Looking around the world and in Taiwan, the number of patients suffering from vertigo is increasing year by year When faced with vertigo testing, most people will choose to have it diagnosed by a doctor or hospitalized with neuromedical imaging tools such as MRI or CT for interpretation However, this may lead to misdiagnosis of vertigo, overdiagnosis of patients, waste of medical resources, etc, and cannot be effectively traced back The actual condition of the patient's dizziness In order to solve the long-term clinical pain point of vertigo, Neurobit has developed a smart wearable medical device - NeuroSpeed smart glasses and an AI assistance system It provides an AI smart solution for rapid screening of vertigo, assisting doctors in quickly screening more than 80 of brain diseases Efficient detection power with accuracy and sensitivity of over 90 Neuron Technology was founded in 2016 The co-founders include Yang Juncheng, Chen Weicheng, Huang Jinxun and Wang Jingfu The four of them were studying at the National Taiwan University Medical Engineering Institute and the Creative Entrepreneurship Program to jointly offer the "Biomedical Innovation and Commercialization" course Next, let’s embark on the entrepreneurial journey together The core team members of Neuron Technology are mainly composed of cross-field experts in medical engineering, information technology, neurology, patents, business, etc The common entrepreneurial concept is to continuously explore and explore unsolved pain points in medical clinical practice Seeing that patients were suffering from vertigo, Neuron Technology invented and independently developed an efficient and practical wearable smart medical device, NeuroSpeed Smart Glasses, which combines hardware AI-assisted decision-making system software to provide an AI smart solution for rapid dizziness screening Neuron Technology CEO Yang Juncheng said that the proportion of people in Taiwan and the world who suffer from vertigo is very high In Taiwan, as many as 3 of the people about 700,000 suffer from vertigo, while in the United States, about 1,000 people suffer from vertigo Tens of thousands of people go to see a doctor due to vertigo From the data, it can be seen that the vertigo medical care market is quite huge Regarding rapid screening for vertigo diagnosis in the clinic, current rapid screening tools in hospitals mainly use neurological examinations, and most of them are processed through questionnaire-type scales The diagnosis will rely too much on the patient's chief complaint and the doctor's experience judgment, and lacks quantitative indicators, resulting in Misdiagnosis of vertigo and loss of golden treatment time For patients with vertigo who are admitted to the emergency department, medical diagnosis in the past relied heavily on neuromedical imaging tools such as computed tomography CT or magnetic resonance imaging MRI After observation, it was found that the equipment was insufficient In the United States, the number of patients admitted to the emergency department Less than 3 of the population can receive immediate MRI diagnosis, and less than 50 can receive CT diagnosis However, excessive use of CT or MRI diagnosis may lead to overdiagnosis and treatment of patients, and even waste of medical resources In order to help vertigo patients accurately and efficiently screen and triage and reduce over-diagnosis in clinics and emergency rooms, NeuroSpeed Smart Glasses, a wearable smart medical device developed by Neuron Technology, is believed to have a great impact on the overall application of medical resources and patient diagnosis and treatment It is very helpful Yang Juncheng said that if it is not necessary to use MRI to track the diagnosis, this device can be used as a rapid screening test before the existing MRI neuroimaging tools and after the patient is admitted to the hospital, reducing over-diagnosis of patients NeuroSpeed's examination method is to quickly screen for nystagmus to identify patients with potential brain diseases The examination method of this technology is to observe the trembling state of the eyes and a series of eye movements when the subject is staring at a stationary object, so as to judge Brain risks for appropriate diagnosis and treatment NeuroSPeed smart glasses can crack brain and eye diseases, clinical trial sensitivity reaches 90 With the active research and development of Neuron Technology, two generations of NeuroSpeed smart glasses have been successfully launched The first generation NeuroSpeed mainly provides doctors with real-time observation of high-quality eye images and eye movement response-related examination data reference, and does not provide auxiliary diagnosis services The second generation of NeuroSpeed allows physicians to record, track, store and view relevant eye movement analysis and pupil area identification, thereby effectively diagnosing diseases of the central, meridian and peripheral nervous systems Because the second-generation NeuroSpeed product has the function of assisting doctors in analysis and diagnosis, it has been classified as a Class II medical device in the United States and must be certified by the US FDA before it can be sold externally At this stage, this product has completed pre-submission and will be submitted for review after the biocompatibility test is completed It is expected that the second generation NeuroSpeed will successfully obtain US FDA certification next year In terms of actual verification fields, NeuroSpeed has currently cooperated with New Taipei Shuanghe Hospital and Taichung Tzu Chi Hospital for clinical verification Its clinical results have confirmed the classification judgment of central nervous system diseases such as stroke and other vestibular system diseases With the addition of NeuroSpeed Smart glasses are designed to be lightweight and easy to