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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】滴水不漏的智慧工安巡檢 鑫蘊林科Linker Vision的影像分析AI平台 創造巡檢時間從100分鐘降至3秒新紀錄
Watertight smart industrial safety inspection Linker Vision’s image analysis AI platform sets a new record of inspection time reduced from 100 minutes to 3 seconds

With the rise of smart manufacturing, there is a demand for industrial safety inspections in high-risk industries such as chemical, energy, and electrical industries Take pipeline inspection in the chemical industry as an example It relies heavily on manual regular inspection and monitoring, and lacks intelligent monitoring by a professional AI team This is not only time-consuming and labor-intensive, but may also cause accidental risks to employees in various industrial safety environments The image analysis AI platform developed by Xinyun Linke not only improves employee personal safety and reduces risk factors, but also significantly reduces the time for human visual inspection of pipeline abnormalities from an average of 100 minutes to 3 seconds Paul Shieh, founder and chairman of Linker Vision Co, Ltd Linker Vision, said, "The overall technological development and progress in the United States comes from entrepreneurship Linker Vision's original intention to start a business in Taiwan has been I hope that through my past experience in entrepreneurship in the United States, I can introduce the American entrepreneurial spirit and culture to Taiwan's budding entrepreneurial fertile ground and truly implement it "American entrepreneurial culture encourages employees to value ownership and emphasizes that employees regard themselves as owners of the company Be a part of the company, with a work attitude and spirit that would be better than mine The company's achievements are your own achievements, breaking the original employer-employee relationship The company will reward outstanding employees with stocks, share the glory together, and establish a partnership with employees Partnership On the other hand, Taiwan still has room for efforts in entrepreneurial culture and management, and it retains the traditional thinking of employers and employees It is expected that Xinyun Linke's establishment of American entrepreneurial culture and values in Taiwan will serve as a starting point to drive more domestic new companies to follow suit, and then Only by upgrading the business constitution of new software AI entrepreneurs can they break out of the cocoon and go global Facing the market, most international players focus on developing AI models and algorithms They are less willing to invest in data-centered Data-Centric AI services They think that processing large amounts of 2D or 3D data is quite time-consuming It’s also energy-consuming Seeing the gap in AI technology and encouraged by Microsoft, Xinyunlinke decided to fully invest in Data-Centric's AI technology layout and deep roots many years ago, and specialize in technical energy in data processing, filtering and accuracy Therefore, Become an important partnership with Microsoft for AI technology supply In addition, due to the gap in industrial demand, domestic large factories, whose strength is chemical manufacturing, still rely heavily on manpower for inspection of pipelines in the factory, which is time-consuming and labor-intensive However, in order to cater to the AI industry, the owner reorganized the IT department originally engaged in database management and control into an AI team However, due to the owner's lack of professional experience in AI software technology, AI models and related domain know-how, the owner introduced AI implementation Industrial safety monitoring in the chemical industry is even more challenging The world's first AI automatic labeling technology surpasses manual labeling and can visually identify objects with an accuracy of over 95 In terms of AI technology power, Xinyunlinke has launched the world's first dual-core innovative technology of automatic labeling Auto-labeling and automatic machine learning to create an efficient and stable image analysis AI platform to provide customers with the best Advanced and complete AI solutions In terms of automatic annotation, this AI technology can overcome the most difficult challenge in deep learning, which is to provide customers with the highest quality training data Taking self-driving cars as an example, how to enable one self-driving car to effectively identify another car is the importance of labeling In the past labeling methods, we first needed to collect digital images of millions of vehicles, roads, signs, and pedestrians, and spent a lot of manpower Manually labeling one image at a time was time-consuming, labor-intensive, high in labor cost, and inefficient Through automatic labeling AI technology, combined with automatic machine learning to automatically label digital images, AI can exclude human error labeling and then throw the correct data into the vehicle's brain for vehicle identification Compared with manual labeling accuracy of only 60, the accuracy of automatically labeling and identifying objects with AI can be as high as over 95 It can also reduce manual labeling time by more than 80 and save at least 80 of labor costs AI automatically marks AI behavior recognition for high-altitude operations In the automatic machine learning part, Xinyunlinke established an AI visual model with continuous learning capabilities to adapt to data changes By optimizing the overall development process, from AI data ingestion and filtering Data Selection to AI labeling AI Labeling , model training and verification, deployment and monitoring, so that AI computer vision can continue to learn