We provide the implementation or support for the implementation of artificial intelligence and machine learning solutions. We also offer one-stop development in collaboration with big data, IoT, and more.
AI and machine learning encompass a variety of mechanisms, exceeding 50 types, ranging from relatively simple ones that utilize statistics to the latest AI methods that employ deep learning. Below are the main functions provided by AI and machine learning: Regression - This involves trend analysis and forecasting. It can also derive the contribution of multiple factors to the results. Classification - This refers to categorization, with various applications such as image classification and credit screening. Clustering - This is also a form of classification, but the software makes its own judgments to categorize data, which can lead to discoveries that humans may not have noticed before. In addition, there are various mechanisms including the popular deep learning, and the fields of application are expanding.
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There are various forms of operation, ranging from on-premises to cloud-based operations. - Methods: Statistics, machine learning, deep learning - Operations: On-premises, cloud - Learning methods: Using pre-trained models, starting from scratch - Data: Public data, internal data Therefore, it is necessary to choose what aligns with the customer's objectives and goals. For example, if you aim to analyze the factors that influence the sales of a certain series of products to aid future product development, it may not be necessary to use deep learning in the cloud; having a statistical method like multiple regression on-premises along with a BI tool might be sufficient to achieve your goals. Since the most efficient methods and forms vary depending on the objectives, it is important to select what is suitable for the customer.
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Applications/Examples of results
Here, we introduce an example of a somewhat unusual problem-solving achievement. The diagram above shows how the picking route for parts in a factory has been optimized using machine learning. When a skilled worker performs the picking task, they naturally pick along the shortest route. However, when an inexperienced worker does it, they may not be able to follow the shortest route, leading to decreased efficiency. This system allows even inexperienced workers to follow a sequence comparable to that of skilled workers, thereby preventing variations in efficiency among workers. This is a classic traveling salesman problem, but by utilizing machine learning, we can find the optimal solution in a realistic timeframe.
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Relationship with IoT and Big Data Sensor data from IoT and data from business activities are stored as big data and are used for corporate purposes such as analyzing data to investigate the causes of issues, formulating countermeasures, and making predictions to aid in product development. The data is utilized as training data for AI and machine learning. As shown in the diagram below, the results are only effectively used when they feedback, like the red arrows, to solve the challenges and achieve the objectives that the company has.
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Data Utilization For data that is not publicly available, such as corporate data, we must start from the collection of the data itself. Below is a diagram summarizing the acquisition and utilization of this data. By storing data in a database instead of individual Excel files, it becomes possible to share the data, enabling its utilization for statistics, AI, and machine learning. Our company actively supports these four stages.
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Problem-Solving Process Our company defines the problem-solving process in three stages as follows. There is no charge for the hearing, but costs will be incurred for the subsequent stages.
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About Frequently Asked Questions I believe many people have questions about how artificial intelligence, machine learning, and deep learning, as well as their English representations, differ. When illustrating the relationships among them, it looks like this.
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We have over 35 years of experience and achievements in software development. We provide various services ranging from open systems to embedded software development. Iwatsu Software Systems is a 100% subsidiary of Iwatsu Electric Co., Ltd., which manufactures and sells business phones and measuring instruments. While we also develop software for Iwatsu products, we actively engage in contract development for external clients as well. Please feel free to consult with us.