Herji Ltd held an interactive teaching session with AI storybooks at the 'Taiwan Early Childhood Development and Remedial Association Taitung Office', allowing children, teachers, and parents to engage in immersive educational experiences AI-generated children's educational storybook materials AI Learning Platform In recent years, changes in the social structure of Taiwan, combined with experiences in hospital emergency departments, have often led us to overlook the depressive symptoms exhibited by adolescents, resulting in tragic incidents of self-harm or even suicide among children A significant part of children's depression stems from their academic performance, with parents worrying about their children's future competitiveness, thus placing a lot of pressure on children who perform poorly academically In a family with two children with the same genetic background and provided with the same resources for growth, we often find that the second child's academic performance is not up to par, with poor grades, an inability to concentrate in class, and even lacking the patience and perseverance to finish reading a comic book or playing a video game We have been exploring why these differences occur and discovered that these issues often arise from undiagnosed learning disabilities during early childhood Due to environmental factors, children with delayed learning abilities are often not acknowledged by over 80 of parents who are reluctant to seek treatment for their children, primarily fearing that their child will be labeled as delayed As a result, the child's learning ability is hindered from an early age, with their academic struggles increasing as they enter primary and secondary school, leading to greater academic lag, frustration from parents, struggles from the child, and increased family disputes If tutoring does not yield effective results, expenditure without achieving positive outcomes often leads to further family conflicts, creating a vicious cycle that accumulates a lot of negative emotions in children during their developmental process, which in turn affects various factors impacting their health In reality, the main reasons behind a child's poor academic performance, inability to learn, lack of interest in learning new things, or even developing health-impacting psychological conditions, actually stem from accumulated learning delays during early childhood The period before the age of six is considered the golden window for treating learning delays If these can be identified and addressed during this time, there is a chance that the child's learning abilities can be greatly improved10The industry's current pain points are as follows 1Lack of methodologies for assessing learning abilitiesLack of databases for sample comparisons in the market 2Traditional parental misconceptionsFear of labeling and treatment delays for mild to moderate cases 3Lack of therapeutic materials and toolsShortage of therapeutic storybooks and series courses This project will develop a national talent development support system, utilizing AI Technological development of a system for assessing children's learning abilities that supports parents in safeguarding their children's health from the start of learning ability testing, offering early detection and treatment In the future, all Taiwanese children, regardless of background, will be able to establish a healthy foundation in early childhood, growing up to become valuable assets for national development 2、 As proposed in this planAIApplications and explanations 'Child Language Ability'AI'Analysis Model' This model quantitatively analyzes 'the condition of children's use of Mandarin' when 'expressing an event' Scenario Preschool teachers guide children in narrating storybook contentAITools analyze the sentences used by children to describe storybook content, applying statistical algorithms for quantitative analysis Analysis indicators include 'sentence type' and 'lexical items' Analysis aspects include correctness of sentence structures, diversity of vocabulary, quantity of vocabulary used, and accuracy of vocabulary usage Application Comparative analysis between an individual child and peers' language abilities can offer more detailed language skills teaching by preschool teachers Techniques used Chinese word segmentation, Chinese POS tagging, Chinese syntactic rules analysis algorithm, and quantitative analysis algorithms Tools usedChinese word segmentation tools, POS tagging toolsChinese POS Tagging Tool 3、 Expected Industrial Value Establish a learning ability assessment and support system, through therapeutic storybooks and courses Collaborate with kindergartens to develop learning ability bases, preventing children from being stuck at the starting point Alongside parents, protect children's health starting with learning ability testing, backed by a robust database, allowing parents to identify early any delays in learning, helping children regain their learning abilities 4、 Expected Industrial Benefits Economic Benefit and Future Spread and Impetus By supporting children with delayed learning abilities, enhancing their learning prowess through this project, these children serve as the future of our nation and can thus significantly contribute to national talent development Furthermore, the purpose of establishing a learning ability development base is to help reunite children with their parents, increasing their interaction time, allowing the children to move beyond mere one-dimensional interactions 3C This facilitates two-way interactions between the child and parents, potentially impacting children who may have been otherwise delayed in developing their capabilities due to environmental factors 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-11-15」

