Launched in late 2022, ChatGPT showed the world the almighty power of generative AI, thus paving the way for the AI 2.0 revolution. At the heart of generative AI is so-called the large language model (LLM), which is trained on large amounts of data. ChatGPT, for example, is based on either GPT-3 with 175 billion parameters, or GPT-3.5 with 200 billion parameters. Currently, apart from Open AI, Taiwan Web Service's (TWS) Formosa Foundation Model (FFM), and other paid LLMs offered by domestic and foreign companies, there are many more open-source LLMs on the market, such as Hugging Face's BLOOM and Meta's Llama 2. These LLMs are equipped with 7 to 176 billion parameters and can be used legally in commercial environments.Both commercially licensed and free open-source LLMs, once trained on proprietary data, can be utilized by companies in a variety of ways. For example, LLMs can be used for intelligent customer service, code writing, or improvement of efficiency of corporate information utilization. Such applications have significant potential to increase business productivity and industrial competitiveness. Therefore, numerous providers on the market have claimed to help with the implementation of generative AI. However, only a few companies have invested in such projects, while most are adopting a wait-and-see attitude.Leo Yang, Chief Marketing Officer of DeepMentor, pointed out that despite the strong demand for generative AI and the urgent need for its early adoption to improve industry competitiveness, companies are still hesitant for three main reasons, i.e., confidentiality and security considerations, high implementation costs, and lack of AI talents. Even if companies are interested in moving forward with generative AI projects, most do not know where to start, as there is a frenzied scramble for AI talent worldwide. In addition, most vendors offer generative AI services on cloud-based platforms, leaving companies concerned about the potential leakage of confidential data. Finally, the cost of training AI models in the cloud can easily reach Hundreds of thousands or even millions of dollars, as most proprietary models need to be trained three to five times to meet customer requirements. These high costs deter many companies from implementing AI projects.Customized Generative AI Designed for Cloud or On-Premises Use Drastically Reduces Project Costs and TimeTo summarize the three factors mentioned above, only a few large companies have enough AI talents and capital to invest tens of millions of dollars at a time in AI servers to satisfactorily perform in-house AI model training and inference. Most medium-sized companies can only look on in envy, not to mention small and medium-sized enterprises with limited budgets and manpower.To help more enterprises and educational institutes adopt generative AI, DeepMentor launched a comprehensive hardware and software solution for designing generative AI, the Mentor series (basic to advanced versions). Customers can select to conduct different levels of all-parameter LLM training (please see the diagram below) based on hardware on Mentor Series. DeepMentor helps customers verify the training results versus actual application needs. Take the basic Mentor-100 as an example. Mentor-100 is a product of collaboration with a major industrial computer brand, Axiomtek, which specializes in creating small-scale edge computing AI servers that are quiet, energy-saving, and optimal for office hardware and software architecture. Used in conjunction with Fine-tune Expert, a training software in DeepMentor's pre-installed GAI application software package, DeepExpertTM, as well as the training counseling curriculum, enterprises from different industries and units of different levels can easily adopt applications that cater to their internal needs.Jack Wu, CEO of DeepMentor, believes that the ability to perform inference using LLMs with 7B or 13B parameters is an important step in advancing AI projects. First, even if medium or large-sized enterprises have sufficient financial resources, it may not be easy to obtain a project budget of more than ten million New Taiwan dollars if there is no supporting data to prove the viability of the project. Whereas, Mentor-100's favorable pricing is very well suited for companies to conduct early-stage proof of concept (POC) on a small scale internally. For schools, research institutes, and small and medium-sized enterprises, LLMs with 7B, 13B, or 33B parameters are more than sufficient for relatively simple usage scenarios or for performing POCs. In these cases, it is not necessary to use an LLM with 176B parameters.It is worth noting that DeepMentor, as one of the few companies focusing on providing generative AI solutions with a considerable track record, was invited to participate in the testing and promotion of the TAIDE program, a Taiwanese LLM in traditional Chinese announced by the National Science and Technology Council.Six Usage Scenarios Accelerate Implementation of Generative AIDeepMentor's DeepExpert solution has two unique features. First, depending on their business needs, customers can choose to use open-source LLMs of different types and parameters, such as Meta's Llama 2, or FFM, a LLM licensed by DeepMentor's partner TWS and pre-trained on traditional Chinese corpuses. Second, for the hardware architecture, DeepMentor is working exclusively with Phison Electronics in using their NVMe module, which is specifically designed for generative AI training and can overcome the memory capacity limitations of current GPU cards. This allows AI models to be trained with just two NVIDIA RTX A4000-ada GPU cards instead of the more expensive NVIDIA A100/H100 chips. This feature can significantly reduce the overall costs, allowing even small and medium-sized enterprises or academic institutions with limited budgets to take on generative AI projects and see the results of inference in only approximately two weeks.Leo Yang pointed out that in addition to the DeepExpertTM solution, DeepMentor also offers pre-trained and optimized AI application modules for six common usage scenarios, namely Document Expert, Code Expert, Customer Service Expert, Meeting Expert, Image Expert, and Fine-Tune Expert. Coupled with the self-developed and easy-to-use No Code tool, these modules help enterprises quickly integrate their own data to perform training and inference of their proprietary AI models. As a result, to date, they already have government agencies, financial institutions, publicly listed IC design companies, well-established enterprises from traditional industries, and retailers running point of business (POB) testing with DeepMentor to verify DeepExpertTM's outstanding capabilities as a one-stop generative AI implementation solution.DeepMentor has been working with Taiwan Tech Arena (TTA) since 2018 and has participated in a number of business matchmaking events, technical presentations, etc. The collaboration has been helpful in raising the company's profile and securing venture capital investment. DeepMentor hopes to maintain a close and cooperative relationship with the TTA in the future to lay a solid foundation for expansion into overseas markets.Enterprise-level GAI On-Premises solution of DeepMentorPhoto: DeepMentor

