Special Cases

11
2020.8
【2020 Application Example】 "AI Color Recognition and Cost Optimization Control System" automatically recognizes colors, breaks through the traditional color grading model, significantly reduces costs, and improves yield!

Mixing new colors relies on the experience of master craftsmen The so-called "computer color matching" in the paint industry is simply the selection of "existing colors" for mixing, but there is actually no way to mix paint for a ldquonew colorrdquo and it all relies on the experience of master craftsmen Hence, it is necessary to start from scratch when a new color is encountered, which consumes a lot of manpower and time Moreover, due to the different color mixing habits of each master craftsman, the cost can be significantly different despite producing the same result The trilogy when paint factories face the crises of transformation I Lack of color mixing standards Generally, when traditional paint factories produce new colors, they will use a "spectrophotometer" to measure the LAB value of the sample color, and then the paint mixer will mix the paint of that color based on past experience After color mixing is completed, the instrument will be used to test the LAB value and C and H wavelength This process does not have a complete system and database records, and there are not standards for color mixing II Production costs are difficult to control Paint factories produce many pigments with different materials and functions, and the cost of paint will vary depending on the "color masterbatch material" used Even if the color number of the masterpiece is the same, the cost will be different if the ratio of the color masterbatch is different Paint mixers do not have a set of color mixing standards when mixing paint, making it difficult to control production costs III The color grading process is lengthy and personnel training is difficult As instruments cannot replace manual color mixing, the training of a paint mixer requires years of experience in paint mixing, familiarity with chromatology, as well as basic understanding of hue, saturation, and brightness If there is no basic reference color values when mixing paint, the paint mixer must spend a lot of time repeatedly mixing colors, resulting in a loss from time cost Developing an "AI Color Recognition and Cost Optimization Control System" The paint factory engaged in industry-academia collaboration with the Department of Computer Science amp Information Engineering of Chaoyang University of Technology through CDIT Information Co Ltd, and utilized the university's AI research capabilities to jointly develop the "AI Color Identification and Cost Optimization Control System" It established a database of "paint color numbers" and "color masterbatch material cost," and analyzes the optimal color mixing and optimal cost formula through data mining methods The paint mixer can refer to the formula analyzed by the system for color mixing, and then input the formula into the system after paint mixing is completed The formula is fed back to the basic database and an "artificial neural network model" is used by the system for deep learning, establishing a color grading standardization system for cost control and data collection, so as to solve the current difficulties faced by paint factories In the early stages of system development, CDIT planned the system requirements of the paint factory, established the system architecture and system database, and then worked with Chaoyang University of Technology on the implementation of model functions for the application of data mining and artificial neural network After the system is completed, CDIT will assist the paint factory in system testing and correction The system will be introduced after correction and testing are completed, and training on system use will be provided to ensure the correct use of the system System Screen Differences before and after using the system Expand new markets for the paint industry to see the paint industry thrive The "AI Color Recognition and Cost Optimization Control System" collects the color mixing formulas of paint mixers, establishes a paint color masterbatch formula database, and records the cost of each color number The system's deep learning function is then used with a spectrophotometer to analyze the optimal color mixing formula for each data entry, so that the paint factory can control the cost of paint mixing The optimal color mixing formula recommended by the system increases the speed of paint mixing and increases output value Future benefits include The improvement in product yield reduces customer complaints and improves customer satisfaction The breakthrough in the traditional color mixing model improves corporate image Improves the efficiency of paint mixing, and allows the remaining time to be invested in training to enhance the professional capabilities of personnel It will also allow the joint expansion of new markets with the paint industry and learning of new application technologies, and promote them to other paint companies, enhancing the industry's overall competitiveness to see the paint industry thrive

2020-08-11
【2022 Application Example】 Even the United Nations is on board! Yoyo Data Application captures global business opportunities with agricultural data

