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【2021 Solutions】 Action Bagel makes AI as simple and efficient as Excel to improve data analysis capabilities

What is AutoML (automated machine learning) and how is it different from ML (traditional data analysis)? It needs further clarification first.

Traditional machine learning must go through data cleaning, data pre-processing, feature engineering, feature selection, algorithm selection, model establishment, model training, parameter adjustment, and then evaluation results to produce model applications. During the process, if there is a problem with the parameters, the algorithm must be re-selected, the model must be re-established, etc., and the process must be repeated hundreds of times. If new information becomes available, all steps must be repeated. Through automated machine learning, the output process of model application only needs to go through the automation of four major steps: data cleaning, feature engineering, data modeling and model evaluation to achieve model application. Even if new data needs to be collected, it can be achieved through Automated machine learning is achieved, saving time and effort.

ML and AutoML Comparison source: Action Bagels Ltd

▲Comparison between ML and AutoML Source: Action Bagel Co., Ltd.

AutoML is a program that can automate the time-consuming and repetitive work in machine learning model development. This allows small and medium-sized enterprises that relatively lack AI talents to create their own customized machine learning models. In recent years, major international companies have rushed into this market, including Cloud AutoML released by Google in 2018, and AutoPilot launched by cloud computing leader AWS in 2019. AutoML has become a standard feature of mainstream learning services, from web-based interfaces to free Program development and workflow visual management, etc., service development is becoming more and more diversified.

MoBagel is a professional team composed of top data scientists, engineers, and product project managers. The team members come from prestigious universities around the world, including Stanford, Berkeley, Oxford, and National Taiwan University in the United States. They also have experience in Selected to participate in Silicon Valley's well-known accelerator 500 Startup, selected to participate in Japan's SoftBank Innovation Program, and also won a name in Nokia's Open Innovation Challenge.

Mobile Bagel Decanter AI platform shortens the analysis project from two months to two days

Mobile specializes in data science and machine learning technology. In 2016, it developed the automated machine learning analysis tool Decanter AI. So far, it has helped more than 100 companies introduce AI into important decisions, and the analysis project has been shortened from two months to Two days. The fields served include retail, telecommunications, manufacturing, finance and other industries.

Lin Yushen, deputy general manager of Action Bagel Co., Ltd., said that Decanter AI makes AI as simple and efficient as Excel, which can improve enterprise data analysis productivity. Users do not need to have in-depth professional knowledge and experience. Through a simple super-operating interface, they can perform automated machine learning for data analysis and prediction.

There are three simple steps to use Decanter AI: Step 1. Organize the data into csv format; Step 2. Upload to DecanterAI to set prediction goals; Step 3. Decanter AI automatically models and obtains prediction results. The deployment method can be in the public cloud or in the private cloud of the enterprise. After the internal data is uploaded, it can be modeled and used.

DecanterAI uses three steps, Simple and convenient

▲DecanterAI uses three steps, simple and convenient

The advantage of AutoML is that it can automatically train a large number of models, adjust parameters, produce the best model, and quickly deploy and import it. After the new coronavirus (COVID-19) epidemic, all walks of life are facing new market changes and must Transform digitally with fast and convenient digital tools.

In recent years, Action Bagel has continued to promote the optimization of the DecanterAI platform and establish industrial data modeling and analysis capabilities, and has produced substantial results. For example, Chunghwa Telecom uses its platform to conduct blind tests on code-carrying customers and perform data analysis to effectively reduce user churn rates and improve customer retention rates. As a leading domestic food manufacturer, due to the expiration date of drinks and the production and sales of the cold chain, it must be fully integrated to reduce inventory and loss problems. After importing the DecanterAI platform, in addition to accurately predicting market demand, it can also accurately predict market demand based on expiration date data. Analyzing production and distribution quantities can also help reduce warehousing and logistics costs.

AutoML industry has diverse and extensive applications and great potential for future development

Action Bagel believes that AutoML has a wide range of industrial applications, including employee turnover prediction, production demand prediction and revenue performance prediction that are troubled by the manufacturing industry; store passenger flow prediction, product replenishment prediction, membership prediction in the smart retail industry Promotional forecasting; customer churn forecasting and potential customer list forecasting in the telecommunications industry; accurate financial marketing, credit card fraud detection and insurance application quick review in the financial industry; and even real estate price forecasting, power outage disaster forecasting, etc. are all helpful. To solve the operating difficulties of the industry and create new business models.

