For many developers, the development of big data applications has not yet started, artificial intelligence has been flooded, and current big data companies are gradually moving closer to artificial intelligence. Will artificial intelligence become a necessary attribute of the application? How should developers face the essence of technology and enrich their skills through phenomena?
In Wu Minghui's view, the core of artificial intelligence is the need for a large amount of data support, whether it is machine learning training or other algorithm optimization. The recent data of RMB 200 million B-round financing will continue to focus on data mining and storage/cleaning/governance research and development at the basic level. At the business level, resident scientists are required to go deep into the customer to achieve business needs. Intelligence, realizing the value of corporate data.
Artificial intelligence is the core data support <br> <br> today's perspective, machine intelligence training results mainly from statistical machine learning, especially learning the depth perception accuracy of intelligence and natural language processing to enhance the great contributions, but also on (identity The data is extremely eager. In order to solve some migration learning methods that are lacking in data, the premise is that there is a related field that can provide data for initial training.
Wu Minghui, who was born in the artificial intelligence profession, has long believed in the role of the data foundation. He even believes that it is impossible to implement artificial intelligence in a scene without data. So, with the goal of implementing artificial intelligence, he was aiming to generate and process high-quality data when he first started his business. Wu Minghui said that Mingluo data focuses on the mining of data itself. In the early days of the company's establishment, it hopes to apply big data to artificial intelligence, whether it is doing big data, mining data itself, and using mining data to do artificial intelligence. Training samples because the relationship between big data and artificial intelligence is very close.
Wu Minghui's professional direction in postgraduate studies is the special industry biometric identification in artificial intelligence, including fingerprint palmprint recognition and vein recognition. Like the popular face recognition today, it belongs to the field of image processing. Although computer vision and deep learning are hot, the data does not change the meaning of technical strategy. Wu Minghui believes that the lack of data preparation is the main challenge for enterprises to apply artificial intelligence/machine learning. For example, unmanned vehicles also require a large amount of test data to continuously test the algorithm. Throughout the interview, he also stressed that “there is no need to deal with the data first, and the data processing is not good.†He believes that it should take more time to find the right data from the Internet/mobile Internet. Clean and used to implement artificial intelligence.
AI + Big Data <br> <br> of course, have the data, also need good algorithm applied to the data, while forming a feedback system in the business scenario above - if not a very good application form, only the original Data, in the end, may not be able to form a self-improving ability to update, such as AlphaGo's limited 9-segment player's game that is published every year in the world, but also a lot of feedback from the PK countless rounds, and then find the reason for winning or losing. Improve.
At present, the artificial intelligence/machine learning algorithm is applied in a relatively good field in the industry. It is also very user-friendly, has a large number of learning samples and training data, and is repetitive. It can give an evaluation of the algorithm in the process of application. Form a closed loop and continually improve the optimization. For example, the search sorting algorithm, the e-commerce recommendation algorithm, and the closed loop of its own data; such as the speech recognition of the University of Science and Technology, and the data input method of the University of Science and Technology, the collection of the identification error data, forming a closed loop.
Therefore, the core of the beginning is to prepare the data, and the core of the latter is to create applications. Wu Minghui said that the future research and development model must be a collaborative, open source model, artificial intelligence algorithms will not be a magical thing.
Millward Brown data of R & D line <br> <br> Wu Minghui details the positioning of Millward Brown data, policies, and research and development focus. His goal is simple, first to help customers prepare the data, use this data to achieve artificial intelligence in all walks of life, of course, in the process also use some artificial intelligence algorithms.
Focus on vertical field <br> Wu Minghui said that the current data mining market is larger, and the positioning of the data is applied in different enterprises, from the underlying data storage / cleaning / governance to the upper level of relationship mining, and behind Machine learning must focus on a few vertical areas, a full set of services, both big data and artificial intelligence - all customers who want to do artificial intelligence, the first thing is definitely to make the data. He explained that if enterprise-level services can't focus on the vertical field, they will eventually become a pure enterprise-level software. From the current trend, the final competitor is not the market and the enterprise, but the open source community. This is not a A reliable business model, at least in China.