Nearly 2,000 days in the fields have made Yoyo Data Application a top player in Taiwan’s agricultural data sector Their comprehensive grasp of crop yields, production periods, and prices has enabled them to collaborate with the United Nations The service area for agricultural land skyrocketed from 24 hectares to over 6,000 hectares in less than three years—a 250-fold increase For Wu Junxiao, founder and CEO of Yoyo Data Application, aligning with global environmental trends and becoming a data company at the intersection of climate technology and the green economy to serve the global market is his ultimate entrepreneurial goal Wu Junxiao, originally an engineer, joined the Industrial Technology Research Institute in 2010, where he honed his profound technical and data science analytic skills 'At that time, I was working in data analysis engineering, and almost all data-related materials would be directed to me Additionally, I worked on indoor cultivation boxes, planting vegetables and mushrooms, hence planting the seed of entrepreneurship by integrating agriculture with data analysis,' Wu recalls Since 2016, Wu Junxiao has been frequently visiting farms to 'embed' himself among farmers and agricultural researchers, chatting and sharing information systematically, which quickly established his agricultural know-how Solid data analysis capabilities have even convinced the United Nations In 2017, he left the Institute to start his own business and founded Yoyo Data Application in 2019 Today, many agricultural businesses are his clients, with service areas rapidly climbing from 24 hectares to over 6,000 hectares, expected to surpass 7,000 hectares in 2022 His clientele includes markets in Japan, Central America, and even entities under the United Nations like the World Farmers Organization, which utilizes the 'Yoyo Crop Algorithm System' supported by Yoyo Data How exactly does Yoyo Data Application manage to impress even UN agencies The 'Yoyo Crop Algorithm System' developed by Yoyo Data Application accurately predicts the production period, yield, and prices Firstly, due to Wu Junxiao's precise mastery over agricultural data, Yoyo Data Application's clients don't necessarily need sensors or other hardware devices 'Sensors are expensive and if you buy cheap devices, you just collect a lot of noise or flawed data, which is useless,' Wu explains He continues, 'Collecting data doesn't necessarily require sensors our data solutions can solve problems more directly and effectively' For instance, one of Yoyo Data Application's products, the Yoyo Money Report Agri-price Linebot, developed in collaboration with LINE in 2020, gathers data on origin, wholesale, and terminal prices spanning over 10 years, driven by Yoyo Data’s proprietary AI algorithms This enables the system to autonomously learn about agricultural product trading prices, using big data and AI to perform price prediction analysis, thereby helping buyers reduce transaction risks and expanding the data application to the entire agricultural supply chain Regarding banana prices, the accuracy of price predictions increased from the original 70 to 998 Wu Junxiao notes that both buyers and farmers are very sensitive to prices Now, through the Yoyo Money Report service, both buyers and farmers can precisely understand the fluctuations in agricultural product prices Yoyo Data can also provide customers with optimal decision-making advice based on predictive models for crop growth, yield, and price estimations Currently, price predictions cover 28 types of crops Precise estimates of production periods and price fluctuations allow Yoyo Data to provide differentiated services based on data analysis The 'Yoyo Crop Algorithm System' provided by Yoyo Data Application incorporates a 'Parameter Bank', usually collecting 200-300 parameters, not just straightforward data like temperature and humidity, but also data divided according to the physiological characteristics of the crops Through effective dynamic data algorithms, it can accurately calculate when crops will flower and when they can be harvested, what the yield will be, and so forth For instance, the prediction accuracy of the broccoli production period is 0-4 days, with the flowering period predicted this year to be precisely 0 days, perfectly matching the actual flowering time in the field In these dynamic calculations, a 7-day range is considered reasonable, and the average error value of Yoyo Data's predictions typically ranges from 2-4 days, with most crop production period accuracies above 80 Through effective dynamic data algorithms, over 120 global crops can have their production periods and yields accurately estimated Using these effective dynamic data algorithms can set estimates for production quantities, helping adjust at the production end Yoyo Data Application's clientele primarily includes exporters of fruit crops like pineapples, bananas, guavas, mangos, pomelos, sugar apples, Taiwan's agricultural production is highly homogenized, often leading to a rush to plant the same crops and resulting in price crashes Yoyo Data Application helps clients differentiate their offerings Thus, Wu Junxiao positions his company as a boutique digital consultant, carefully selecting clients for quality over quantity He notes that Taiwanese agricultural clients focus on how to improve yield rates, even categorizing yield rates by quality, aiming for high-quality, specialized export markets whereas international clients prioritize maximizing per-unit yields, showing different operational approaches in domestic and international markets In addition to agricultural fruit, Yoyo Data Application has also extended its services to the fisheries sector, including species like milkfish, sea bass, and white shrimp, all using the same system to establish various parameters related to the growth of fish and shrimp, such as when to feed and when to harvest, and the anticipated yield, timing, and prices Yoyo Data Application harnesses the power of data to create miracles in smart agriculture In response to the company's rapid development, Yoyo Data Application introduced venture capital funds in 2021 to expand its staff and promote its business Wu Junxiao states that in response to the global trend towards net zero carbon emissions by 2050, he plans to help clients plant carbon in the soil, effectively retaining carbon in the land while also connecting clients to carbon trading platforms, creating environmental business opportunities together Wu Junxiao says that from the start of his entrepreneurial journey, he positioned the company as a global entity, thus continuous international collaborations are planned As a data company serving a global clientele and focused on climate technology and the green economy, this represents Wu’s expectations for himself and his company's long-term goals Yoyo Data Application founder and CEO Wu Junxiao「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

2022-03-14
【2020 Application Example】 Peeking into a Baozi to See How AI Reduces Scrap Rates by 50% and Boosts Production Efficiency by 60% for Frozen Foods

From production line to dining table, who oversees the hygiene management of what we eat In recent years, there has been a continuous stream of news reports concerning food safety, such as repackaging expired goods, and poisoning incidents at Hong Rui Zhen It's clear that people are increasingly concerned about the hygiene of their food However, due to various quality control methods in food processing, there are inherent risks The World Health Organization WHO has pointed out that unsafe food and water cause physical harm to 2 million people each year Hence, international markets demand that food processing companies must establish a traceability system for products This is why major domestic food processors also aim to set up a production traceability system to quickly trace back to problematic raw materials and initiate recall and destruction of problematic food Visible assurance, implementing production transparency A major domestic food manufacturer producing frozen food and instant meals has expanded its market presence to North America, New Zealand, Japan, etc They are also at the forefront in promoting food management domestically, having obtained certifications such as HACCP, ISO22000, ISO14001 Since food production is labor-intensive, it is prone to quality impacts caused by worker fatigue Additionally, the production lines often have unclear records of production quantities, processes, and timing This obscurity in traceability makes it difficult to track production information when defects occur, leading to food safety management gaps that result in the scrapping of entire batches To address this, the Production Development Center at National Sun Yat-sen University utilized its advisory resources to help the food manufacturer tackle food safety management challenges, planning the use of AI technology to collect production data and establish anti-fraud and traceability for food production Intelligent manufacturing boosts food safety Although the level of automation is not high in the processing of bakery products, the food plant in this case is keen to enhance the automation of its production lines and introduce smart manufacturing For businesses, a traceability system not only helps establish brand image and increase product and brand value, but also gives consumers peace of mind due to the transparency of production lines Therefore, the Production Development Center at National Sun Yat-sen University matched AI technology service providers, Hong Ge Technology, in the first phase to plan the introduction of data collection devices to link food work orders information, reducing human operational omissions and capturing real-time production information through dashboards to ensure the consistency of production stage information potentially affected by human factors Schematic for intelligent production line planning The second phase involves using deep learning during the dough fermentation stage to calculate size and volume, analyze the relationship between temperature, humidity, fermentation time, and product volume, and assess whether to introduce AOI foreign object detection after freezing as a second quality control step Schematic of AI-integrated quality control for finished products Food processing ID card, launching the AI-era of food safety tracing In Taiwan, the understanding and acceptance of production history by consumers is gradually improving From the supply of raw materials, processing, production, to distribution and sales, it is necessary to have complete control and provide transparent information Publicly disclosing the production history not only increases trust between enterprises and consumers, but also aligns Taiwan's food safety environment with international standards In 2020, the Production Development Center at National Sun Yat-sen University will assist enterprises with the adoption of advanced AI technology, documenting the entire data process from industry to dining table and supervising food production processes to successfully implement product tracing, prevention of adulteration, and the establishment of high standards for products, thus advancing food processing products to international standards「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

2020-03-12
【2021 Application Example】 Advancing to Smart Logistics 5.0: Hsinchu Logistics Delivers Medical Materials with Ultra-High Efficiency