On the machine tool production line, there are some slight differences in the first step of assembly Accumulated tolerances will cause the assembly work to be repeated, which is time-consuming and labor-intensive, resulting in shipment delays that will impact the company's reputation Narili Technology Company focuses on the field of smart manufacturing and provides various AI solutions It uses machine learning models to inherit the experience of old masters In the CNC processing machine assembly and casting process, it uses AI to analyze production line data, accurately adjust various data, and improve Production accuracy is 25 This AI production line data analysis system is called "Master 40" by Huang Changding, chairman of Naruili Technology It is the most evolved version of the master plus artificial intelligence It has been used in machine tool processing factories with remarkable results In addition, Nairi Technology used AI defect detection technology to participate in the 2021 AI Rookie Selection Competition of the Industrial Bureau of the Ministry of Economic Affairs, assisting AUO in advanced panel image defect detection, with an accuracy rate of 100, and won the award Assisted panel manufacturer AUO to solve problems with 100 accuracy in defect detectionHuang Changding further explained that during the production of general panels, edges and corners are There may be defects in the corners Although the defects are visible to the naked eye, AOI is often difficult to identify, causing the detection error rate to often exceed 30 Therefore, re-inspection must be carried out with manpower to improve the accuracy rate However, in response to the demand for a small number of diverse products and insufficient manpower, using AI detection is indeed a good method Nairui Technology, founded in 2018, has been able to win the favor of major panel manufacturers with its AI technology in just three years In fact, it has been honed in the field of CNC machine tools for a 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 significantly from 70 to 95Tang Guowei then said that the original size data set by Master during assembly All were recorded on paper After the information was written, it was stored in the warehouse and sealed No one studied the relationship between the dimensions Narili assists customers in designing the Fu 40 system Through the human-machine panel, the master can directly input the measured dimensions and related data during assembly After collecting data from different masters, AI algorithms are used to analyze the relationship between the data and create an AI model The AI model automatically notifies the operator what size to adjust to, and the quality inspection will definitely pass In this way, the yield rate will be improved It has increased significantly from 70 to more than 95 Narili Technology Company focuses on the field of smart manufacturing and provides various AI solutionsTang Guowei added, assembling the spindle of a CNC processing machine It took four hours In the first step, the machine made measurement errors, including vibration, temperature, speed, etc that were out of range It had to be dismantled and reinstalled, which took another four hours How to adjust after disassembly depends on the experience of the master At first, the master may have done the best assembly method based on experience, but the error rate was also 30, and the assembly took several days With the assistance of AI masters, the assembly time only takes half a day, and the yield rate reaches over 95, saving a lot of time and manpower "Use the AI model of machine learning to collect the experience of all the masters and provide it for AI learning The first step is digitalization, and the second step is knowledgeization This is the transformation of the enterprise "An important key", Huang Changding believes that Narili Technology is an important partner in the transformation of traditional manufacturing from automated production to digital transformation In addition, another industry that Naili Technology focuses on is the smart car dispatching system of the leading brand of elevator manufacturers The so-called car dispatch referring to the elevator car means that if there are more than two elevators, group management is required In the past, car dispatching was based on fixed rules If the elevator was closer to the requested car, that elevator would be automatically dispatched On the one hand, it did not take into account that dispatching a car if the elevator was called too many times might make other people wait longer The previous vehicle dispatching model did not take into account the usage characteristics of the building, resulting in a lot of waste For example, in an office building, there are peak hours in the morning, lunch break, and afternoon after work AI smart car dispatch can be flexibly adjusted according to off-peak and peak hours, increasing the efficiency of car dispatch, reducing waiting time, and reducing wasted electricity Introducing elevator smart dispatch to improve transportation efficiency and have environmental protection functionsHuang Changding added that just like the previous traffic lights at