In the vertical field where the data is focused, the most important direction is public safety. Other areas include finance, taxation, and manufacturing. The clear goal is to achieve the most bullish police in the public security field and achieve the most in the financial field. The cow's risk controller and auditor, the most effective doctor in the medical field... Wu Minghui introduced that there is already a preliminary exploration in the manufacturing industry for the detection and prediction of faults based on equipment data and deep learning for a large manufacturing company. Wu Minghui said that although this is the simplest job, the final goal will be very exciting.
Data governance as the core <br> <br> Millward Brown research and development center of gravity data at this stage, Wu Minghui also represent data governance, which in turn is associated more focused on data mining - companies currently have a variety of scattered data there are different In the system, the data should be linked, and the explicit and implicit associations should be mined. For example, in the public security system, hotel data, flight data, communication data, map data, etc. exist in different systems. Connected, according to a few people often travel together, through the algorithm to infer that they are colleagues or friends. Wu Minghui believes that the data management and the association of the mining, the data will be really connected, will greatly help the realization of artificial intelligence in the future.
The HV power module is also equipped with a DB9 interface to facilitate the bus control of embedded installation equipment. Customers can apply 0-10V signals and dry contact signals to the interface according to our interface definition to achieve comprehensive control and monitoring functions on the power supply, like high voltage start / stop, output setting and reading.
The CCP1000 high voltage power modules are equipped with complete protection functions, which can deal with sparking, short-circuit, and overload conditions. With the discharge protection circuit recommended by iDealTek-Electronics, the high-voltage module can also cope with conventional capacitor charging and discharging conditions.
At present, the high voltage power modules are mainly used in air or oil fume purification, capacitor charging and other application fields that require a high-voltage power module that can be embedded installation.
Wu Minghui: The core of artificial intelligence must be big data.
Recently, Wu Minghui, Chairman of Mingluo Data, interviewed by reporters, based on his educational background and entrepreneurial practice, analyzed the technical context of big data and artificial intelligence, and the latest layout of artificial data for artificial intelligence technology, including thinking about future research and development priorities. . Developers can get inspiration from where to go.In Wu Minghui's view, the core of artificial intelligence is the need for a large amount of data support, whether it is machine learning training or other algorithm optimization. The recent data of RMB 200 million B-round financing will continue to focus on data mining and storage/cleaning/governance research and development at the basic level. At the business level, resident scientists are required to go deep into the customer to achieve business needs. Intelligence, realizing the value of corporate data.
Artificial intelligence is the core data support <br> <br> today's perspective, machine intelligence training results mainly from statistical machine learning, especially learning the depth perception accuracy of intelligence and natural language processing to enhance the great contributions, but also on (identity The data is extremely eager. In order to solve some migration learning methods that are lacking in data, the premise is that there is a related field that can provide data for initial training.
Wu Minghui, who was born in the artificial intelligence profession, has long believed in the role of the data foundation. He even believes that it is impossible to implement artificial intelligence in a scene without data. So, with the goal of implementing artificial intelligence, he was aiming to generate and process high-quality data when he first started his business. Wu Minghui said that Mingluo data focuses on the mining of data itself. In the early days of the company's establishment, it hopes to apply big data to artificial intelligence, whether it is doing big data, mining data itself, and using mining data to do artificial intelligence. Training samples because the relationship between big data and artificial intelligence is very close.
Wu Minghui's professional direction in postgraduate studies is the special industry biometric identification in artificial intelligence, including fingerprint palmprint recognition and vein recognition. Like the popular face recognition today, it belongs to the field of image processing. Although computer vision and deep learning are hot, the data does not change the meaning of technical strategy. Wu Minghui believes that the lack of data preparation is the main challenge for enterprises to apply artificial intelligence/machine learning. For example, unmanned vehicles also require a large amount of test data to continuously test the algorithm. Throughout the interview, he also stressed that “there is no need to deal with the data first, and the data processing is not good.†He believes that it should take more time to find the right data from the Internet/mobile Internet. Clean and used to implement artificial intelligence.