After incorporating AI technology, traditional logistics companies have seen significant improvements in transportation efficiency and reductions in transportation costs, especially in the transfer of medical materials which involves timely service and rights of hospitals and patients The implementation of intelligent logistics can save medical material businesses the cost of constructing GDP warehouses and other expenses up to millions A major domestic logistics leader, Hsinchu Transport HCT, owns a fleet of 3,500 vehicles and a storage area of 60,000 square meters, providing customized logistics solutions including logistics, commerce, finance, information, distribution, storage, and processing The company handles up to 580,000 parcels per day, with a maximum capacity reaching 900,000 parcels, making the enhancement of transshipment efficiency crucial for HCT Medical materials transportation at hospitals need optimization of current operational processes and enhancements in systematization and intelligence Especially the transportation of hospital medical materials, which encounters various challenges Medical materials suppliers need to cater to varying customer product demands, temperature requirements, and delivery times through multiple logistics providers This highly depends on the experience and careful control of operations staff Whether it is the product shipment or actual logistics process, each step must be interconnected Any human errors can impact the service timing and rights of the hospitals and patients Thus, all concerned businesses, along with the government and hospitals, are working to optimize current operational processes and elevate the level of systematization, automation, and intelligence to minimize service errors and cost losses HCT's distribution process prior to AI implementation Currently, with the government's push for standardized platform operations on the demand side of hospitals, supply-side businesses collaborate through data coordination to improve the accuracy and efficiency of product shipments, enhancing operational quality and management benefits at the demand side At the same time, some businesses are also investing in the standardization and systematization of internal operational processes, thus enhancing operational efficiency and quality In the freight logistics sector, logistics companies' warehouse staff need to expend labor to control different logistics shipment operations If they often receive emergency task notifications for shipments to medical facilities, they usually depend on small regional logistics providers to provide customized delivery services Although this improves delivery times, it does not allow for integrated informational services The new GDP regulations for medical materials require suppliers to undergo GDP compliance certification Therefore, Hsinchu Transport, assisted by the Ministry of Economic Affairs' AI coaching program, not only extends existing logistics services compliant with GDP regulations but will also use data integration and optimized AI technologies to help medical material businesses streamline and improve their logistics operations Complex logistics issues are solved using the Simulated Annealing SA algorithm To meet the 'Good Distribution Practices for Medical Devices,' Hsinchu Transport is not only actively introducing new logistics vehicles but will also implement artificial intelligence-based mathematical optimization technologies to assist in intelligent scheduling at nationwide business points and transshipment stations They aim to optimize the routing of medical materials between business points or regions thereby enhancing efficiency in the distribution process Currently, during the transshipment process of medical materials at Hsinchu Transport, detachable tractor heads and containers are used Each business point and transshipment station differ in location design and staffing, impacting the throughput per unit of time Furthermore, daily cargo conditions size, destination vary, and due to these fluctuating and distinct demands, the deployment of tractor heads and containers changes accordingly Under these circumstances, Hsinchu Transport relies on past experiences to schedule departures at each satellite depot and adjusts daily according to the cargo needs Due to the reliance on empirical scheduling, it is often difficult to consider all variables and considerations, leaving room for improvement in the current departure schedules The cargo delivery planning inherently constitutes an NP-Hard problem, difficult to solve with traditional analytical methods Hsinchu Transport, in collaboration with Singular Infinity, utilizes the Simulated Annealing SA algorithm to find solutions The new logistic service introduced by Hsinchu Transport is 'GDP Container Shift Planning' This planning involves estimating future volumes of medical materials between stations and scheduling container truck shifts accordingly, ensuring timely and quality delivery of medical materials while maximizing operational benefits and reducing travel distances Hsinchu Transport introduces AI-optimized shift planning, constructing the most efficient route from its origin to destination Hsinchu Transport introduces 'Optimized Shift Planning' service, reducing transportation costs by 5 The introduction method involves using cloud software services Hsinchu Transport regularly inputs 'Interchange Item Tables' from station to station into the 'Optimized Shift Planning' service After setting the algorithm parameters, a GDP container shift schedule is generated At the same time, developing a Hsinchu Transport medical material scheduling system allows Hsinchu Transport's medical transport units to compile suitable schedules through the Interchange Item Tables Under the same level of service, it's estimated that this can reduce transportation costs by 5, saving medical material businesses millions in construction costs for GDP warehouses and distribution Due to its requirements for sanitation, temperature, and its fragility, the transportation and transshipment of medical materials should be minimized to reduce exposure and risk However, logistics efficiency and costs must still be considered AI designs the most efficient route for each cargo from its origin to destination, effectively completing daily transportation tasks In response to the future high development demand of industrial logistics, distribution and transshipment AI optimization will be a key issue Through this project, a dedicated project promotion organization will be established, staffed with AI technology, IT, and process domain talents After accumulating implementation experience, the application of AI will gradually expand, comprehensively optimizing and transforming Hsinchu Transport's operational system, and partnering with AIOT and various AI domain partners to accelerate and expand the achievement of benefits「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

2021-10-14

Records of Solutions

【解決方案】台灣軟體科技實力媲美國際 Golface智慧服務促高球轉型
【2022 Solutions】 Taiwan's Software Technology on Par with International Standards: Golface's Intelligent Services Transform Golf