AutoML industrial applications are diverse. Covering manufacturing, retail, finance and other industries. Source: Action Bagel Co., Ltd.

▲AutoML has diverse industrial applications, covering manufacturing, retail, finance and other industries. Source: Action Bagel Co., Ltd.

How much time and preparation does it take to import AutoML? Lin Yushen said that in actual practice, the introduction process of automated machine learning enterprises includes four major stages:

1. Preparation period: Collaborate with enterprises to discuss business pain points, help define analysis propositions, and provide professional data science advice and optimal solutions, lasting about two weeks.

2. Verification period: Use a small-scale pilot project to quickly verify the analysis results to ensure proposition setting, data quality, analysis process, prediction technology, etc., as the basis for subsequent practical application and amplification. It takes three weeks.

3. Introduction period: Support cloud or local product deployment according to enterprise needs. Provide operation and maintenance teaching, Help Center, data analysis consulting, corporate training courses and other product introduction services, which will take more than one month.

4. Application period: Analysis/data teams can execute various AI projects through the product's common interface and implement them quickly. The prediction engine can be connected through the API to develop application modules according to practical scenarios. This is the final stage of application and is time-consuming and can take up to several months.

However, Action Bagel conducts a system integration project process with its SI partners. The SI partners discuss business propositions and provide data sets, and then conduct data health checks and Baseline models. Based on this, Action Bagel provides data diagnosis reports. After confirming the pilot project proposition and producing a demand planning document, the project execution phase begins, with model establishment, optimization and analysis reports provided. System integration with SI industry players, on the one hand, optimizes module development, and on the other hand, uses APIs to connect data sources and output prediction results, import them into the enterprise's field, and effectively solve the propositions faced by enterprises in digital transformation.

Looking forward to the future, Decanter AI platform will continue to develop various AI innovative application services, and cooperate with the upstream, midstream and downstream industries such as enterprise resource planning (ERP), customer relationship management (CRM), business analysis (BI) and e-commerce platforms ( EC) and other partners maximize the benefits of the ecosystem through co-creation, sharing and altruism.

(This article is derived from the selected content of "AI Engineering Online Small Gathering")

「Translated content is generated by ChatGPT and is for reference only. Translation date:2024-05-19」

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【解決方案】瑕疵辨識率達百分百 耐銳利科技獲面板大廠青睞
Defect identification rate reaches 100%, Nairi Technology is favored by major panel manufacturers

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long time Tang Guowei, general manager of Narili Technology, pointed out that the top three CNC machine tool factories in Taiwan hope to introduce AI into the two production lines of assembly and casting Among them, on the assembly line, in order to maintain the accuracy of assembly, every part of the component is designed Tolerances are designed During assembly, each component is within the tolerance However, the cumulative tolerance still fails the final quality inspection and must be dismantled and reassembled This is not only time-consuming and labor-intensive, but also causes waste "After entering the production line, I realized that some masters have accumulated a lot of experience and are good at adjustment After his adjustment, the accuracy rate has improved a lot and the speed is faster" On the contrary, the new engineers did not Based on experience, it takes a long time to adjust and may not pass the quality inspection The yield rate of Master 40 system has increased 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affected by unexpected factors such as delays in the customer's construction period, the elevator factory will often be idle or the schedule will be difficult to arrange Tang Guowei pointed out that generally those who understand the progress of client projects may be from business or engineering, but overall, the accuracy rate of shipments is only about 60, which means that 40 of them will not be shipped as scheduled Therefore, if the shipping schedule can be accurately estimated, the production line can be freed up for emergency orders or other product production needs The AI smart scheduling system will analyze past shipment data, about 20-30 parameters such as climate, distance between the factory and the construction site, and customer credit, and put them into the AI algorithm to accurately predict whether shipments can be made as scheduled goods Huang Changding also specifically stated that the machine learning of Naili Technology is not ordinary machine learning, but also 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content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】聲麥無線推出殺手級5G即時AI語音翻譯 降低5成口譯成本
VM-Fi launches killer 5G real-time AI voice translator that reduces interpretation costs by 50%