more quickly and easily Automatic machine learning can currently be applied to different business cases such as object identification and counting, personnel entry and exit security detection, product defect detection, people flow identification, product shortages on shelves, etc Looking at domestic companies such as TSMC, Formosa Plastics and Hon Hai towards intelligent AI management and purchasing a large number of cameras to meet the image recognition needs of industrial safety surveillance, coupled with the introduction caused by the unfamiliarity of existing customer organizations with AI applications Thresholds and preliminary preparations for image recognition include complicated workflows such as data screening and annotation To this end, Xinyunlinke has been committed to accelerating the development of AI computer vision applications in recent years, providing client-to-end services, and can flexibly deploy according to customer needs Complete automated AI solution services in the cloud, on-premises, or cloud on-premises Xie Yuanbao said that the AI automation technology process provides data selection Data Selection AI technology through domain-type pictures given by customers, helping customers automatically filter out precise such as 10,000 transactions from a large amount of data such as 1 million transactions Data, and by using the AI algorithm technology of Auto-Labeling to replace manual labeling, it can effectively save customers a lot of labor costs and achieve efficient data labeling processing In addition, the AI technology of automated machine learning can help clients customize automatic AI model training or repeated training when the factory environment changes, providing more accurate AI models and allowing customers to operate autonomously Through the above-mentioned key features and advantages of the automated AI technology provided by Xinyunlinke, we believe that it can definitely meet the needs of customers for an automated end-to-end AI independent learning platform, and at the same time, it can significantly save customers the cost of AI team establishment In terms of technological competitiveness, in addition to providing the chemical industry with AI image analysis applications in smart industrial safety, Xie Yuanbao said that Xinyunlinke can also extend the process application of automatic annotation and automated machine learning to different industrial landing services, such as Various fields such as self-driving cars, smart warehousing self-propelled robots and self-driving buses in future smart cities are all in line with the spirit of automated mobility of Mobility as a Service We look forward to the role played by Xinyunlinke The process of image annotation in different industries accelerates the efficiency of developing image recognition services in different fields We believe that by providing client-to-end AI solutions and a complete set of automated AI image analysis pre-operation processes from Data Selection AI technology, Auto-Labeling AI technology, and automated machine learning AI technology, we can greatly satisfy our customers The demand for AI autonomous learning platform Image analysis AI platform sets a new record for smart industrial safety inspections from 100 minutes to 3 seconds Seeing the high demand for industrial safety supervision in high-risk industries such as the chemical industry in recent years, Xinyunlinke launched the "Vision AI Platform", which uses AI image recognition technology Its main functions include real-time AI streaming It has four major functions detection, event notification, defining customer-specific AI models and continuous learning In the real-time AI stream detection part, the Vision AI system can use the customer's factory camera combined with the AI module to perform real-time stream detection of AI image events It can help customers manage various operations and factory environments and keep track of them anytime and anywhere Various work situations in terms of event notification, the Vision AI platform can provide a web version or APP or LINE instant messaging software to provide customers with video records of the events at that time, so that the team does not miss any events, maintains daily production capacity and reduces accidents in defining customers In terms of exclusive AI models, a variety of basic AI models are available, including 8 detection scenarios electronic fences, personal safety equipment, construction safety equipment, construction operations, personnel counting, screen availability, smoke detection, pipeline corrosion and damage , illegal stacking for use in different industries, customers can build exclusive AI models without spending time writing programs in the continuous learning part, the Vision AI system can provide customers with the performance and accuracy of AI models, and have the ability to adapt as the environment changes Continuous learning ability Vision AI has a simple user interface and intuitive operation For cross-field industries, this platform has automated and flexible AI capabilities Customers can build self-defined AI models without spending time writing programs, and Vision AI gives AI models the ability to continuously learn and improve, allowing customers to save the labor cost of building an AI team In addition, the platform can significantly reduce the manpower allocation for routine inspections required for operational safety management, improve employee safety in the working environment, and reduce on-site accidentsrisk factors at various work sites In the platform operation mode, customers can reduce the risk of manual monitoring operations through remote operations, ensuring normal work operations