Compared to Japan, where 90 of golf courses operate without caddies and use an automated service model, golf course management in Taiwan still heavily relies on human labor Facing a labor shortage of up to 70, adopting a site and membership management platform to provide intelligent golf services may be a transformation worth considering for golf course operators 'Taiwan's software technology is comparable to international standards and definitely has the capability to compete in the global market,' says Tsung-Che Liao, co-founder and CEO of Golface, established in 2014 with the vision to leverage technology at its core, aiming to create Taiwan's first golf entertainment platform With over 9 years vested in cultivating intelligent golf services, Liao is well-versed in the nuances of golf course services He has considerable domain knowledge and has launched a comprehensive intelligent golf solution The world's first networked smart golf cart hits the road automation of golf courses is no longer just a dream In mid-May, Golface's newly developed ARES Smart Golf Cat, the world's first networked smart golf cart, officially became operational Equipped with a dedicated vehicle computer mainframe, dual network systems, AI-based visual recognition cameras, and high-precision GPS tracking, golf courses can now confidently allow golfers to drive themselves The system enables real-time monitoring of any driving violations, and the presence of digital consumption traces allows for insurance coverage The procedure is as follows golfers book the cart via a reservation platform, receive a QR code, pay through the platform, and unlock the cart with the QR code at the golf course The golf cart can then be driven onto the course The course management platform can monitor and restrict the areas through which the cart can travel, ensuring it does not leave the paths Upon completion, the cart is returned through a tablet in the cart In instances of any infractions, penalties are applied directly through the user's account, and for severe violations, future access to the carts may be prohibited This achieves the goal of 'automation' ARES Smart Golf Cat is the world's first networked smart golf cart, officially in service since May 2022 'As labor costs continue to rise, recruiting and training caddies are becoming common pain points in the market While Taiwan's courses still employ caddies, there's a 70 labor shortage,' Tsung-Che Liao added This smart golf cart tablet, combined with a mobile app, has become the ultimate smart caddy Golface is striving to complete the last piece of the 'automated golf course' puzzle Amassing digital consumption trails for advanced client segmentation services Starting with consumer needs, Golface has sequentially launched services like the golf cart tablet, mobile app, golf reservation platform, instructional videos Golface TV, golf tourism, and smart carts The smart cart has been operational since May 2022, currently featuring four units with plans for mass production in the latter half of 2022 Although the cart currently requires manual operation by golfers, remote operation is anticipated early in 2023, with autonomous driving expected in the third phase Via the cart tablet and management system, staff can understand the status of the course through on-screen visual representations, showing each cart's real-time and relative location, departure times, and duration of service per hole, which aids course managers in monitoring on-course consumption effectively, thus reducing traffic jams and customer complaints 'Previously, we relied on staff's mental imagery now, we can employ imagery to visualize real-time situations on the course This makes it possible for those who don't understand golf to work in this field,' emphasized Tsung-Che Liao While course control has traditionally been handled by experienced professional players, the shortage of skilled professionals makes hiring even more challenging Therefore, replacing manpower with digital tools yields twice the result with half the effort The golf cart tablet has entered the Japanese golf market, installed at Fukuoka Century Golf Club Golface's golf cart tablet has been introduced to 14 domestic courses, and has now officially entered the Japanese market, favored by Fukuoka Century Golf Club, where tablets have been installed in carts providing automatic voice announcements for hitting strategies, distance measurements, and visual charts displaying hitting data During the COVID-19 pandemic, with borders closed, Golface utilized OTA technology to provide software updates and troubleshooting, ensuring uninterrupted services, which was highly appreciated by the Japanese golf courses Tsung-Che Liao remarks that Taiwan's software technology is not inferior to other countries like Japan, but more support from golf courses is needed to help transform the industry intelligently 'To assist in the transformation of golf courses, the first step is digitalization,' Liao pointed out By helping courses accumulate data and understand customer service cycles and hitting rhythms, it enables courses to avoid congestion and serve more customers To date, Golface has accumulated data on over 20,000 teams, 35 million scorecards, and over 10 million records This data helps enhance management performance, segment customer layers, reduce complaints, and plan marketing strategies for off-peak periods Golface co-founder and CEO Tsung-Che Liao has spent 9 years deepening intelligent golf services, aiming to build Taiwan's first golf entertainment platform「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】7毫秒內分離人聲 洞見未來科技協助聽損者「聽說更簡單」
【2022 Solutions】 Voice Separation in 7 Milliseconds: RelaJet's Future Technology Makes 'Hearing and Speaking Easier' for the Hearing Impaired

