge such as low throughputan unacceptable recover rate.

Due to the recent outbreak of COVID-19 and ongoing mutants, we developed a coronavirus variant protein microarray that includes all the current spike mutations and the wild-type viral antigens and applied in detecting immune responses and drug specificities. We filed the patients and published our findings in the Analytical Chemistry. Besides massive production of the coronavirus protein microarray, we also collaborated with a scanner company, developed artificial intelligence software, and collaborated with suppliers. We are welcome any sort of collaboration.

With the rapid advancement of artificial intelligenceIoT, many solutions have been successfully implemented. However, for very large biomedical image computations, such as MRI’s, the deep learning/ training will be a lot more time consuming.

With the rapid advancement of artificial intelligence and IoT, many solutions have been successfully implemented. However, for very large biomedical image computations, such as MRI’s, the deep learning/ training will be a lot more time consuming. At the moment, GPU’s are considered the baby of the AI world, Google has also developed a TPU to expedite AI procedures. Both GPU and TPU make the process swift. Prof. Darsen Lu’s Research Team has built an open simulation platform called (simNemo) to enable design exploration by academic and industry users in Taiwan on both the AI platform and AI application fronts.

With the development of science and technology, more and more kinds of electronic products come out, and the demand for charging is becoming more and more important. The compound annual growth rate of wireless charging exceeds 40％. For the demand for wireless charging equipment, the nitride developed by our team Gallium power transistors can achieve high-efficiency wireless charging through power levels ranging from 25 watts to 2500 watts and meet fast charging. It is one of the best applications for exhibiting the characteristics of gallium nitride transistors.

Our PEDD has been used to detect the HNE level in both tear and wound fluids of 9 patients, and the limitations of detection were about 0.76 μg/mL and 0.63 μg/mL respectively. Our device requires only 15 minutes, 3 μL of clinical sample for each test, and offers superior sensitivity compared to other current HNE detection methods. The HNE concentrations in the patient samples have shown that the elevated HNE levels might suggest an abnormal healing of either acute or chronic wounds, consistent with previous studies that showed excess protease levels in all non-healing wounds.

e propose an AI dynamics drug repurposing platform applicate on COVID-19. This platform analyzed a large number of structures of SARS-CoV, MERS, and cross-species coronavirus 3CL protease-ligand complexes to construct uncovering six flexible active site conformations and pharmacophore clusters for SARS-CoV-2 3CL protease screening all FDA drugs and found four inhibitors within three months. Among them, JM206 had even demonstrated ten times better efficacy than Remdesivir in-vitro assay and also show the effect on the in-vivo hamster model to alleviate the symptoms caused by COVID-19.

Taiwan was formerly the Shrimp Capital of the World. With the changing of the timesincreasingly updated technology, AI smart farming is the new milestone for Taiwan’s agriculturefisheries.

Assisted by in-house AI deep compression toolchain (ezLabel, ezModel, ezQUANT, ezHybrid-M), the proposed technology supports automatic AI model design and optimization with the integrated performance of 120x model size reduction and 70x power reduction in 2D CNN model, and develops a world-first 1/2/4/8-bit CNN model realized by the developed high efficiency Hybrid fixed point CNN NPU (Hybrid-NPU), which has been verified in Xilinx ZCU102 FPGA and achieves the performance up to 2.5 TOPS(8-b)/ 20TOPS(1-b)＠28nm technology running at 550MHz and 4TOPS/W energy efficiency.

Quote:br / “It is worth giving up some things because of dream pursuing” Professor SHOU-DE, LIN  at the department of computer scienceInformation Engineering in National Taiwan University, Chief Machine Learning Scientist in Appier, said “An escape from comfort zone to seek new challenges makes my life become more colorful.”br /  br / Content:br /  br / Given qualified for being as the freshman of National Taiwan University College of Medicine, Professor Lin chose the department of electrical engineering in NTU as the first priority in Joint College Entrance Examination (JCEE). Though the undergraduate education  did not cultivate him the passion on the field of electrical engineering, Professor Lin said, however, he was still recommended for further study at the graduate institute of electronics engineering in NTU due to his talentsoutstanding academic performance.

AI農情調查之UAV群眾協作平台後台支援自動鑲嵌建模，更具備四項突破技術：(1)巨量影像格化技術；(2)平行運算技術；(3)任務規格標準化；(4)UAV任務媒合。致力於打造空中UBER協作服務，未來能應用於農作物分佈調查、大範圍災情調查、農業保險、農地違法使用調查與休耕補助調查等面向。

Electroplated nanotwinned Cu possesses excellent electrical & mechanical properties. It can be applied in three major joints:1. Low thermal budget/ low resistance Cu bonding for high performance computing chip.We are able to achieve low temperature bondinginstant bonding. Low temperature bonding is performed at 150°C for 1 h to achieve low contact resistance copper bonding. Instant bonding is performed at 300°C for 5 seconds under a pressure of 90MPa achieve low contact resistance.2. High strength/ High ductility copper lines in 3D-IC packaging We are able to fabricate high strength foils with tensile strength of 800MPa. After annealing at 150°C for 3 hours, the foil retains a tensile strength of 750MPa. 3. Cu foils for lithium ion battery

As we age, our memory also gradually begin deteriorating. At what point should one seek out a consultation with a doctor? Statistics estimate that worldwide, every 3 seconds someone experiences dementia.