intersections, the system has already The number of seconds to stop and pass on highways, sub-trunks and small streets is programmed Smart traffic lights are now used to flexibly adjust waiting times to make road sections prone to congestion smoother Using AI to learn usage scenarios and introducing a smart dispatch system into elevators will improve transportation efficiency and make it more environmentally friendly In addition to introducing smart elevator dispatching, Nairili also introduced AI into the smart production and shipment scheduling system of elevator factories Elevator factories often cannot accurately estimate the customer's elevator delivery date For example, office buildings or stores must be completed to a certain extent before the elevator can be installed on the construction site If 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 incorporates various calculation methods such as traditional image processing technology and statistics Only by being very familiar with the domain knowledge can we make good products AI models are also where the company’s competitiveness lies He emphasized that the data that general SaaS platforms can process is very limited, and the accuracy rate has increased from 70 to 75 at most Naili’s strength lies in AI algorithms and machine learning, and it must be coupled with in-depth industry knowledge to produce output Good AI model Narili Technology started with the AI project, gradually deepened the technology, chose to start with the more difficult tasks, and accumulated rules of thumb It is expected to develop SaaS services this year 2022, based on customer needs starting point, gradually gaining a foothold and becoming an important partner in smart manufacturing The picture left shows the general manager of Naruili Technology Tang Guowei and Chairman Huang Changding right「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

Quality inspection, like a double-edged sword, has always been a favorite and painful subject for Taiwanese manufacturers When AI deep learning enters the industrial visual inspection of traditional manufacturing industries, it can not only save inspection manpower investment, solve the problem of inconsistent manual visual standards, overcome the limited visual recognition and defect detection blind spots of traditional automatic optical inspection AOI, and also enable real-time traceability Causes of quality problems The overall AIAOI visual inspection solution developed by Xiaoshi Intelligent Inspection integrates software and hardware to create efficient appearance defect detection capabilities, helping electronics OEM customers create high-efficiency products with a miss detection rate of less than 1 and an overkill rate of less than 3 Check the level Xiaoshi Intelligent Inspection was established in 2020 Although it is a new venture two years ago, it did not start from scratch Founder and CEO Hong Peijun and the core team have been deeply involved in Foxconn factories for many years and participated in countless smart factory-related solutions and process improvements , has profound AI deep learning development capabilities, and accumulated rich experience in world-class AI application implementation Seeing that AI industrial inspection must be the last mile for the manufacturing industry to move towards Industry 40, Hong Peijun resolutely decided to implement AI deep learning technology in the field of smart manufacturing with high output value, and specialized in the development of AI industrial visual inspection For the manufacturing industry, product inspection is the most important part of all quality control, but traditional industrial inspection faces two major pain points 1 Manual visual inspection Today, more than 95 of the entire manufacturing industry still relies on manual visual inspection Inspection makes it difficult for manual visual quality inspection standards to be consistent, and visual inspection of fine objects, such as passive components or highly reflective components, will cause long-term vision damage 2 Traditional AOI automatic optical inspection The product has limited visual recognition capabilities and blind spots in defect detection Among them, the detection of appearance defects such as scratches, oil stains, dirt or hair and other unexpected subtle defects has always been a problem in AOI applications Insurmountable difficulties AIAOI visual inspection overall solution is a great boon for appearance defect detection When designing the product roadmap of Xiaoshi Zhikan, customer group positioning and strengthening customer product services and value were important indicators Moreover, appearance defect detection has always been an unresolved pain in the manufacturing industry, Hong Peijun said With industrial quality inspection AI software as the core, Xiaoshi Intelligent Inspection provides an overall solution for AIAOI visual inspection It mainly promotes three major products, including "QVI-T AI deep learning inspection modeling platform software" and "AI six-sided defect inspection and screening machine" ” and “AI Industrial Quality Inspection Platform” The main customer groups served are semiconductor packaging and testing, EMS electronics foundry, small metal parts processing and other industries with high production capacity and high gross profit margin In response to customer needs, Xiaoshi Intelligent Inspection provides corresponding software and hardware services, combining self-developed AI deep