and uninterrupted production operations They can also review high-risk operating situations and collect data to assist in the planning and correction of operating processes In addition, in order to ensure that customers comply with government regulations, Vision AI can help customers control the equipment and safety regulations required in different workplaces at any time through the platform's event notification and management detection The image analysis AI platform is used in cross-field AI image recognition technology Generally, for industrial safety inspections in the chemical industry, most rely on the naked eye of personnel to regularly inspect pipeline abnormalities It takes an average of 100 minutes to scan an area each time, which is time-consuming and laborious, and the pipeline location is difficult to visually observe, which may cause Employees are exposed to accidental risks in various work safety environments In order to reduce the pain points of industrial safety inspections in the chemical industry, Xinyunlinke assists well-known domestic chemical industry players by using an automated image analysis AI platform, combined with customized virtual electronic fences, and using in-plant cameras to configure AI pipeline leakage modules , the AI automatic inspection method can effectively reduce the abnormal detection time to less than 3 seconds In addition, cameras deployed in the factory can automatically record inspection schedules to achieve full-time monitoring, allowing customers to instantly discover and fully control pipelines, minimizing risks In addition, the automated image analysis AI platform can help customers apply fire warnings in factories It is conservatively estimated that the return on investment can be less than 9 months to pay back the investment The longer the platform is used, the higher the cost-effectiveness Build an automatic learning image analysis AI platform for Mobility as a Service in various fields Xie Yuanbao observed that the biggest challenge facing the entrepreneurial culture of software companies in Taiwan is that young new entrepreneurs or employees in Taiwan do not understand the entrepreneurial model and lack the awareness to regard themselves as part of the company owners This has caused It is a pity that your future is unclear or you have a past-experience mentality that prevents you from staying competent in a new start-up company for a long time I believe that the essence of true entrepreneurship lies in every employee rolling up their sleeves and working hard, so that they can truly enjoy the fruits of entrepreneurial profits Otherwise, for young entrepreneurs or employees who often change tracks, it will be like a rolling stone that gathers no moss , I am unable to take a deep root on the road of entrepreneurship, and I lose my ability to solidly accumulate financial independence Regarding the business promotion challenges of Xinyun Linke, Xie Yuanbao said with emotion that because the Taiwan market does not have a deep understanding of AI software applications, it relies more on open source AI visual analysis or machine learning and other resources on the market, but in fact These AI technology resources are limited in their ability to support customers' AI model needs, resulting in uneven quality of AI visual analysis software in the market Therefore, the impact is more indirect on Xinyunlinke's ability to truly provide customers with professional and data-centric AI image analysis services, and it also reduces the company's original business value in customer reference In terms of technical research and development challenges, the visual analysis AI platform cannot rely solely on AI model experts It must gather talents in various fields such as cloud, machine learning, data science, front-end and back-end and other professional team combinations to make the platform operate successfully Xie Yuanbao said that he believes that only through the automatic learning of the visual analysis AI platform, automatic fast and accurate data processing capabilities, and providing customers with complete AI solution services in the cloud, cloud ground Hybrid to pure ground, can we truly Convince customers and stand out from the competition Looking to the future, Xie Yuanbao hopes that Xinyunlin Technology can build an image analysis AI platform for Mobility as a Service to automatically learn in various fields such as self-driving cars, smart warehousing robots, and unmanned buses in smart cities At the same time, I am also grateful to the support of the Industrial Bureau of the Ministry of Economic Affairs for the smooth landing of Xinyunlin Technology in Taiwan and the opportunity to recruit talents from all walks of life to work together In the short-term layout, the company will actively cooperate with domestic players such as Hon Hai and TSMC to implement image analysis AI technology in fields such as self-driving cars, smart industrial safety, and smart warehousing robots In the medium to long term, Xinyunlinke will target the United States, Europe, Japan and other countries as its global market layout, establish investment and cooperation partnerships with major international companies such as Microsoft, and replicate its successful experience and promote it internationally Xinyunlinke official website Xie Yuanbao, founder and chairman of Xinyunlinke 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】AI智慧眼鏡 雄欣科技鎖定智慧照護市場 讓老者住得安心安全
AI + Smart Glasses: Hsiung-Hsin Technology Targets Smart Care Market, Ensuring Safety and Security for the Elderly