This integrated research project follows the Taiwan's 2030 Science & Technology Vision and takes LOHAS community and inclusive technology as the major research direction. We aim to develop trustable AI technologies, and introduce them to future smart services. That will realize the development of human-centric smart technology, and strengthen the governance and application of emerging technologies. The integrated project consists of 7 sub-projects led by PIs from National Taiwan University, National Tsing-Hua Universiy and Academia Sinica and composed of top AI technological teams. These sub-projects are divided into 3 clusters, including machine learning (sub-projects 1 and 2), computer vision (sub-projects 3 and 4), and human-centric computing (sub-projects 5, 6 and 7). We will deal with the issues of bias, fairness, transparency, explainability, traceability, and so on, from the aspects of data collection, technology, and application landing. Each sub-project will implement specific smart services to reflect the benefits and practical applications of the developed technologies. The NTU Joint Research Center for AI Technology and All Vista Healthcare, an AI Innovation Research Center supported by MOST, is responsible for management, planning, and execution of the integrated research project. We will propose a plan that can be generalized and applied to the intelligent service industry.

As artificial intelligence rapidly develops and enhances human’s quality of life, another cause for concern is the dangers and possible threats to humanity. “Moral judgement” will be a big issue that needs to be addressed as these intelligent machines become more and more prevalent in society. As with any new technologies, the topic of applied ethics often arises. So, the extension of that is AI ethics issues.

The IHC staining intensity grading algorithm combines a series of complementary processes of deep learning and image processing in order to overcome the difficulties in cell boundary segmentation and grade definition, and provides a cell-based IHC staining intensity grading and quantification capability. The proposed method serves as a useful assistive tool for physicians in performing accurate staining quantification in tissue microscopic images.

This project goes on developing embedded AI deep learning technology focus on the ADAS/Self-driving applications. We develop the technology from five aspects, including automatic object labeling toollabeled datasets, deep learning softwarehardware technology development, various ADAS/Self-driving object detectionbehavior prediction technology, self-driving control technology as well as virtual simulation environment establishment for ADAS/Self-driving applications.

As artificial intelligence rapidly developsenhances human’s quality of life, another cause for concern is the dangerspossible threats to humanity. “Moral judgement” will be a big issue that needs to be addressed as these intelligent machines become moremore prevalent in society. As with any new technologies, the topic of applied ethics often arises. So, the extension of that is AI ethics issues.

If you experience symptoms such as difficulty hearing, frequent headaches, loss of balance, deteriorating hearing, etc., it might be wise to check if you have acoustic neuroma. Because symptoms are similar to other common ear issues, it isn’t always detected. Vestibular schwannoma is a benign tumor with a slow growth rate, however as it grows and affects surrounding nerves it may have side effects that could possibly be fatal if not addressed.

This project goes on developing embedded AI deep learning technology focus on the ADAS/Self-driving applications. We develop the technology from five aspects, including automatic object labeling toollabeled datasets, deep learning softwarehardware technology development, various ADAS/Self-driving object detectionbehavior prediction technology, self-driving control technology as well as virtual simulation environment establishment for ADAS/Self-driving applications.

The dialogue system is the main subsystem of the visually impaired navigation system, which provides destinations for the navigation system through multiple dialogues. We use the knowledge graph as the basis for reasoning. In terms of close-range navigation, deep learning technology is used to develop RGB camera detection depth algorithm, indoor semantic cutting algorithm, integrated detection depth estimation and indoor semantic cutting in indoor obstacle avoidance, etc. The whole system uses the CellS software design framework to integrate distributed AIoT systems.

div style="text-align: justify"According to the statistics of World Health Organization (WHO) in 2018, Chronic Obstruction Pulmonary Disease (COPD) has killed 3 million peoplebecome the 3rd place among the top 10 leading causes of death in the world, which means one person dies for this fatal disease every 10 seconds. In Taiwan,chronic lower respiratory disease is at the 7th place among the top 10 leading cause of death. There are over 5000 people died for obstructive pulmonary every year.

The liver is a silent organ, yet it affects the health of many. In Taiwan, there are over 10,000 deaths annually due to chronic liver
disease, cirrhosis and liver cancer. Liver cancer is currently the second leading cancer in Taiwan.

AI is applied to assist data cleaning and cross-database authority control of names and institutions in the bibliographic materials such as patents, papers and research projects.

A famous commercial ad stated: “If the liver is unwell, life becomes black and white.” Those who have seen this are reminded to take good care of the liver, however liver disease is still quite prevalent in Taiwan. 13,000 deaths each year are due to some form of liver disease. Liver cancer is the 2nd leading cause of death in Taiwan and chronic liver disease & cirrhosis are the 9th leading cause of death.

Did you know that Tuberculosis is still a highly infectious disease affecting Taiwan and is one of the top 10 causes of death worldwide? TB is an airborne illness that can be contracted by breathing in germs. Early TB detection greatly reduces the risk of spreading the illness.

To develop an AI model that doctors trustthat generalizes to as many hospitals as possible, NVIDIAMass General Brigham embarked on an initiative called strongEXAM/strong (strongE/strongMR CstrongX/strongR strongA/strongI strongM/strongodel) the largest, most diverse federated learning initiative with 20 hospitalsresearch institutions from around the world. In just two weeks, the global collaboration achieved a model with .94 area under the curve (with an AUC goal of 1.0), resulting in excellent prediction for the level of oxygen required by incoming patients.