AI + Big Data <br> <br> of course, have the data, also need good algorithm applied to the data, while forming a feedback system in the business scenario above - if not a very good application form, only the original Data, in the end, may not be able to form a self-improving ability to update, such as AlphaGo's limited 9-segment player's game that is published every year in the world, but also a lot of feedback from the PK countless rounds, and then find the reason for winning or losing. Improve.
At present, the artificial intelligence/machine learning algorithm is applied in a relatively good field in the industry. It is also very user-friendly, has a large number of learning samples and training data, and is repetitive. It can give an evaluation of the algorithm in the process of application. Form a closed loop and continually improve the optimization. For example, the search sorting algorithm, the e-commerce recommendation algorithm, and the closed loop of its own data; such as the speech recognition of the University of Science and Technology, and the data input method of the University of Science and Technology, the collection of the identification error data, forming a closed loop.
Therefore, the core of the beginning is to prepare the data, and the core of the latter is to create applications. Wu Minghui said that the future research and development model must be a collaborative, open source model, artificial intelligence algorithms will not be a magical thing.
Millward Brown data of R & D line <br> <br> Wu Minghui details the positioning of Millward Brown data, policies, and research and development focus. His goal is simple, first to help customers prepare the data, use this data to achieve artificial intelligence in all walks of life, of course, in the process also use some artificial intelligence algorithms.
Focus on vertical field <br> Wu Minghui said that the current data mining market is larger, and the positioning of the data is applied in different enterprises, from the underlying data storage / cleaning / governance to the upper level of relationship mining, and behind Machine learning must focus on a few vertical areas, a full set of services, both big data and artificial intelligence - all customers who want to do artificial intelligence, the first thing is definitely to make the data. He explained that if enterprise-level services can't focus on the vertical field, they will eventually become a pure enterprise-level software. From the current trend, the final competitor is not the market and the enterprise, but the open source community. This is not a A reliable business model, at least in China.
In the vertical field where the data is focused, the most important direction is public safety. Other areas include finance, taxation, and manufacturing. The clear goal is to achieve the most bullish police in the public security field and achieve the most in the financial field. The cow's risk controller and auditor, the most effective doctor in the medical field... Wu Minghui introduced that there is already a preliminary exploration in the manufacturing industry for the detection and prediction of faults based on equipment data and deep learning for a large manufacturing company. Wu Minghui said that although this is the simplest job, the final goal will be very exciting.
Data governance as the core <br> <br> Millward Brown research and development center of gravity data at this stage, Wu Minghui also represent data governance, which in turn is associated more focused on data mining - companies currently have a variety of scattered data there are different In the system, the data should be linked, and the explicit and implicit associations should be mined. For example, in the public security system, hotel data, flight data, communication data, map data, etc. exist in different systems. Connected, according to a few people often travel together, through the algorithm to infer that they are colleagues or friends. Wu Minghui believes that the data management and the association of the mining, the data will be really connected, will greatly help the realization of artificial intelligence in the future.
The CCP1000 series high-voltage power supply module is a single-phase 220Vac input modular high-voltage power supply. The whole series adopts unified small and compact aluminum chassis with the designed output power at 1KW, and the output voltage levels at 5KV / 10KV / 20KV / 30KV / 40KV / 50KV for selection.
The HV power module is also equipped with a DB9 interface to facilitate the bus control of embedded installation equipment. Customers can apply 0-10V signals and dry contact signals to the interface according to our interface definition to achieve comprehensive control and monitoring functions on the power supply, like high voltage start / stop, output setting and reading.
The CCP1000 high voltage power modules are equipped with complete protection functions, which can deal with sparking, short-circuit, and overload conditions. With the discharge protection circuit recommended by iDealTek-Electronics, the high-voltage module can also cope with conventional capacitor charging and discharging conditions.
At present, the high voltage power modules are mainly used in air or oil fume purification, capacitor charging and other application fields that require a high-voltage power module that can be embedded installation.
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Yangzhou IdealTek Electronics Co., Ltd. , https://www.idealtekpower.com