【2021 Solutions】 Customized AI Models: Jia Heng Technology Helps Clients Accelerate AI Application
After the COVID-19 pandemic, the push for digital transformation using digital tools has accelerated across all industries. However, for business owners, the question arises: Is it worth implementing AI? What benefits does it bring to the company? In fact, there are many AutoML platforms currently available that help businesses speed up the introduction of AI and build AI models, simplifying the adoption of AI for companies.
Businesses face significant challenges in adopting AI, and automated machine learning platforms offer solutions
Jia Heng Technology's General Manager Liang Baifeng stated that businesses face challenges such as scarcity of talent, data handling, timing of modeling, integration with production, technology mastery, and cost efficiency when adopting AI. Nevertheless, not every process needs to incorporate AI technology. What businesses need are AI custom solutions that meet business requirements. Thus, AutoML is a core tool for businesses applying AI technology. Previously, to build 100 AI models, 100 modeling experts were needed. With AutoML, only a few data scientists are required to build 100 models. Once AI models are established, they can be integrated into business production processes. Thus, complex application scenarios can be addressed through highly customized modeling to meet client demands.
In the process of enterprise AI adoption, it used to rely heavily on AI experts, but in the future, it will be driven by industry experts, focusing on solving real business application scenarios as the key to success. Liang Baifeng thinks there are four key phases:
One, Scenario Selection: Deciding whether machine learning is the right approach for solving the problem.
Two, Data Preparation: Data is just material. Choosing the 'right' and 'effective' data is crucial.
Three, Model Building: Focus on the efficiency of model design, a combination of multiple models is necessary to solve problems.
Four, Production Integration: The model meets the restrictions of production while maintaining flexibility based on production conditions. To address the issues of diverse business scenarios, high implementation hurdles, long cycle times, and high costs faced by traditional AI model design, it is essential to utilize AutoML technology to create an automated platform, effectively resolving the developmental and implementation challenges of AI.
DarwinML's Four Core Technologies help enterprises start from scratch in model design
Developed by Jia Heng Technology, DarwinML is an AutoML platform for designing AI machine learning models based on genetic evolution theory. DarwinML uses an evolutionary approach to automatically design and optimize machine learning and deep learning models, featuring excellent capabilities in model generation and hyperparameter optimization, starting from 'zero' to design models automatically.
The four core technologies of DarwinML are described as follows:
One, Model Gene Bank: Collects a large number of algorithms and basic modules that can be applied to Deep Learning, Machine Learning, and Data Feature Extraction.
Two, Auto-evolution Algorithm: Utilizes genetic algorithms, model interpretative statistical methods, and reinforcement learning techniques. In the continuous model evolution, it enhances model quality.
Three, Complete Model Lifecycle Management: Uses DarwinML and Darwin Inference to build a closed ecosystem for model generation, use, and re-optimization.
DarwinML significantly shortens the modeling time, and efficiency is markedly improved
In the traditional model design process, originally from data feature extraction, model design, model training to parameter adjustment, it took AI engineers 3-6 months to manually model. However, using DarwinML for automatic modeling can shorten it to 3-7 days, significantly reducing time and markedly improving efficiency. DarwinML can automatically generate models and rule sets based on objectives, with modules possessing self-evolving capabilities. Its core technologies include machine/deep learning/model gene banks, model evolutionary design algorithms, and big data parallel computing technology, among others, yielding significant benefits such as:
One, Data organization, data labeling, and data cleaning are semi-automated, reducing dependency on the workload and volume of labels by 40%.
Two, Machine learning modeling time is reduced to minutes, with a modeling capacity 5%-10% higher than traditional modeling.
Three, Deep learning modeling time is reduced to hours, achieving a standard consistent with the industry's best models but more straightforward and faster.
(This article is organized from selected content of the 'AI Engineering Online Meetup')
「Translated content is generated by ChatGPT and is for reference only. Translation date：2024-05-19」
Recommend Cases
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」
In construction site operations, implementing safety protection measures and establishing related processes are essential for controlling workplace safety Every business owner strives to minimize industrial safety risks To reduce the probability of workplace accidents, it is particularly important to inspect personal protective equipment PPE and safety measures The Yongyi Smart Construction Site Security Platform utilizes an AI-embedded system, not only to detect whether workers are properly wearing helmets, but also to manage access control at construction site entrances and verify worker identity The Smart Construction Site Security Platform is also a part of the government's push for the Smart Construction Label Initiative 'Smart Site Management' is one of the three main items under the 'Maintenance Management' indicator, highlighting the importance of 'Smart Site Management' This solution includes access management, surveillance management, safety management, and environmental monitoring as aspects of its AIOT solution Feature Highlights 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-11-09」