In the small care room, Mr Wang, who is over eighty, is coughing intensely The nurse gently uses a suction device to help him, hoping to make him more comfortable Meanwhile, a sharp-eyed family member notices that the nurse is wearing smart glasses At the other end, the doctor organizes medical records while simultaneously monitoring Mr Wang's condition on a screen With the advent of precision care, it will soon be a blessing for the care market for doctors to remotely monitor crucial physiological information of the cared-for in real time In fact, Hsiung-Hsin Technology, established in 2020, uses smart glasses combined with AI algorithms to launch smart care services as an AI startup Through AI multiple sensors to achieve effective smart care In 2021, Hsiung-Hsin Technology participated in the Ministry of Economic Affairs Industrial Bureau AI Emerging Selection event, cooperating with smart glasses leader Jozhen Technology Jozhen provided millimeter-wave radar and smart glasses, combined with Hsiung-Hsin Technology's AI algorithms, to launch 'AI Care Recognition Service System' and a life-saving 'Fall Prevention System' The 'AI Care Recognition Service System' uses radar millimeter waves and Time-of-Flight ToF among various sensor technologies combined with point cloud and mmWave deep learning analysis in AI algorithms While protecting personal privacy, it can detect patients' physiological data upon hospital admission as well as detect falls and bed exits during bed care The 'life-saving fall prevention system', on the other hand, utilizes artificial intelligence and 3D technology, combined with radar sensing devices, while protecting personal data through 'de-identification' technology, detecting falls in real-time in the environment Building the AI Care Recognition Service System, Hsiung-Hsin Technology is aiming at the smart care market Lee Jia-Hsin, founder and chairman of Hsiung-Hsin Technology, who has worked for IBM Taiwan for 14 years, states that after placing millimeter-wave radar in the medical test field, combined with AI algorithms, they can obtain physiological signals such as the patient's breath and heartbeat Moreover, when paired with Jozhen's smart glasses, during a doctor's consultation, the physician can immediately see the patient's heartbeat and breathing data through the glasses, enhancing efficiency Additionally, Jozhen has also developed a management platform where physicians and nursing staff can view the patient's physiological data at a glance After integrating the 'AI Care Recognition Service System' and 'Life-Saving Fall Prevention System', they were launched and commercialized in June 2021, and officially introduced into Kaohsiung Municipal Triumph Hospital by the end of November last year It not only helps medical staff understand the residents' physiological conditions, monitoring elders' physiological data continuously, but also reduces the burden on medical institutions while preventing accidents and enabling quick action in emergencies to provide optimal medical care Aside from medical institutions, another major target customer group for Hsiung-Hsin Technology's products are long-term care institutions, with ongoing product implementation plans in Tainan and Eastern Taiwan On-demand lightweight design, easy to use and reasonably priced Lee Jia-Hsin mentions that the company's productsservices are developed in-house, designed to be lightweight Depending on the needs of the institution where they are implemented, they may choose between CPU computing or edge computing for flexible configuration, which is very convenient and also comparatively cost-effective In the future, through Jozhen smart glasses, diagnoses can be made more immediately and quickly The method allows nursing or care staff to wear smart glasses when visiting patients or residents The images seen by the nursing staff's eyes are transmitted in real-time to the backend, allowing doctors to make immediate diagnoses based on real-time images and take appropriate care measures, effectively assessing the patient's condition on time Hsiung-Hsin Technology's smart care services have been listed on the Startup Common Supply Contract Platform Last year, Hsiung-Hsin Technology's productsservices were also listed on the Ministry of Economic Affairs, Small and Medium Enterprise Administration's Startup Common Supply Contract Procurement Platform, available for government agencies, public medical institutions, and long-term care facilities to purchase for lease In the future, they hope to expand to private medical institutions and care centers, enabling more care facilities to utilize technology for transformation and reducing the talent shortage in the care market Furthermore, with more than 300,000 elderly people living alone in Taiwan, Lee Jia-Hsin believes that as the aging society approaches, the health and safety issues of solitary elderly individuals are increasingly receiving attention If technological care medical solutions can be incorporated into the subsidy scope for assistive devices, it can also help reduce the burden on local government institutions for solitary elderly care, effectively lowering societal costs Extended application Smart campuses enhance management safety and efficiency Lee Jia-Hsin points out that the company's core values are making life safer and improving living quality The company has developed its own software and hardware solutions for big data, artificial intelligence, and the Internet of Things Using a hybrid cloud development approach, it addresses various types of medical care pain points, enhances medical management efficiency, and improves residents' safety, thus significantly enhancing overall services by medical institutions Hsiung-Hsin Technology's partners include SI businesses, medical care institutions, large chain restaurants, and major venues