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

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」

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」