What shopping centers in Xi'an are worth taking children to
1. Candidates of the national civil service examination first determine their positions, and then take the examination after they pass the examination and pay successfully
2. The local civil service examination usually requires candidates to choose the position first, and then take the examination after the examination is approved and the payment is successful
3. In the process of civil service registration, candidates can pay attention to the national and provincial examination announcements in the next calendar year. Notice for the examination process and time has a detailed introction.
at present, there are still many deep learning technologies to be explored, which are far from the saturation period. The so-called bottleneck used to be a hardware bottleneck. With nvdia and some hardware manufacturers constantly upgrading their computing tools, the hardware bottleneck has basically disappeared. In fact, the key is to look at other disciplines. We hope that the development of neuroscience can bring some new things to machine learning. Otherwise, we will continue to propose network model adjustment and change the application field of this technology in the paper
"Neumann machine" has made an indelible contribution to the development of computers, and almost "dominates" all the "domains" of computers. However, in the face of artificial intelligence research, it has become an obstacle to the further development of computers and a "bottleneck" restricting the high-speed processing of knowledge and information. The new generation computer must be able to process information in large scale parallel, adopt new memory structure, new programming language and new operation mode. Yuan Yibo and the researchers did not even name the machine they developed as a computer, but as a "knowledge information processing system" (kips).
In 2020, the scale of China's AI market will reach 71 billion yuan
although China's AI instry started relatively late, the enterprises represented by Internet, Alibaba, Tencent and iFLYTEK have begun to invest and layout on a large scale, the enthusiasm for instrial investment and entrepreneurship is high, and the technology research and development of the instry are becoming more and more popular Instry applications and other rapid development. According to the statistics of China information and Communication Research Institute, the scale of China's artificial intelligence market reached 21.69 billion yuan in 2017, with a year-on-year growth of 52.8%. It is predicted that this value will increase to 71 billion yuan in 2020
In the medical instry, medical imaging department is one of the departments with the largest patient flow in the hospital diagnosis and treatment system, and 70% of clinical diagnosis depends on imaging. However, the 4.1% annual growth rate of radiologists is far behind the 30% annual growth rate of imaging data, which provides a driving force for the upgrading of imaging artificial intelligence medical instry. The data shows that the intelligent medical imaging market will grow by more than 40%. More and more hospitals place high hopes on artificial intelligence assisted diagnosis. In the imaging department office of Shanghai First People's Hospital, radiologists will use the Artificial Intelligence Aided Diagnosis System of coronary heart disease to diagnose the degree of arterial stenosis for patients. Unlike in the past, it takes a lot of time to process and write the diagnosis report. The artificial intelligence aided diagnosis system can quickly build a three-dimensional model, judge the degree of stenosis, and output a structured report. The whole process does not exceed 2 minutes. This software is independently developed by domestic enterprise Shukun technology, and has served more than 100 hospitals in Chinathe above group of figures has clearly demonstrated the great development of artificial intelligence in the future. In the digital economy, artificial intelligence, as the engine of the fourth instrial change, has graally penetrated into various instries, bringing changes to human society and economic development
however, artificial intelligence is closely related to data and constrained by data. The landing of AI procts and the differentiation of focus areas have posed more challenges to data collection and annotation, which can answer the question of data gate, which is a difficulty that needs to be solved in the future development of AI
according to cloud measurement data, at present, AI is only in the stage of "weak intelligence", and most of them only focus on a certain field. General AI is still in the stage of research and development, and whether the "strong intelligence" stage of high intelligence will come and how long it will take is still unknown. Artificial intelligence will certainly replace part of repetitive labor in the short term. AI itself actually has a kind of warmth and care, because it replaces high-risk and repetitive labor, which will save a lot of human time and greatly change the interaction mode between people. The bottleneck of AI is data. The amount of data, especially the data quantity and quality in the special field, is not enough, the cost of hardware engineering is relatively high, and there is a lack of response scenarios
according to cloud survey data, artificial intelligence is supported by data, algorithm and computing power. These three elements actually promote and restrict each other. Among them, data is the basis of the development of artificial intelligence. Without data, no strong algorithm can have a good model“ The key to the instrialization of artificial intelligence lies in the data. No matter how well the algorithm model is done, the data will be wrong from the source, and the correct training results will not be obtained. "
now many AI procts are in the landing stage, so the accuracy of the model is very high, and the accuracy of the corresponding data is also very high. Moreover, in order to improve the accuracy of model recognition, the data used by AI company has also changed from single to multi-mode. Take autopilot as an example, from the earliest camera based sensing scheme to the introction of lidar, more other sensing devices may be introced to improve the sensing algorithm. In the future, multi-sensor solutions will be widely used in our AI procts. Its perception mode will not only be based on a single image, sound or text, but also introce more modal data
in order to improve the algorithm, AI enterprises not only need customized data collection to obtain the data of long tail scenario; At the same time, the accuracy of annotation data also needs to be further improved. With the continuous mining of application scenarios, the whole AI instry will have a trend of focusing on more and more subdivided fields in the future
at present, under the trend of focusing, refining and verticalizing in the field, AI has higher requirements for data. Cloud measurement data provides customized, efficient and safe data collection and annotation services for AI enterprises by creating scene laboratories