During the three-year pandemic, food businesses had been impacted by decreasing in-person dining and government endemic prevention policies globally. As a result, they have been collaborating with delivery platforms to sustain their survival and increase revenue. Despite increasing diversity in delivery services, people began dining in restaurants or ordering takeout again after the pandemic eased off. To avoid hefty platform fees, food businesses are seeking collaboration with other platforms. They hope that by diversifying delivery channels, they can improve their profit margin and the overall revenue.Bogi Huang, Chief Operating Officer of DotDot Global, pointed out that with the advent of the post-pandemic era, the top two delivery platforms in Taiwan have started offering takeout services. However, businesses still have to pay a fee as high as 18% to 20%, which significantly diminishes the profit of food businesses. These days, we find that businesses are working hard to attract new customers and meet the demands of regular customers. Therefore, apart from maintaining partnership with delivery platforms, they also indicate additional ordering channels on their menus for regular customers to avoid incurring high platform fees. DotDot Global has launched a smart ordering system that has been integrated with LINE, and in conjunction with a complete membership management and payment system. This system has been adopted by chains such as 50 Lan and Old God Kung Food Hot Pot, with more than 10,000 customers.DotDot Global Maximizes Popularity of LINEFollowing the rapid rise of delivery platforms, numerous takeout system solutions for the food industry have emerged. During the pandemic, many cloud-based point of sale (POS) providers introduced online ordering modules to meet a variety of operational demands. Unfortunately, they did not become mainstream systems.Upon in-depth analysis, DotDot Global identifies two major challenges that are hard to overcome. First, online ordering systems are designed for general restaurant operators and are therefore, less applicable to vastly different food businesses like bubble tea shops, and street vendors. Second, cloud-based POS providers are not familiar with consumers' ordering needs. Most online ordering modules are designed to facilitate business management, causing the interfaces to be less user-friendly. As a result, they struggle to attract consumers to adopt them.Huang said, "When entering the food market, we decided to launch our own online ordering service through LINE because it is the most popular app in Taiwan." Consumers can order online conveniently by adding the official LINE@ account of the vendor. The platform offers takeout and delivery services, as well as online payment like LINE Pay and JKOPay, making it extremely convenient for both food businesses and consumers. As businesses are facing labor shortage, online payment can eliminate the need to handle cash, make change, and save businesses from dealing with abandoned orders. Furthermore, DotDot Global has also collaborated with many logistics companies to offer delivery service for food businesses without charging high platform fees.From Philippines to Entire ASEAN MarketDotDot Global offers a one-stop solution for food businesses, covering the POS system of stores, online ordering, in-store WiFi, digital payments, integrated delivery services, food delivery logistics, and marketing strategies for attracting customers. Food businesses can customize these services according to their needs. Take the online ordering system as an example. For stores that have limited operational space and staff, DotDot Global provides cloud-based order-taking and printing machines. Once the equipment receives an order from an online platform, it automatically prints the receipt, and the store can prepare the order on the receipt without changing their workflow. This process is also very easy to learn.The LINE ordering service introduced by DotDot Global caters to the needs of different types of food businesses. Over the years, it has gradually incorporated various customization settings into its ordering system. Take bubble tea shops as an example. The online ordering system provides options for different sugar and ice levels. For braised food shops, the system offers a discount option of three products for NT$50. After its launch, the LINE ordering service immediately attracted users with all kinds of dining preferences. Furthermore, in 2023, DotDot Global introduced the SoftPOS payment service, adding contactless credit card payment to existing POS machines. Dine-in customers can safely making payment without any physical contact.Huang pointed out that DotDot Global was founded in 2014 and has since joined two to three accelerator centers. In recent years, there has been noticeable growth in Taiwan's entrepreneurial environment. The number of accelerator centers has significantly increased since ten years ago, offering a more diverse range of services for startups. Whether it is acquiring venture capital, reducing time to market, or transforming creativity into actual products or services, these resources provide tremendous help that can significantly increase the success rate of startups.DotDot Global recognizes the immense global opportunities in food delivery and takeout industry. After achieving notable success in the Taiwanese market, DotDot Global plans to expand its operations overseas, starting from the Philippines. DotDot Global is currently conducting proof of concept (POC) verification with Philippine partners in local food courts, and has received positive feedback overall. The company plans to expand into other food industries in the future.

