Shulou(Shulou.com)11/24 Report--

With the development of the times and the continuous improvement of the level of science and technology, artificial intelligence (AI) technology is also in continuous development, which provides great convenience to our production and life.

Common artificial intelligence technology

AI is a general purpose technology, which is being applied from local to all kinds of industries. Such as traffic autopilot, manufacturing industry quality inspection, voice recognition and so on. According to the 2019 "towards a New World of everything" study, the adoption rate of AI by enterprises will reach 86% by 2025. So how to integrate AI into the production and life of enterprises?

First, let's take a look at the development process of AI applications:

A) determine the purpose, clarify the direction of AI application development, in order to determine the subsequent development direction and the overall architecture.

B) prepare data, that is, collect the original data needed for the analysis and processing of the current AI application. The original data is to ensure that AI can better predict and analyze more data, thus reducing the consumption of manpower.

C) the training model, the data to be collected will be trained with certain computing power and algorithms, and finally the model will be used for later prediction and analysis.

D) the evaluation model is used to evaluate whether the accuracy of the model generated by the training is up to the standard. If the model is not up to the standard, it is necessary to continue the training optimization.

E) deployment model, which will deploy the model passed by the evaluation to specific equipment for predictive analysis.

Among them, data, computing power and algorithm are the three elements of artificial intelligence, which play a key role in the process of AI application development.

The whole AI application development process involves a lot of professional knowledge, such as the construction of the overall application framework, the selection of appropriate algorithms, the process of application deployment, enterprises need to overcome a lot of difficulties in AI application development. To further simplify the difficulty of developing AI applications, Huawei Cloud has launched an one-stop AI development platform, ModelArts. The following is the overall framework of ModelArts:

Overview of Huawei Cloud ModelArts platform Architecture

Huawei Cloud ModelArts platform supports multiple devices (Ascend, Kunpeng), provides massive computing power for AI application development, and supports the industry's mainstream AI development frameworks (PyTorch, TensorFlow, MindSpore). At the same time, the matching ecological community AI Gallery also provides a large number of open source data sets, algorithms, models and other content to help developers obtain development resources for AI applications.

As mentioned earlier, a completed AI application development requires five steps: determination of purpose, preparation of data, training model, evaluation model, and deployment model. In addition to determining the purpose, the ModelArts platform can be optimized in the last four steps to improve the efficiency of AI applications.

Prepare data: on ModelArts, you can select a large number of data sets on Gallery for development. At the same time, common data set formats such as image classification, target detection and speech recognition are supported. If it is unlabeled data information, you can label only part of the data, and then call the fast annotation to complete the annotation of all the data.

Training model: on ModelArts, you can choose the common algorithms on Gallery for training, and also provide the current mainstream LLM model for fine-tuning. At the same time, you can provide real-time view of the training log during the training process to facilitate problem troubleshooting.

For evaluation models and deployment models, ModelArts also provides corresponding evaluation methods and online deployment testing functions to facilitate developers to use them quickly.

At the same time, in order to further reduce the development difficulty of developers, ModelArts will prepare data, training model, evaluation model, deployment model to form a Workflow pipeline, developers only need to talk to ModelArts, provide the data set needed by the project, ModelArts will automatically analyze the data set and select its own algorithm to train to get the final model, and evaluate to the developer.

ModelArts conversation Workflow

Of course, if you want to develop your own algorithm, ModelArts also provides cloud Codelabs code development environment, which can quickly call the cloud AI computing power and storage space to achieve the rapid development of AI algorithm. At the same time, it also provides local IDE + ModelArts plug-in, remote direct connection to cloud resource development, close to your usage habits.

Codelabs operating environment

So far, many enterprises have used the ModelArts platform to develop AI applications in various scenarios.

Many sellers develop AI application scenarios based on Huawei Cloud AI development production line ModelArts, creating an AI shelf identification solution to solve the problems caused by the diversification of commodity packaging in the FMCG industry. The shelf identification solution integrated with Huawei Cloud AI capability can accurately obtain goods and their location information, and calculate the number of layout / shelf ratio in milliseconds, thus greatly improving business efficiency. It can also be used to identify complex scenarios with high precision. Through technological innovation, a professional anti-remake solution is created with the shelf head of the FMCG industry as a pilot in the actual scene.

Henan Xinlei Group integrates and uploads operation data, coke data, raw coal data, production process equipment sensor data and other data to Huawei Cloud through its business system, which is intelligently calculated and analyzed by Huawei Cloud AI to obtain the optimal coal blending ratio. In the initial stage, the average accuracy of the coke quality prediction model is more than 94%. With the increase of data samples, the accuracy of the model will continue to improve, and at least 30 million of the cost can be saved every year.

Using ModelArts platform, Tuo Anxin realized the fast marking and training of water meter photos, and completed the development and optimization of water meter reading recognition algorithm. Save tens of millions of manpower costs, achieve AI automatic water meter reading, and automatically input into the management system, management efficiency increased by 30%, but also further ensure the data security of customers.

Water meter reading recognition

Thus it can be seen that ModelArts, an one-stop AI application development platform, provides full-process help for enterprise AI application development, and effectively improves the development efficiency and output of AI applications.

Times are changing with each passing day, and science and technology are developing at a high speed. As early as 2025, China's State Council issued the "made in China 2015" policy, in which intelligent manufacturing is the core of this policy. In order to further improve the AI capability of enterprises, we need to constantly learn AI knowledge and use appropriate AI development tools to bring greater convenience to our production and life.

In September this year, Huawei developer space stack jointly created by Huawei Cloud, Kunpeng, Luoteng and Terminal was officially launched! Space stack is a technological growth and learning position for a new generation of developers, focusing on hot technologies or cutting-edge trends in industries such as artificial intelligence, big data and the Internet of things. Through training camps, community activities and other forms to help developers to learn more about Huawei technology and products, continue to build future competitiveness, interested developers can search Huawei developer website to enter the experience.

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