In the future, there are plans to develop into an AI SaaS company, extending services to Japan, Southeast Asia, and other overseas markets Additionally, Lee Jia-Hsin, who teaches at Tunghai University in Taichung, is also actively promoting the smart campus initiative Currently, Hsiung-Hsin Technology has established a 'smart campus' at Tunghai University, utilizing up to 700 cameras throughout the campus to build a miniature AI SaaS platform for monitoring This not only allows for mask, human traffic, restricted area, and license plate recognition within the campus but also enables automatic records of the campus's flora and fauna, greatly aiding in the efficiency of campus safety management As the population gradually ages, home care becomes a universal challenge With a low doctor-to-patient ratio, both inside and outside hospitals, including extended to care institutions, medical professionals face a scarcity of manpower Using AI technology to assist the elderly care market presents itself as the best solution Besides smart elderly care and smart campuses, Hsiung-Hsin Technology also applies its image recognition technology in places like factory safety and parking lot license plate recognition, and future applications will continue to expand boundlessly Hsiung-Hsin Technology's founder and chairman, Lee Jia-Hsin「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】洞悉消費者行為 智能演譯運用AI協助餐飲業順利轉型
Insight into consumer behavior and intelligent interpretation using AI to assist the catering industry with smooth transformation

In May 2021, due to the local COVID-19 outbreak, a ban on internal use was adopted, making the catering industry feel like it has entered a cold winter, with business bleak and operations facing difficulties However, there are also catering companies that have turned the crisis into an opportunity and actively carried out digital transformation, introducing online ordering and delivery platform systems, establishing customer membership systems, etc, to effectively reduce inventory and increase sales Intelligent Interpretation, a new start-up company established just one year ago, acts as a transformation consultant for the catering and retail industry, collecting, connecting and analyzing consumer behavior data to provide the best solutions for the cateringretail industry Li Qihan, the founder of Intelligent Interpretation, is good at online marketing and website construction As AI technology continues to evolve, he graduated from the Northern Phase II Manager Class of Taiwan Artificial Intelligence School AIA and was impressed by the large number of website sales Data and marketing analysis data can help companies improve their competitiveness and reduce operating costs Therefore, we established an intelligent interpretation company with Taiwan Artificial Intelligence School alumni, hoping to use member information to start collecting more first-party data to help customers build customer vision Analyze the data and identify relevant sales opportunities Targeting the catering and retail industries, intelligent interpretation helps stores use AI to transform "There are many small and medium-sized restaurants in Taiwan We hope to help these small and medium-sized restaurants use simple cloud services and social tools, such as Line, to start collecting and establishing member information systems and collect relevant information Consumption data is used to establish behavioral models of different consumers" Li Qihan went on to say that the catering and retail industries will be targeted at the initial stage, and different consumption behavior analyzes will be used to help stores further increase the frequency of customers visiting the store and the frequency of dining or purchasing, and reduce the use of ingredients Preparation costs The main features of the AI service of intelligent interpretation Affected by the ongoing epidemic, which has severely impacted the performance of physical stores, intelligent interpretation also assists physical stores in establishing e-commerce websites or shopping malls, combining physical and virtual consumption data to provide 360-degree OMO consumers Analysis, and can send marketing messages to different consumers, reducing the large-scale and indiscriminate casting of traditional marketing methods that cause customers to blacklist merchants or block lines, and also increase consumers' willingness to click and purchase Will Li Qihan pointed out that the AI service of intelligent interpretation has the following characteristics 1 Use LINE combined with membership system 2 Use QR Code to replace membership card 3 Provide LINE online orderingreservation 4 Use AI to analyze consumers’ personal preferences 5 Send coupons based on consumer behavior and preferences Using Line ordering information, you can understand consumer behavior such as consumer type, taste, time period, ordering frequency, etc, find consumers of the same group, and conduct summary analysis, which is important for one-to-one customized marketing Reference Li Qihan emphasized that the cost of digital marketing at this stage is very high If there is no classification and grouping after acquiring customers, preferential information will be distributed randomly and easily blocked by consumers The conversion rate will become lower and lower, and the marketing budget invested previously will be in vain AI combines the advantages of MarTech to provide exclusive customized services Although Intelligent Interpretation is a new startup that has been established for nearly a year, in terms of the company's future development strategy, Li Qihan hopes to use MarTech combined with the advantages of AI to first assist the catering and