learning software and hardware quality inspection equipment to reduce the manual visual burden on the production line and effectively improve the production quality of the factory In order to help equipment manufacturers and technical engineers with development capabilities accurately grasp product appearance defect detection, Xiaoshi Intelligent Inspection independently developed QVI-T deep learning detection software, which can provide customers with defect location, defect classification, defect segmentation, anomaly detection and text recognition Key functions such as this are different from the fixed detection methods of traditional software Algorithms can be refined based on different industrial detection methods and different APIs can be developed to connect devices with different lenses The software design of this platform is very lightweight It is a SaaS software built on public cloudprivate cloud It mainly involves simple image uploading, labeling, training modeling, and verification testing After completion, users can download models, SDKs, APIs, and reports Effectively help customers achieve AI inference functions Currently, most of the industrial inspection services on the market are traditional AOI software industrial inspection machines, which can only measure product contours such as the head and length of fasteners, etc, and cannot truly provide detection of subtle product surface defects such as screw head cracks and tooth damage There is a lack of such high-precision defect detection companies in the market, Hong Peijun observed Xiaoshi Intelligent Inspection developed and independently built the "AI six-sided defect detection and screening machine" from customized services in the past to providing standardized services for customers at the current stage It provides standardized testing services for fasteners in measurement and surface defects, as well as passive components High-speed surface defect detection of similar products This professional machine uses the AI deep learning AOI composite algorithm technology independently developed by Xiaoshi Intelligent Inspection Through parallel computing technology, it can achieve model inference up to 3 milliseconds per picture, and realize multiple complex defect detection on the electrodes and body of passive components This professional machine is mainly used for the inspection of fasteners, small metal parts and passive components In terms of competitiveness in the industry, the software hardware integration provided by the AI six-sided defect inspection and screening professional machine is an important core competitive advantage of Xiaoshi Intelligent Inspection It is not as simple as it sounds Hong Peijun said with emotion that this special machine is very important in the industrial inspection industry Commonly known as the highly integrated integration of optical mechanisms, electronic controls, software and algorithms, the process requires continuous optimization and iteration, and requires multiple client verifications and modifications After a long period of hard work, the technical threshold has also been raised The AI six-sided defect detection and screening professional machine will be the main product promotion direction of Xiaoshi Intelligent Inspection in the next 3-5 years It is believed that AI combined with measurement technology and surface defect detection will be an important source of core competitiveness of Xiaoshi Intelligent Inspection, Hong Peijun said AI six-sided defect detection and screening professional machine will be the main product promotion direction of Xiaoshi Intelligent Inspection in the next 3-5 years Faced with the booming development of Industry 40 in smart factories, customers often ask "Does quality inspection data have secondary use value" Hong Peijun said that the "AI Industrial Quality Inspection Platform" launched by Xiaoshi Intelligent Inspection has a machine learning mechanism , which can be used for secondary use of quality inspection data to provide customers with multiple functions including real-time monitoring and early warning of production quality, quality traceability analysis, quality factor assessment, process parameter prediction and recommendation Taking the successful introduction into the automotive parts factory as an example, through the prediction and recommendation of process parameters provided by the AI industrial quality inspection platform, when we know the product defects, we build a set of models based on the experience of past masters, coupled with the network connection data from the previous stage, After integration, we have process data, incoming material data, and quality inspection data We can predict whether these machine parameters have run out, and we can recommend whether the process parameters of certain sections should be adjusted up or down Through the AI industrial quality inspection platform, Xiaoshi Intelligent Inspection can help customers connect visual quality inspection results, process data and acceptance standards with the existing MES system of the customer's factory to improve production quality, improve efficiency and reduce costs In terms of business model, Xiaoshi Zhiqian also provides a software subscription system for the deep learning detection modeling platform software It provides public cloud customers with traffic subscription and charges based on the amount of image uploads, while private cloud customers adopt an annual license fee license