carry, detect quickly and easily, and have the functional characteristics of automatic interpretation They can effectively assist doctors in quickly screening for potential brain disease risks in patients with vertigo Field verification with foreign medical centers mainly involves vertigo patients admitted to the emergency department Physicians can use NeuroSpeed smart devices to interpret the phenomenon of stroke diagnosis Currently, the accuracy of clinical trials in the above-mentioned cooperative hospitals reaches 80 and the sensitivity reaches 90 Neuron Technology develops smart wearable medical device NeuroSpeed smart glasses In addition to becoming the best smart medical assistant for doctors to quickly screen brain disease risks in the clinic and emergency department, NeuroSpeed smart glasses also assist doctors in the detection and assessment of strabismus risk They are jointly developed with the Tri-Service General Hospital through neuron technology The "Portable Strabismus and Abnormal Eye Movement Diagnosis System" is implemented in the Tri-Service General Hospital, providing doctors with a complete preoperative assessment of strabismus and postoperative tracking basis This excellent RD technology achievement was recognized by the 17th National Innovation Award-Clinical Innovation Award in 2020 We know that many diseases can cause congenital or acquired eye movement abnormalities, and even cause symptoms of strabismus or nystagmus Among them, as for strabismus, according to expert physician consultation surveys, the global prevalence of strabismus among school-age children is 2 5, while the prevalence of strabismus among school-age children in Taiwan is about 1 to 4 Yang Juncheng said that clinical diagnosis of the symptoms of these diseases is mainly divided into two categories deviation measurement of eye position and eye movement test It has been observed that there is currently a lack of objective quantitative methods for diagnosing eyeball position deviation, and eyeball deviation measuring instruments are used to check subjectively For Neuron Technology, the current NeuroSpeed instrument and strabismus and abnormal eye movement diagnosis system software can integrate objective and clear eyeball images, eye muscle function and eye deviation angle data as a rapid test that meets clinical diagnostic criteria Service, the data of these tests can be used as the basis for doctors’ complete preoperative assessment and postoperative tracking of strabismus Therefore, this system can provide objective and effective quantitative analysis, which can greatly reduce the medical risks of patients during surgery In terms of business model, Neuron Technology mainly cooperates with hospitals to sell research-based products It is believed that the company expects to have significant revenue performance after passing the FDA next year At present, Neuron Technology will use the country's first wearable smart medical device NeuroSpeed smart glasses and AI assistance system to provide software and hardware integrated solutions to assist doctors in quickly screening brain diseases and eye diseases, extending patients' golden treatment time and reducing social risks health care costs to create a triple win NeuroSpeed smart glasses assist doctors in quickly screening brain and eye diseases Looking at the world, the pioneer of smart medical equipment, a new paradigm of biomedical software and hardware system integration In the early days of Neuron Technology’s entrepreneurship, technology research and development and business expansion faced many challenges Yang Juncheng expressed his sentiments that since the NeuroSpeed product is the first medical smart glasses developed in China, both in terms of obtaining hardware raw materials and developing technical specifications, The challenges associated with building and integrating related systems are higher than those for consumer electronics Additionally, bringing together cross-disciplinary talent and integrating it into a core team is also an entrepreneurial challenge In terms of business development, although the company has accumulated clinical verification results and published related outputs, the establishment of market channels still requires continuous efforts to expand It is hoped that it can continue to rely on the assistance of legal persons such as the Capital Strategy Council to actively create more diversified market channels and connect potential Cooperating manufacturers In order to accelerate international expansion and market operation exchanges, the company will conduct a new round of fundraising planning at this stage to meet development Since its establishment, Neuron Technology has taken long-term development and stable profits as its operating goals Yang Juncheng said that in addition to focusing on existing professional fields, we also develop and apply value-added products through the company's software development and software development The accumulated RD energy of hard integration is expanded to other medical disciplines and fields Yang Juncheng hopes that Neuron Technology can become a pioneer in smart medical equipment, with research and development oriented to meet the needs of users and patients, and also hopes to become a model for the integration of biomedical software and hardware systems For the medium and long-term layout, the company will promote industry-university exchanges and cultivate biomedical talents integrate upstream and downstream industry resources to create smart medical solutions and platforms and actively explore foreign sales markets such as the United States and Europe as a basis for sustainable development of the company Vision 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

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

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