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【2020 Solutions】 Focusing on Various Quantitative Analysis Techniques to Tackle Profound Challenges!

In today's digital age, both individuals and companies face challenges in writing copy and designing layouts when managing a brand online. What constitutes good design? The online world often gives a mysterious impression, and the WoodThought team has been focusing on studying various data sources for years, hoping to find the answers they seek.

Focused on data analysis for exploring and solving problems

WoodThought is a group of consultants specializing in data (Big Data & Deep Learning) and solving the essence of problems. The team utilizes various quantitative analysis techniques to challenge many of the profound issues found on the internet and strives to continually enhance the data analysis capabilities of both Taiwanese businesses and individuals. The application of this technology is extensive, including personalized navigation and recommendation systems on news platforms, eCommerce personalization for navigation, search, and recommendations, or strategy development, design, and backtesting in financial transactions. Moreover, WoodThought also offers data analysis courses like web scraping and data visualization in response to technological and current events, aiming to cooperate with both domestic and international enterprises to implement various data science solutions.

WoodThought is a group of consultants dedicated to data analysis, exploring and solving fundamental issues, utilizing various quantitative analysis techniques to challenge the many uncertainties of the internet.Image Source

Taking the simplest web design as an example, WoodThought believes that with the advancement of personalized tracking technology and the combination of A/B Testing experimental designs and testing techniques, professionals in all industries can now avoid relying on the so-called '20 years of marketing experience'. Instead of using inefficient and unpredictable methods, making use of data analysis enables even intuitive observations to have a basis, thereby capturing the sentiments of online users. Supported by adequate data evidence, incorrect decisions and directions can be corrected promptly before mistakes are made.

WoodThought showcased its proprietary 3D marking system at the recent AI HUB conference, which utilizes AI image recognition technology to help doctors quickly determine the condition of patients' lung nodules.

WoodThought 3D marking system abnormal image marking

The AI model will automatically learn from the markings, providing recommendations for future markings by doctors, allowing for early discovery and immediate treatment, resolving past difficulties of 3D image marking and the challenge of obtaining marking data.

The team developed a 3D marking system using AI image recognition technology, significantly enhancing the efficiency of medical diagnosis

The same AI data analysis technology, also applicable in the medical sector, was showcased by WoodThought at the recent AI HUB conference. This includes their own 3D marking system with features like Auto-Learning and Pre-Labeling. This system assists doctors in diagnosing lung nodules. As doctors complete the diagnosis and marking, the AI model will learn from it and provide future marking suggestions, enabling early discovery and immediate treatment, thereby greatly resolving the difficulties of 3D imaging marking and issues of data accessibility.

WoodThought image analysis technology and treatment integration interactive diagram

WoodThought aims to solve various personalized service demands through data analysis techniques and calls for everyone to go beyond mere imagination, interact personally with different types of data, and dig out the answers behind the problems.

Over the past two years, core members of the WoodThought team have actively assisted and guided ordinary users on various e-commerce and media platforms to establish correct views through introducing relevant technologies and services. This helps solve various personalized service demand issues and enhances the likelihood of matching products with customers. WoodThought encourages everyone to leave behind imaginary notions, to engage with data, and to uncover the answers behind the problems, while also experiencing the problems behind the answers. Given the rapid changes of the internet era, each rising wave brings different user needs and voices. WoodThought aims to help everyone solve problems quickly and efficiently using various data analysis techniques.

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

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【解決方案】小柿智檢 以「AOIAI」雙劍合璧,軟加硬體千錘百鍊 打通外觀瑕疵檢測任督二脈
Xiaoshi Intelligent Inspection uses the two swords of "AOI + AI" to combine software and hardware to open up the two channels of appearance defect detection and supervision.

