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

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」

【解決方案】光禾感知科技智慧球場體驗 AR互動讓看球變得更加有趣
OSENSE Technology Qubby AI customer service helps enterprises comprehensively upgrade from customer service to knowledge management

"What are your business hours" "What are the functions and features of the product" "What discounts are available now" "Does the product have a warranty" "Does the manufacturer cooperate with the product for repair" From the perspective of consumers, every inquiry is a unique customer experience, but from the perspective of companies, 90 or more of these questions are repeatedly asked every day OSENSE Technology's Qubby AI customer service can help companies seize the opportunity to continue to provide high-quality customer services every time they come in contact with customers, and optimize service processes through AI to create an efficient service team Taiwanrsquos first IMSNS virtual human real-time interactive voice AI customer service Qubby AI The information age has caused changes in consumer behavior Companies have deployed online and offline platforms, such as official website apps for their brands, physical stores, distribution channels, and third-party e-commerce, to increase channels for contact with consumers However, this has created a greater workload for customer service personnel, who need to monitor even more channels to provide timely services OSENSE Technology's Qubby AI customer service helps enterprises integrate and manage multiple platforms, such as websites, LINE, Facebook Messenger, WhatsApp, and multimedia interactive machines, with a single account The service supports 29 languages and serves domestic and overseas customers 247, building good relationships by meeting customer needs and creating an endless stream of important and valuable customers Qubby AI customer service features Saves training time, standardized AI response, supports IMSNS, improves customer service efficiency, optimizes the service experience, and the web page is applicable everywhere Efficiently create enterprise-specific AI customer service in 3 steps, eliminating the need for design QA OSENSE Technology has condensed the establishment of Qubby AI customer service into three steps based on its years of experience with domestic and overseas projects and strong technical capabilities, so as to help enterprises build efficient teams The first step is to create an image and personify the corporate image Upload a profile photo, create a realistic or anime-style 3D virtual person, or customize a real person image, transforming the one-way corporate communication model in the past into a two-way interactive service model It not only improves brand favorability among customers, but is also an indispensable part of creating warm services The second step is to select the voice Qubby AI customer service can interact with customers through text, preset QampA, and voice For voice, users can choose the system's preset AI voice, or use AI to clone a real person's voice It supports the conversion of 29 languages, and is like customer service personnel providing services in person, increasing customersrsquo trust in the brand The third step is to 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Taiwanrsquos market, OSENSE Technology is actively expanding into international markets, such as the United States, Japan, and Southeast Asia In January 2024, it has signed a contract with the largest clinic management system developer in Southeast Asia to bring Qubby AI customer service southward, hoping to provide comprehensive AI digital services and solutions to medical institutions and people ofnbsp Southeast Asia, creating better healthcare experiences and expanding the smart healthcare ecosystem AI is ushering in a new industrial revolution According to Gartnerrsquos estimates, there are approximately 17 million customer service personnel working in customer service centers around the world 95 of the cost of a customer service center is from personnel Even if 10 of the service volume is automated, tens of billions of US dollars can be saved every year Based on the 2023 Taiwan Industrial AI Survey released by the Artificial Intelligence Foundation, nearly half of Taiwanrsquos 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【解決方案】AI電眼取代人眼 慧演智能運用AI幫製造業做品管
Using AI vision to replace human vision, Claireye Intelligence uses AI to help the manufacturing industry with quality control