One rainy Thursday afternoon near Taipei Arena, the Taipei Experience Center of RelaJet was fully booked with appointments from people with hearing loss eager to try hearing aids made with a voice separation engine For the hearing impaired, having affordable, lightweight, and effective noise-reducing hearing aids is truly a blessing 'We hope to help users in need to hear the world's wonders again' This empathetic expectation by RelaJet's founder and CEO Po-Ju Chen, who is also hearing impaired, illustrates his understanding of the needs of the hearing impaired He hopes that RelaJet's unique voice amplification hearing aid technology will benefit many more people Affordable hearing aids benefit many with hearing loss Founded in 2018 by Po-Ju Chen and his brother Yu-Ren Chen, RelaJet developed a multi-voice separation engine paired with Qualcomm's Bluetooth audio platform, drastically reducing the price of imported hearing aids, typically costing 80,000-100,000 NT dollars, to just under 10,000 NT dollars They aim to develop affordable goods with excellent noise-cancelling capabilities that wirelessly connect to smartphones In its first two years, the company primarily developed the multi-voice separation engine, which significantly improved the noise reduction quality Once equipped with Qualcomm Bluetooth earphone chips, the audio processing time is drastically short, at about 7 milliseconds to enhance main voice projection and reduce ambient noise, less than half the time required by traditional medical standard of 16 milliseconds for hearing aids, nearly 'zero-delay' 洞見未來科技推出平價助輔聽器,大大嘉惠聽損者 Yu-Ren Chen explains that the primary use of Qualcomm chips for edge computing, along with a streamlined algorithm, achieves extremely low latency and better noise reduction The hearing aids can cover 18 channels, whereas traditional hearing aids cover 4-48 channels In the future, RelaJet will progressively increase the number of channels According to statistics, there are 470 million people globally with hearing disabilities, with a 30 average device use rate in developed countries, with the highest in Western countries Taiwan has nearly 15 million people with disabling hearing loss, of which the middle-aged and elderly make up 30, yet the device use rate is only about 10, which is quite low Yu-Ren Chen further analyzes that the low device usage rate is due to two reasons firstly, the high average selling price of international big brands ranges from 80,000 to 200,000 NT dollars with a three-year usability period, which deters many due to the high cost and maintenance Secondly, in noisy environments, the noise is also amplified which does not necessarily ensure clarity for the users, and the sound parameters can't be adjusted in real-time, making it inconvenient to frequently visit stores for tuning Thirdly, most models cannot connect to smartphones, making it inconvenient for the hearing impaired to take phone calls Utilizing Qualcomm Bluetooth chips for rapid product development In light of this, Po-Ju Chen, formerly a semiconductor engineer at MediaTek, leads the technical development, while Yu-Ren Chen, with a legal background, manages the operations Their seamless collaboration, along with their team employing AI algorithms and chip integration, learns from thousands of hours of audio files in databases through neural networks and deep learning technologies to develop low-latency, high-noise-reduction voice amplification technologies for hearing aids In 2019, this sound processing technology was integrated into Qualcomm Bluetooth chips, winning first place in the Qualcomm Taiwan Startup Competition and becoming a partner in Qualcomm's Global Expansion Program, significantly boosting product development pace In 2021, they launched their own Otoadd series of hearingenhancement products in Taiwan, which received both market favor and positive reviews from many with hearing loss Based on different consumer needs, various product designs are available According to Yu-Ren Chen, the Otoadd wireless earphones with hearing enhancement functions, model N1, are entry-level neckband style priced at 9,500 NT per pair Users can wear the hearing aid while taking calls, and control noise reduction strength and volume through a mobile app They plan to develop accessories in the future tailored to the needs of older adults Besides being available for trials at experience centers in Taipei and Kaohsiung, this hearing aid is also sold through PChome, Taiwan Mobile's myfone, and Elder Age networks, among other channels Another model intended for individuals with mild to severe hearing loss is the Classic R hearing aid, which received the Japanese Good Design Award in 2021 Since its market debut last year, it has attracted those with congenital hearing loss, with users noting improved clarity in noisy environments and appreciating the convenience of Bluetooth connectivity for calls and watching videos This product is anticipated to be exported to international markets in the latter half of this year Additionally, a hearing aid product combining Bluetooth functionality, set to launch in June this year, is sized like typical Bluetooth earphones, targeting visually conscious consumers with hearing loss Its small size and attractive wireless earphone design allow for phone calls, and if approved by the Ministry of Health and Welfare, eligible users can apply for government subsidies RelaJet to expand into overseas markets, using the USA as a beachhead An interesting question arises due to the pandemic everyone must wear masks which impedes lip-reading How does this affect those with hearing loss Yu-Ren Chen indicates that this situation highlights RelaJet's advantages As each person with hearing loss has different levels of hearing ability, hearing aids can only augment to an appropriate volume, assisting users to hear about 60-70 content, with the remainder relying on lip reading and gestures During the pandemic, as everyone wears masks, masks also muffle sounds, but RelaJet's voice separation engine can correct and strengthen the separation, making it easier for those with hearing loss to recognize voices Besides the Taiwan market, RelaJet's next stage will be expanding into overseas markets, expecting to obtain ISO 13485 medical device quality management system certification and US medical device approval in 2022 They plan to enter the US market, either under their own brand or through OEM arrangements Apart from the Taiwan market, RelaJet will also enter the US market in the next phase for hearing aids「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】客廳化身為健身房 Uniigym矢志成為健身界的Netflix
【2022 Solutions】 Living Room as a Gym: Uniigym Aims to be the Netflix of Fitness

Afflicted by the pandemic, most people choose to stay at home However, for those who enjoy exercising, missing a day at the gym can feel uncomfortable With Uniigym's 'AR Fitness x Uniigym' app, users have access to nearly 1,000 diverse exercise classes With a dedicated AI coach, users can exercise anytime they wish, while also tracking their fitness journey, and understanding their condition completely To encourage public fitness and fight the pandemic together, Uniigym has also collaborated with Chunghwa Telecom, offering free access to the 'AR Fitness x Uniigym' app for 30 days starting from now until the end of June, contributing to the public health effort Founded in 2019 by CEO Yu-Chieh Lin, Uniigym was conceived from the monotony and limited options of gym venues like fitness centers and school gyms, and low interaction with trainers The company aims to make exercising as fun as gaming through technological solutions, starting with their first product—an intelligent dynamic projection system that has gained favor in the fitness market Uniigym continuously innovates fitness products creating a comprehensive platform for sports health Uniigym is dedicated to creating an immersive fitness course platform starting from offline venues to an online platform, thereby achieving a full spectrum of fitness content and increasing data traffic for enhanced monetization capabilities Over three years, Uniigym has continued to develop new products So far, they have reached the third generation of products In addition to the Uniicube, a dynamic projection fitness system, there's also Uniihome, which turns living rooms into gyms through set-top boxes provided by Taiwan Broadband Communications and cable television provider Kbro Furthermore, the third generation, Uniicell, allows users to exercise anywhere anytime with mobile devices and 5G networks Next, Uniigym plans to launch the fourth generation, Uniicare, targeting businesses and government employees with camera and heart-rate devices to gather health data and offer health management solutions Features of the AR Fitness x Uniigym App "Uniigym is a combination of Netflix and Nintendo, aiming to become the Netflix of the fitness world" By lowering the barriers to exercise through Uniigym's diverse workout classes and fostering a national habit of exercise, marketing director Shu-Wei Wang explained the company's strong ambition and its ongoing progress towards these goals Since the launch of the AR Fitness x Uniigym app in collaboration with Chunghwa Telecom in November 2021, the app has seen over 20,000 downloads in less than half a year, featuring nearly 1,000 multi-category classes including aerobics, fat-burning, body sculpting, strength training, yoga, boxing, and popular dance Built-in latest AI posture algorithm for real-time monitoring of exercise state The AR Fitness x Uniigym APP features six key functionalities, consisting of One Celebrity fitness courses, featuring a hundred top instructors, pick and practice anytime without appointment Two AI real-time motion matching that captures 20 skeletal points of the body through the phone's camera, accurately comparing movements and providing instant feedback Three AR fitness trainer, accompanying you in any environment, personally guiding the workouts, making the fitness experience more engaging Four Gesture remote control interface, allowing you to remotely access various features, making operations easier Five Supports screen casting, syncing the phone with TVs and screens to enhance immersive exercise experiences Six Self-data tracking, fully recording fitness progress including exercise hours, calories burned, and training programs AR动滋动 x Uniigym Rise to Exercise, Safeguard Health TAIWAN SAFE Event Introduction Most importantly, the system platform integrates the latest AI posture algorithm, comparing user movements and skeletal points with those of the fitness trainer during exercise, combined with heart-rate belts to display changes in heart rate on the screen during exercise By employing technology in exercise, it not only protects users during training but also helps in logging physical energy consumption, effectively enhancing exercise efficiency and preventing exercise injuries Uniigym is deeply rooted in Taiwan and expanding to international markets In fact, Uniigym's products are iteratively evolved according to different user groups The second generation product, Uniihome, turns living rooms into gyms in collaboration with the television system platforms, Taiwan Broadband Communications and Kbro, featuring set-top boxes with a menu of 1,700 classes, each lasting 3-5 minutes suitable for all family members ranging from grandparents to children, providing a freely selectable fitness menu for different groups AR Fitness x Uniigym App Product Experience Scenario Illustration In the post-pandemic era, exercising at home has become a trend Uniigym's interactive sensor-based fitness courses offer consumers a convenient, economical way to exercise anytime, anywhere It eliminates the need for purchasing fitness equipment or spending on expensive courses, as users can enjoy personal guidance from an AI coach directly through their smartphones, enhancing their willingness and frequency of exercise, playing an essential role in promoting a healthier lifestyle for all Uniigym provides a combination of online and offline AI cloud-based interactive sensor technology services, matched with home settings and various types of exercise spaces, to offer consumers an entry-level threshold to enjoy professional and entertaining fitness experiences anytime, anywhere This innovative business model has attracted investments from renowned Taiwanese listed companies such as, Nan Yih Textile and Taishin International Bank, and also partnerships with notable international sports enterprises like Decathlon Besides deep-rooting in the Taiwanese market, Uniigym is also actively expanding into international markets including Singapore, Thailand, and China This year 2022, Uniigym plans to launch its products with the Singaporean telecom group Singtel, allowing Chinese-speaking users and a broad international audience to enjoy new interactive sensor-based fitness courses In the future, Uniigym will also introduce home-based health management solutions for corporate and government employees, where employee health data is collected during exercise through cameras or heart rate devices, analyzed, integrated, and linked with health and medical data to achieve preventive medical goals Uniigym founder and CEO, Yu-Chieh Lin「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【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
【2022 Solutions】 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