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【解決方案】客廳化身為健身房 Uniigym矢志成為健身界的Netflix
Living Room as a Gym: Uniigym Aims to be the Netflix of Fitness

Afflicted by the pandemic, most people choose to stay at home However, for those who enjoy exercising, missing a day at the gym can feel uncomfortable With Uniigym's 'AR Fitness x Uniigym' app, users have access to nearly 1,000 diverse exercise classes With a dedicated AI coach, users can exercise anytime they wish, while also tracking their fitness journey, and understanding their condition completely To encourage public fitness and fight the pandemic together, Uniigym has also collaborated with Chunghwa Telecom, offering free access to the 'AR Fitness x Uniigym' app for 30 days starting from now until the end of June, contributing to the public health effort Founded in 2019 by CEO Yu-Chieh Lin, Uniigym was conceived from the monotony and limited options of gym venues like fitness centers and school gyms, and low interaction with trainers The company aims to make exercising as fun as gaming through technological solutions, starting with their first product—an intelligent dynamic 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heart-rate devices to gather health data and offer health management solutions Features of the AR Fitness x Uniigym App "Uniigym is a combination of Netflix and Nintendo, aiming to become the Netflix of the fitness world" By lowering the barriers to exercise through Uniigym's diverse workout classes and fostering a national habit of exercise, marketing director Shu-Wei Wang explained the company's strong ambition and its ongoing progress towards these goals Since the launch of the AR Fitness x Uniigym app in collaboration with Chunghwa Telecom in November 2021, the app has seen over 20,000 downloads in less than half a year, featuring nearly 1,000 multi-category classes including aerobics, fat-burning, body sculpting, strength training, yoga, boxing, and popular dance Built-in latest AI posture algorithm for real-time monitoring of exercise state The AR Fitness x Uniigym APP features six key functionalities, consisting of One Celebrity fitness courses, featuring a hundred top 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belts to display changes in heart rate on the screen during exercise By employing technology in exercise, it not only protects users during training but also helps in logging physical energy consumption, effectively enhancing exercise efficiency and preventing exercise injuries Uniigym is deeply rooted in Taiwan and expanding to international markets In fact, Uniigym's products are iteratively evolved according to different user groups The second generation product, Uniihome, turns living rooms into gyms in collaboration with the television system platforms, Taiwan Broadband Communications and Kbro, featuring set-top boxes with a menu of 1,700 classes, each lasting 3-5 minutes suitable for all family members ranging from grandparents to children, providing a freely selectable fitness menu for different groups AR Fitness x Uniigym App Product Experience Scenario Illustration In the post-pandemic era, exercising at home has become a trend Uniigym's interactive sensor-based fitness courses offer consumers a convenient, economical way to exercise anytime, anywhere It eliminates the need for purchasing fitness equipment or spending on expensive courses, as users can enjoy personal guidance from an AI coach directly through their smartphones, enhancing their willingness and frequency of exercise, playing an essential role in promoting a healthier lifestyle for all Uniigym provides a combination of online and offline AI cloud-based interactive sensor technology services, matched with home settings and various types of exercise spaces, to offer consumers an entry-level threshold to enjoy professional and entertaining fitness experiences anytime, anywhere This innovative business model has attracted investments from renowned Taiwanese listed companies such as, Nan Yih Textile and Taishin International Bank, and also partnerships with notable international sports enterprises like Decathlon Besides deep-rooting in the Taiwanese market, Uniigym is also actively expanding into international markets including Singapore, Thailand, and China This year 2022, Uniigym plans to launch its products with the Singaporean telecom group Singtel, allowing Chinese-speaking users and a broad international audience to enjoy new interactive sensor-based fitness courses In the future, Uniigym will also introduce home-based health management solutions for corporate and government employees, where employee health data is collected during exercise through cameras or heart rate devices, analyzed, integrated, and linked with health and medical data to achieve preventive medical goals Uniigym founder and CEO, Yu-Chieh Lin「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」