In response to customer demand on a wide variety of products in small quantities in the manufacturing industry, there is an urgent need to find AI solutions from the cloud to terminals Claireye Intelligence provides a solution that integrates software and hardware - BailAI image inspection solution to assist traditional manufacturing industries in improving process efficiency and product quality, thereby achieving the initial goal of transformation After the government declared 2017 to be Taiwan's "First Year of AI," AI startups have sprung up in Taiwan Established in 2018, Claireye Intelligence targets smart manufacturing and provides a platform for AI image analysis and process optimization, using the power of deep learning to detect product defects and abnormalities in the assembly process It assists companies in building infrastructure from terminals to the cloud, which enables automated monitoring of factory production to improve process efficiency and quality Focusing on AI image inspection based on its familiarity with the production line quality control process Shirley Liu, founder and CEO of Claireye Intelligence, is a young entrepreneur She entered the manufacturing industry after graduating from college and held a quality control position in the plastic injection process of hard disk parts "She was already on the production line at the time, and is familiar with the production line process of production machinery" She later switched career paths to marketing and planning, and then worked as an AI product manager When the time came, Shirley Liu decided to start a business, focusing on AI image recognition in the manufacturing industry "The difficulty for enterprises is the lack of an AI development team Even if an enterprise has an AI team, development projects will take a lot of time, at least 6-12 months" said Shirley Liu, who is well versed in the market's pain points The problem that needs to be solved by platforms is to provide services that allow traditional manufacturing industries to build their own AI models without needing employees with a programming background, and to remotely assist production lines with troubleshooting and subsequent system maintenance, helping companies save development time and labor costs BailAI image inspection platform usage scenarios Facing the large number of competitors that provide AI image recognition in the market, what are the technical advantages of Claireye Intelligence Shirley Liu said that many companies currently have AOI equipment, but the bottleneck in the application of AOI is that it can only be used for defect inspection in fast production of large quantities, and parameters need to be adjusted after each inspection or production Based on her understanding of the industry, most SMEs are limited by their financial resources due to AOI equipment often costing over NT1 million, but they also want to use automated inspection This is where Claireye Intelligence comes in Shirley Liu went on to say that it is impossible for traditional manufacturing industries to maintain a technical team that includes AI engineers, data engineers, cloud architects, and terminal architects Claireye Intelligence specializes in software and hardware integration Enterprises can use the BailAI image inspection platform to easily solve inspection problems on the production line In other words, customers only need to provide images or samples for Claireye Intelligence to carry out model training, model deployment, and system integration, and they can easily use AI technology to optimize and monitor production line processes Participated in the AI New Talent Selection and achieved a recognition rate of over 90 in assembly behavioral image recognition For example, a certain connector manufacturer only has 1-2 AI engineers in its technical team The main problem that needs to be solved is that most operators are on the production line, while quality control and senior managers are not on site, and the company wants to understand the actual situation of the production line through remote monitoring Claireye Intelligence uses industrial cameras to capture production line images, and transmits AI image analysis to the remote end Supervisors and quality control personnel can observe if there are any errors in the production line assembly, such as whether the connectors and lines are connected properly, through the monitor Claireye Intelligence's AI image inspection operates on Microsoft's Azure cloud platform, and also utilizes terminal equipment, such as NVIDIA's edge computing equipment placed around the inspection station, to assist traditional manufacturing industries with improving production line efficiency and detecting problems early through an integrated solution from the cloud to terminals Claireye Intelligencersquos customers currently include aviation, electronic peripherals, connectors, and metal industries Assembly process solution for human behavior recognition in assembly lines achieves an accuracy of over 90 In order to demonstrate the depth of technology, Claireye Intelligence participated in the 2021 AI New Talents Selection of the Industrial Development Bureau, Ministry of Economic Affairs, and provided Lite-On Technology with the "assembly process solution for human behavior recognition in assembly lines" The solution determines effective working hours and ineffective working hours of operators on the production line through cameras and AI image recognition It recognizes hand posture and position through images to determine the operator's assembly behavior, achieving an accuracy of over 90 Shirley Liu added that the assembly process of electronic components is complex, mostly carried out manually, and cannot be replaced by robotic arms Claireye Intelligence used cameras to film the assembly process of operators at Lite-On's assembly station The algorithm is then trained and corrected based on the video, and the final trained model can directly determine whether there are any errors in the assembly process to improve the overall process Project development time is expected to be shortened to 1 month by using the BailAI image inspection platform Since its establishment more than three years ago, Claireye Intelligence has accumulated a considerable amount of project experience and hopes to commercialize the project experience Shirley Liu pointed out that the trial version of BailAI image inspection will be completed this year 2022 Customers can choose industrial cameras or video cameras based on the detail of the object being inspected It can even use X-rays to capture images, and then the images are automatically marked by the platform Claireye Intelligence will provide customers with AI application models suitable for the field Inferences can also be made in the cloud or terminals for launch in the manufacturing industry The metals industry, metal casings of industrial computers, connectors, electronic peripherals, and mechanical parts can all use the platform for defect detection and object identification Claireye Intelligence will continue to improve its technical capabilities, accumulate customer experience to complete commercialization, and also accelerate the implementation of AI inspection applications In the mid-term, it will build terminal and cloud infrastructure and shorten the development time of enterprise AI projects from 6-12 months to 1 month, reducing usage time and lowering the threshold for enterprises The long-term goal is to target the Southeast Asian market where Taiwanese businesses are gathered, expand software and hardware integrated AI solutions to overseas markets, and expand the scale of operations