【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
【2022 Solutions】 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】AI電眼取代人眼 慧演智能運用AI幫製造業做品管
【2022 Solutions】 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

【解決方案】讓硬碟裡的音樂重生 愛飛媒平運用AI為影像找到最佳拍檔
【2022 Solutions】 Rebirth the music on the hard drive. Aifei Matchmaking uses AI to find the best partner for the image.

A young girl, alone in Los Angeles, USA, is looking for a dream, a dream that allows the music creator to find her soulmate again with the music she buried deep in the hard drive Li Zihui, the founder of iFeiMedia, has a background in science and engineering, but she has a strong gene for musicians In order to help global musicians create music and find the "best partner" who can successfully match them, she founded iFeiMedia Ping Company provides a one-stop AI video and music matching platform AV Mapping to help video creators quickly find copyrighted original music One-stop AI image music matching solution to find innovative business opportunities for music creators Generally speaking, in the past, video creators had to work on video music, including composing lyrics, music, and finding copyrights It usually took two weeks Through the AV Mapping video and music matching platform, it can be instantly matched to a suitable video in 10 seconds Music, musicians can also remarket their creations to gain profit sharing, creating a win-win situation This new, decentralized operating model is also favored by the descendants of the late Taiwanese music master Li Taixiang On the platform, you can relive a time when music creation was free to fly Li Zihui has practiced piano since she was a child, participated in choirs and wind bands, and composed her own music Although she studied science and engineering in college - the Department of Surveying and Spatial Information at Cheng Kung University, she joined the imaging team to work on soundtracks from her junior year , and went to the Applied Music Department of Nanyit University to audit After graduating from college, Li Zihui decided to obey the voice in her heart and become a music dreamer Aifei Matching provides a one-stop AI image and music matching solution Aifei Matching provides a one-stop AI image and music matching solution, which mainly uses artificial intelligence image recognition and music analysis Image creators can search and match suitable music by themselves on the platform, and use the system to It can shorten the duration of the soundtrack from 8 hours to a few seconds, a significant reduction of nearly 2,000 times Li Zihui said that in addition to creating suitable soundtracks, traditional video scoring projects also require a lot of time and cost in communication and search, including subsequent post-production processing such as arrangement and recording, and music licensing, which are even more time-consuming and labor-intensive With the assistance of AI, creators can focus all their efforts on creation without worrying about finding suitable music or having their music copyright stolen Integrated virtual and real marketing, from transaction to contract signing with one click At present, AifeiMeiping's music database has a total of 60,000 tracks in more than 60 categories, covering music from Europe, America, Asia and other parts of the world, including pop, EDM, rock, Irish music, etc The original decentralized concept of iFlyMediaPing further protects the rights and interests of musicians Musicians on the platform can set their own prices and track the transaction process, achieving open, transparent and decentralized features There are currently more than 7,000 video and music creators on the platform Music creators who successfully trade on the platform can share profits of more than 40, up to 50 The two parties transact and complete the contract on the platform, and the procedure is very simple AVMapping has a total of 14 AI models, making it easy to find speed dating music Li Zihui said that the AI image music matching solution has a total of 14 AI models The method is to disassemble all elements, conduct music analysis through image recognition and text recognition, and then use machine learning algorithms to train extensively The characteristics of images and music are listed, which can quickly match the soundtrack that suits the image situation, atmosphere, and rhythm In addition to online matchmaking transactions, Aifei Matchmaking also holds physical concert events, inviting music and video creators to participate The content of the event revolves around the display of AI video soundtracks, and a video directed by the director is used on-site to allow music creators to participate PK soundtrack or take out a demonstration video and let AI match it It only takes 10 seconds The images and music matched by AI are very accurate in terms of mood and atmosphere, which amazed the participants Three years of research and development won the Red Dot Design Award, using technology to support the development of music and art Aifei MatchPing spent three years of research and development, and the platform was officially launched in August 2021 In January 2022, it participated in the CES event in Las Vegas, USA, which attracted great attention from reporters present and received more than 100 awards in total media reports, the number of uses in a month has exceeded 1,000 times, attracting 7,000 video and music creators to join the matchmaking platform According to statistics, in the initial stage, the proportion of matchmaking transactions between the United States and Taiwan is evenly divided Li Zihui said that the licensing methods of traditional music are very complex, including types of works, types of copyright property rights, etc To obtain authorization for a song, one must go through a songwriting agency, a collective management group, a production company, a record company, or even a composer , lyricists, it is very cumbersome, and musicians may not necessarily get profit sharing Through the AI image music matching platform, all transaction contracts are completed online, music creators can gain profits, and their creative enthusiasm is constantly stimulated Three steps to help video creators easily complete the soundtrack work It is worth mentioning that NFT Non-fungible token, also known as non-fungible token is currently very popular in the art and cultural market What is the possibility of introducing it into the field of video and music Li Zihui said that the current transaction fees gas fees of Ethereum remain high, and coupled with the conclusions she obtained from attending many gatherings in Los Angeles, the acceptance of NFT is still in the process of brewing However, Aifei Matching is still optimistic about the future of NFT Trend, in the foreseeable future, relevant technologies will still be introduced into the AV Mapping platform to provide more diversified trading methods In order to rapidly expand overseas markets, Li Zihui continues to seek funding from international strategic investors in San Francisco At the same time, due to the appropriate control of the epidemic in Los Angeles, the industry is gradually recovering, and Li Zihui also participates in many offline creative gatherings Aifei Media hopes to become a bridge connecting images and music, introduce well-known user cases in the international market, and let more creators see the power of the platform Aifei Media Ping also frequently reports good news After winning the DSA Digital Advertising Singularity Silver Award and the AWE Female Entrepreneurship Best Potential Award co-organized by the American Institute in Taiwan and META, the one-stop AI video and music matchmaking company founded by Li Zihui The platform AV Mapping also won the Best of the best in the Design Concept of the German Red Dot Award in 2020 We hope to continue to be based on technology and nourished by art Support music creators to create better works Li Zihui, the founder of Aifei Matchping, has won many international awards and is a female entrepreneur with great potential「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】AI也懂行銷太米科技個人化推薦服務助時尚電商提升3倍轉換率
【2022 Solutions】 AI Understands Marketing?! Tammy Technology's Personalized Recommendation Service Helps Fashion E-commerce Increase Conversion Rates by 3 Times