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」

【解決方案】2秒鐘完成結帳動作 Viscovery AI影像辨識助攻智慧零售
Complete checkout in 1 second, Viscovery AI image recognition assists smart retail

Artificial intelligence AI has gradually changed the way various industries operate in recent years However, most of the work is still done by humans, with AI playing a supporting role This has led to emergence of the term "AI Copilot," which stands for "AI-driven tools or assistants" that aim to assist users in completing various tasks and improve productivity and efficiency The concept of AI Copilot comes from the role of "co-pilot" During flight, the co-pilot assists the main pilot in completing various tasks to ensure flight safety and efficiency In fact, there have been signs of various "machines" beginning to play the role of "copilot" in different fields since the Industrial Revolution, assisting humans in completing heavy physical and repetitive tasks, greatly improving factory production efficiency, and driving rapid economic development Following the advancement of computing equipment and breakthroughs in machine learning, deep learning, and image recognition technologies, the concept of AI Copilot has gradually taken shape The development of AI Copilot marks the transition from "machine-assisted to AI-assisted" Early robots could only complete preset repetitive tasks, but today's AI copilot can learn and adapt to new environments and tasks, and continuously optimize its performance in practical applications This transformation not only changes human-machine interactions, but also has a profound impact on various industries The application scope of AI copilot covers various industries, including finance, healthcare, manufacturing, education, retail, etc, and are everywhere to be seen Application of AI copilot in the retail industry AI image recognition checkout In the retail industry, the application of AI copilot has begun to show concrete results Take Viscovery's AI image recognition checkout system as an example This system is a type of AI copilot model that helps store clerks speed up checkout or assists consumers in simplifying the self-service checkout process The store clerk needs to scan the product barcodes one by one in the regular checkout method If a product does not have a barcode, such as bread and meals, the clerk needs to first visually confirm the items, and then input them into the POS checkout system one by one Based on actual measurements at a chain bakery, it takes 22 seconds for an experienced clerk from "visual recognition" to "entering product information of a plate of 6 items into the checkout system" New clerks may need even more time In addition, according to a Japanese bakery operator, it takes 1 to 2 months to train employees to become familiar with products Now with AI image recognition technology, store clerks let AI handle the "product recognition" step, and AI will play the role of copilot, quickly identifying items within 1 second, speeding up checkout to save 50 of checkout time, and optimizing customers'shopping experience The time cost of training employees to identify bread can also be effectively shortened Even for products with barcodes, AI can quickly identify multiple items in one second, which is more efficient than scanning barcodes one by one The self-checkout system "assisted" by AI image recognition allows consumers to successfully complete shopping without the help of store clerks, eliminating the trouble of swiping barcodes or searching for items on the screen, which improves the shopping experience In a time when store clerks are hard to hire due to labor shortage, this also helps stores reduce operating costs AI quickly identifies multiple checkout items in just one second Source of image Viscovery Recently, startups dedicated to developing AI image recognition checkout solutions have emerged in various countries The most lightweight solution currently known is in Taiwan It can be immediately used by installing a Viscovery lens and a tablet installed with Viscovery AI image recognition software at the checkout counter to connect to the store's existing POS checkout system There are various integration methods, including plug-and-play and API solutions integrated with the store's POS system Viscovery AI image recognition system can be painlessly integrated with the store's existing POS system Source of image Viscovery Example of AI image recognition checkout Currently, the Viscovery AI image recognition system is being used in bakery chains in Taiwan, Chinese noodle shops in Singapore, micromarkets in department stores in Sendai, Japan, and Japanese bakeries and cake shops Over 7 million transactions were completed through this AI system, which identified more than 40 million items These use cases demonstrate the extensive application of the Viscovery AI image recognition system in the retail industry In the future, the company will continue to explore the various possibilities of using Vision AI in retail and catering nbsp The Viscovery AI image recognition system is already being used in bakeries, cake shops, restaurants, and convenience stores in Japan, Singapore, and Taiwan Source of image Viscovery

這是一張圖片。 This is a picture.
AI Smart Health Prevention Plan

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」