retail industries that are currently most in need of digital transformation Quickly enter the first stage of digital transformation, establish member information and collect consumer data, and then assist these companies to enter the second stage of digital transformation, analyze and use these consumer data, and provide exclusive customized services Li Qihan said that Taiwan’s MarTech market still has considerable room for development Most companies think that advertising on the Internet is the so-called MarTech, or that combining website data with advertising conversion rates and looking at the GA report Google Analytics every day is the so-called MarTech However, he believes that the above situation is only It stops at the collection and analysis of marketing data and is not integrated into the corporate sales and management levels In fact, after the data is collected, it still needs to be integrated, analyzed, and applied according to individual business scenarios This is the real MarTech application method Li Qihan, founder of Intelligent Interpretation, shared his smart retail experience at the AIGO forum As for most companies that believe that as long as they have data, AI algorithm analysis can solve all problems, Li Qihan suggested that companies should have a correct concept of data First, it does not have to be big data AI algorithms can also work with small data Great effect 2 Data is accumulated year by year To collect information, you need to understand the purpose and needs After collecting data, you need to find out its correlation That is to say, first define the use situation and the problem you want to solve, collect data, Only by analyzing data and using machine learning to identify undiscovered sales opportunities can we start to provide marketing application suggestions "The key to the success of using technology for digital transformation lies not in technical issues, but in concepts AI is not a magic pill that will take effect after taking it AI is more like a health food and must be taken continuously to help adjust the corporate body" This is Li Qihan realization He also mentioned that there is an 8020 rule in customer management How to define the 20 customer group What is the definition of VIP customer What issues does the company want to analyze What data should be disassembled It is necessary to peel off the cocoons layer by layer and clarify the above issues one by one This is the "basic project of the sewer" If the foundation is stable, there will be no problem in building a few more floors on top The Industrial Bureau of the Ministry of Economic Affairs’ AI problem-solving competition creates a win-win situation for enterprises and innovations Intelligent Interpretation has assisted the internationally renowned catering chain Din Tai Fung to participate in the AIGO "Problem Solving" competition of the Industrial Bureau of the Ministry of Economic Affairs It understands that almost all catering industries have problems with how much to prepare Many times, when there are too many guests, there is insufficient preparation There are fewer customers, resulting in a waste of ingredients Therefore, it is very important for restaurants to predict the number of customers every day Intelligent interpretation suggestions can be based on weather, store location, and special holidays such as Valentine's Day, Mother's Day, etc through AI , special time parents’ birthday, wedding anniversary and other data correlation analysis, the estimated number of guests is expected to increase the accuracy by more than 80, effectively using AI to solve the problems of catering operators Restaurant Consumer Service Flow Chart Li Qihan pointed out that "industry problem solving, new innovation problem solving" can help enterprises and AI startups find common goals, and also solve the dilemma of new startups not getting usable data, and provide identification through matchmaking on the enterprise side Based on the data, AI startups can put algorithms into practical application, and enterprises can also get solutions for digital transformation, creating a win-win situation After the epidemic, digital transformation is related to the life and death of enterprises How should the cateringretail industry choose AI companies and introduce them Li Qihan, who currently serves as an AIGO smart retail coach for the Industrial Bureau of the Ministry of Economic Affairs and a number of AI consultants, said frankly that if data analysis does not have a certain degree of understanding of AI and practical implementation experience, there may be a high chance of failure in project execution In the retail industry, when it comes to choosing an AI project company, it is best to choose a company that has actually introduced AI projects or has experience in operating e-commerce The recommended principles and steps for introducing AI into the cateringretail industry are If the problem the company asks is too big, it needs to continue to dismantle it Because different problems naturally require different ways of collecting data, with the help of consultants step by step After dismantling, use the data collected according to the usage situation to analyze, and you will naturally get the answer to the problem you want to solve After you find a certain accuracy, you can then use transfer learning to solve similar problems one by one Looking to the future, Intelligent Interpretation hopes to become the number one AI company in Taiwan in the catering and retail industries, using simple and practical methods to help the catering and retail industries implement AI and improve the competitiveness of Taiwan's industry「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」