Having experienced small to medium-sized e-commerce, founders and CEO Zi-Hao Huang and co-founder and COO Yi-Ting Li of Tammy Technology decided to tackle the marketing challenges of all e-commerce personnel using AI technology Focusing on fashion e-commerce, Tammy Technology's personalized recommendation SaaS Software as a Service helps small to medium enterprises tackle the rising costs of marketing and the overwhelming data, enhancing conversion rates and average order value, becoming an invaluable AI assistant in the fashion e-commerce industry Enhancing conversion rates has always been a major challenge for all e-commerce platforms Unlike major players like Google and Facebook who collect browsing history to target interested messages or advertisements, smaller e-commerce businesses lack the resources and manpower to construct data analysis systems or tools Company Position Marketing technology team for small and medium-sized e-commerce utilizing AI to establish automated marketing Established in 2016, Tammy Technology initially aimed to become 'the marketing technology team for small to medium-sized e-commerce,' hoping to resolve challenges of low conversion rates and customer retention through data analysis and personalized recommendation services 'Daniel referring to Zi-Hao Huang and I have both worked in small to medium e-commerce I handled branding, marketing, and design, while he managed backend systems, project management, and development launches, almost everyone was multitasking' Understanding the pain points of e-commerce operators, they decided to help small and medium enterprises by developing automated marketing systems and a personalized recommendation SaaS, aiding those with limited marketing resources Through AI technology, analyze consumer purchase preferences and provide personalized recommendation services By analyzing each consumer's purchase preferences using AI technology and storing their digital footprints in the backend for data analysis, Tammy Technology stands apart from traditional recommendation systems that categorize customers They offer personalized product recommendations based on each individual's style preferences to achieve precise marketing objectives Yi-Ting Li emphasizes that Tammy Technology's personalized recommendation service has two main functions one is to make website personalized recommendations, and the second is to integrate with marketing channels such as email, SMS, and chatbots chatbot to send personalized promotional messages When consumers enter the official website, based on consumer profiles and preferences, different product recommendations can be provided on each page Individual products also have different recommendation systems on different website pages, providing each consumer with a unique shopping experience after entering the site Using deep learning AI technology, Tammy Technology analyzes consumer behaviors at various online shopping touchpoints through various devices, digitalizing all consumer behavioral data to build consumer profiles For example, a consumer with high purchasing frequency designated as VIP, whose preferences for Morandi color schemes, lace materials, high-neck styles, etc, are recorded and tagged When browsing the store's website, the website will recommend corresponding products based on these purchase preference tags for VIP, and can also set customized discounts and pop-up windows, or send personalized messages through mobile SMS, email, etc, ensuring each customer receives discounts that fit their needs At this stage, Tammy Technology's client base includes male and female apparel, shoes, accessories, cosmetics, and other fashion design industries with a strong personalized color Many clients have seen significant results after introducing personalized recommendation services For example, Shu Uemura under the L'Oreal Paris group, specializing in high-performance skin products and trendy makeup products and professional makeup tools, experienced a significant increase in conversion rates by 3 times and a revenue increase of 18 times after adopting Tammy Technology's service Additionally, the well-known apparel business iRoo, after installing a personalized recommendation system on the official website and integrating digital marketing channels like Line and Chatbot, saw the conversion rate rise more than 5 times, with a monthly revenue increase of 21 The pricing model is subscription-based, with large corporations being charged based on specific feature needs The overall effect after customer usage achieves at least a 3 times increase in conversion rate, and an average of 2 times growth in average order value New client base After apparel and cosmetics, pushing into the home decor industry Despite the overall increase in e-commerce sales, the personalized recommendation service has shown impressive results However, due to the pandemic, non-essential fashion industries have been impacted Tammy Technology, which primarily relies on the fashion design industry, saw a decrease in e-commerce performance by about 30 during the pandemic To diversify operational risks, starting from 2022, Tammy Technology expanded its service clientele to include distinctive, quality-type home furniture and living products As for why not expand the client base to 3C products Yi-Ting Li explains, 3C products focus on cost-effectiveness and brand strength, like Apple computers which have a loyal group of fans, making it challenging to sway their purchasing behavior However, apparel, cosmetics, and home decor focus on personalization, style, and taste, like apparel with the fast, short-term 'fast fashion' trends, updating products weekly, and seasonal characteristics, updating personalized recommendations every 3-5 days and cosmetics, including makeup and skincare, which have high customer loyalty and repurchase rates, are most suitable for recommendations and proactive discount messaging Makeup and outfits represent personal taste, thus these two industries can complement each other in personalized recommendations To accelerate the process of integrating businesses with personalized recommendations, it is necessary to establish an SOP,' Yi-Ting Li continued, 'Tammy Technology, by introducing recommendation services in the fashion design industry, has constructed a service process SOP to facilitate rapid successful experience replication, expecting to quickly integrate into the life and home industry in the second half of the year New business model Establishing a new marketing model centered on the consumer Currently, Tammy Technology's client number has exceeded 2000, including globally renowned fashion brands like L'Oreal and BLUE WAY The future focus will remain overseas, aiming for markets like Hong Kong, Singapore, and North America Tammy Technology, with its successful experience of integrating recommendation systems into fashion e-commerce, has gained investors' favor, securing investments from domestic and international accelerators in 2021, raising a total of 70 million New Taiwan dollars, allowing for workforce and scale expansion Future plans include integrating investor resources to establish a new marketing model centered on consumers Tammy Technology co-founder and COO Yi-Ting Li「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