charging mechanism In addition, the company also provides customers with a buyout charging mechanism for the overall solution equipment, and provides a one-year warranty, after which consumables and software update maintenance fees are charged annually Going in the opposite direction, using both hard and soft methods, with a missed detection rate of less than 1 and rapid modeling in 15 minutes Faced with various small-volume and multi-sample inspection needs in the manufacturing industry, general AI deep learning visual inspection usually requires customers to collect a large number of photos of defective products, which is time-consuming to label, and also causes customers to have difficulty in importing AI, and defective products cannot be collected The introduction cycle is long and implementation is full of risks If there are not enough bad samples, the model will be inaccurate Kosaki Chikan goes in the opposite direction and uses its product "AI Visual Inspection Model Development Tool" to train models through pictures of good products provided by customers It is relatively easy for AI to learn good products, no labeling is required, and the time can be quickly compressed to complete the modeling Take the implementation of IPC electronics industry - AAEON Technology as an example In order to reduce the manpower input of the quality inspection station in the PCBA production line and have standardized quality inspection, Xiaoshi Intelligent Inspection provides an overall solution for PCBA AI visual inspection software and hardware services, and conduct in-line inspection on the factory's highly automated assembly line, effectively saving inspection manpower investment, improving the standardization of quality inspection rates, and improving the problem of inconsistent standards caused by manual visual inspection Through the introduction of AI visual inspection software and hardware integrated solutions, we have effectively helped customers maintain an overkill rate of less than 3 in the past two years, and achieved high-efficiency performance with a missed detection rate of less than 1 In addition, this solution allows practitioners who do not understand AI to quickly operate modeling By installing the modeling tool on the device, when the customer has a new product number and needs to create a model, he only needs to provide 10 pictures of good products to scan under the device It only takes 15 minutes to quickly train the model In terms of product core strategic layout, compared with market competitors who rely solely on general software services to seize all manufacturing markets, it is not feasible to apply it to industrial inspection Hong Peijun has observed over the past 10 years and believes that only software hardware can With technical thresholds and focusing on one industry and field, only by adopting a standardized company's AI six-sided defect detection and screening special machine can it be replicated and scaled up, and the company can truly continue to move towards optimization and create product competitiveness, even if there are other competing products It’s not easy to compete for this pie, Hong Peijun said Xiaoshi Intelligent Inspection’s overall AIAOI visual inspection solution creates rapid modeling and excellent results for customers with a missed detection rate of less than 1 The most competitive AIAOI overall solution provider with global presence For new entrepreneurs, facing business expansion is a challenge every day Hong Peijun said that small companies are easily snatched away by large companies, company talents are poached by high salaries, lack of deep customer relationships, and the business team is not large enough, etc How to overcome this Hong Peijun believes that the key to success and competitiveness of a new start-up company is to be diligent in making up for mistakes, provide better services, provide more immediate feedback, and create more professional solutions to convince customers Since its establishment in 2020, Xiaoshi Intelligent Inspection has always gone against the grain in terms of product core strategic layout, surpassing the competitive market among its peers, and actively taking root in the overall solution of AI visual inspection software and hardware Hong Peijun hopes that Xiaoshi Intelligent Inspection will become the world's most competitive AIAOI overall solution provider for the electronics and semiconductor industries in the future, and provide the top AIAOI professional machines and equipment to the electronics and semiconductor industry customer base Hong Peijun said that the technical capabilities of the company's AI six-sided defect detection and screening professional machine have reached the top domestic level In order to speed up the research and development of professional machines to become more standardized and sell them to overseas markets, the company will conduct a fundraising plan at this stage, hoping to use legal persons such as the Capital Strategy Council to assist in more business connections and fundraising channels For the medium and long-term goals, Xiaoshi Intelligent Inspection will lay out the global market including mainland China and Southeast Asian countries At the same time, it will follow the international footsteps of major OEMs in global layout Under the target inspection project, it will continue to develop specialty products and spread towards the international field 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」