這是一張圖片。 This is a picture.
【2022 Solutions】 Understand customers better than they do themselves, business opportunities created by the pandemic doubles the performance of Spingence Technology

"After the COVID-19 pandemic, even though we could not expand business overseas, the pandemic increased demand for AI automated optical inspection AOI and drove another wave of rapid growth in performance," said Jesse Chen, Founder and President of Spingence Technology The company started early in AOI and accumulated a wealth of experience, resulting in performance in 2021 growing multiple times compared with the previous year Spingence Technology's AI technology has great potential, and its fundraising plan successfully attracted strategic investors, such as the leading industrial computer company Founded at the end of 2015, Spingence Technology started out as a developer of automation software to help customers lower the barrier to automation In just two years from 2017 to 2018, AI technology quickly took off At that time, Jesse Chen observed that product defect detection caused headaches for companies in the process of automating manufacturing The traditional method of manual visual inspection was time-consuming and laborious Moreover, human error easily occurred and AI deployment could not be customized, resulting in high investment costs for enterprises Seizing the AOI market, successful application of AI optical defect detection "The gap in AOI is defect detection Since defects cannot be clearly defined, conforming products were often labeled as non-conforming products to meet the customer demand of not releasing defective products As a result, the overkill rate is often very high, which not only increases the cost of the manufacturing plant, but also lead to a waste of resources" In addition, there is strong demand for process automation due to the shortage of labor in the production line, which created a rare business opportunity for Jesse Chen AI optical defect detection has become the focus of Spingence Technology's AI applications After accumulating nearly 8 years of experience in production line automation, Spingence Technology target customers in three major industries, namely passive components, connectors, and semiconductors, and established a huge database for the production line product defect data it collected Since Spingence Technology started early, it enjoys the advantages of a first mover and continues to optimize database data Its wealth of experience enables it to quickly determine customer needs and propose solutions Spingence Technology uses image recognition and deep learning technologies to develop AOI algorithms, and developed AI defect detection solutions with an accuracy greater than 99 In terms of specific benefits, the overkill rate in the semiconductor industry can be significantly reduced from an average of 5-8 to less than 3, and the overkill rate of passive components can also be reduced from 5 to 12, which can save customers nearly NT300 million in expenses This not only reduces the waste of human resources, but also makes Spingence Technology a good helper for customers' sustainable intelligent manufacturing The outbreak of COVID-19 at the end of 2019 has changed the way people live and work around the world During the pandemic, demand on automation in the manufacturing industry significantly increased due to the need to avoid frequent contact between people Spingence Technology has a good reputation in the industry, so business kept coming in and doubled the number of customers and revenue The secret to winning Follow the footsteps of customers and always think more than customers In addition to Taiwan, Spingence Technology has also extended its reach to markets such as China and Vietnam, where Taiwanese businessmen gather The team in China is expected to increase from 3-4 people to 10 people, and Vietnam also hopes to have a team of 5 people to provide closer services to customers "Spingence Technology always follows the footsteps of its customers We are wherever our customers are" Jesse Chen went on to say that although the pandemic has brought another wave of demand for AI automatic detection, due to the impact of border controls, it was hard to go on business trips Meanwhile, overseas markets on-site personnel to provide nearby services, including consultation and diagnosis, AI implementation, and calibration, all of which require dedicated personnel Spingence's automation software development platform integrates modularized visual inspection, motion control, IO control, and AI analysis functions Coupled with the AI training software "AINavi", one heat sink inspection machine can complete multiple inspections and continue to train the AI deep learning model, which will further lower the miss rate of the machine and improve its inspection quality The integration of AINavi and automation is already sufficient to meet most functional requirements of customers, and then a small number of customized services are provided for different industries and customer needs This allows the company to quickly provide solutions needed by different customers Popular among strategic investors, the company has attracted investments from industrial computer companies and venture capital Spingence Technology has made a mark in the field of AIAOI inspection in the manufacturing industry, and has gain the favor of strategic investors In 2019, a leading industrial computer company made a strategic investment in Spingence Technology and integrated the AINavi deep learning visual inspection tool with the company's complete hardware platform The cooperation between the two parties provides more complete service solutions to customers, creating an example of win-win through "big large company leading small start-up" In February 2022, Spingence Technology reported another good news in its fundraising and received an investment from venture capital, all of its original major shareholders also increased their investment, and nbspSpingence Technology successfully completed the Pre-A round of funding The company will continue to expand its business in the short term, and establish a foothold in China and Vietnam In the future, it plans to build expert systems for passive components, connectors, and semiconductor industries, deepening its domain knowledge and data analysis to create greater value for customers Spingence Technology prides itself as a management consulting company for the manufacturing industry, that is, it provides customers with the most appropriate and valuable consulting services through consulting services, diagnosis, introduction, system launch, personnel training, model optimization, and AI model management

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