STMicroelectronics (NYSE: STM), a global semiconductor leader serving customers across the spectrum of electronics applications, is introducing its comprehensive ecosystem offer for companies to transform their products with edge AI. The announcement of the ST Edge AI Suite, an integrated set of software tools free-to-use with ST hardware, takes the offer to customers one step further, enabling them to jumpstart the design and deployment of billions of connected, autonomous things embedding artificial intelligence locally. The ST Edge AI Suite will simplify the development of customers' AI solutions by exploiting ST's broad range of hardware (general-purpose and automotive microcontrollers and microprocessors, smart sensors) and related tools for embedded AI optimizations. It will expand and integrate the multiple software tools, evaluation, and development kits introduced over the past 10 years while leveraging the existing AI ecosystem of machine learning (ML) frameworks and key partners (such as Nvidia and AWS)."We are moving towards a world with tens of billions of connected, autonomous things bringing value and convenience to their users throughout all aspects of consumer life and enterprise productivity. To achieve this, AI algorithms will need to be run both in the cloud and on-device, at the edge across a broad range of devices: smartphones and connected personal devices, smart home and building control systems, industrial machines, cars, and many more," said Jean-Marc Chery, President and CEO of STMicroelectronics. "ST products are already at the core of all those devices, but it is their combination with the industry-leading, free software suite we are announcing today that will make the difference. This combination will enable the transition to a more intelligent edge, empowering customers of any size to deploy edge AI more easily and build their vision of this connected future leveraging ST's hardware portfolio."A preview of the ST Edge AI suite capabilities was presented today at ST's online Edge AI Summit. ST's industry-leading offer will empower embedded developers who want to create optimized machine-learning models, data scientists who want to run their models on an embedded device, and product designers and creators who want to redefine product greatness.With free access, ST will enable customers large and small, pooling resources and knowledge into a community-driven approach. The Suite will further enable this transformation by federating the tools and their users around a broader edge AI community.The first release of the ST Edge AI suite will be available in the first half of 2024.More information about the benefits of the adoption of edge AIEdge AI is a crucial technology for businesses to transform their products in today's connected world by bringing intelligence and decision-making capabilities closer to the data source. This offers numerous benefits in terms of speed, power consumption, privacy, security, and cost-efficiency empowering businesses to create more intelligent, responsive and efficient products that meet the demands of today's fast-paced and data-driven world.Examples of businesses transforming their products with ST:15-40% performance improvement for washing machines:A major home appliance maker is currently adopting this solution and we should see their product on the market next year. The first machine learning algorithm is creating a virtual sensor approach, estimating the weight of the clothes to be washed based on the motor current measurement. Another machine learning algorithm is collecting data from a 6-axis motion sensor to enable drum collision avoidance by calculating if the drum will touch the outer shell of the washing machine. Based on the algorithm input, a program drives the motor using exactly the current needed and adjusts the water and detergent used to save between 15 and 40% energy and water for a washing cycle. Both algorithms have been developed with NanoEdge AI and are running on an STM32G0 MCU together with an ST 6-axis motion sensor.Ultra-low-power PC activity monitoring:The HP engineering team worked closely with ST to develop and train AI models that recognize different user activities based on device and user motion. Multiple use cases were addressed, including scenarios where the laptop is placed on a table, on the user's lap, or carried inside a bag and taken out. This helped create an AI model specific to HP devices that was put on a smart 6-axis motion sensor. But the really interesting part here is the power consumption. This sensor is running an edge AI algorithm at 34 microamps. This allows HP computers to detect changes and respond accordingly. And most importantly, conserves the battery power for more critical tasks.EV motor operation and maintenance optimization:ST is working with the HPE Group to optimize the operation and maintenance of motors in electric vehicles. The challenge here was to monitor the internal temperature of the rotor of an electric motor in actual use so that power output could be optimized for more efficient and safer operation. This is something that could be done in a lab with the rotor exposed but is not possible in an actual running motor in a vehicle. The solution was to train a model and build a virtual temperature sensor with edge AI to estimate the internal rotor temperature from the external temperature measurement. The algorithm runs on the microcontroller that controls the motor – a Stellar automotive MCU. The same MCU also runs an AI algorithm that detects potential anomalies through the analysis of vibrations. The same approach can be used with other critical components, like EV batteries, where the internal temperature of the battery is not practical to measure but an edge AI model can simulate it from an external measurement.Additional technical informationST's strategy on AI relies on the availability of a comprehensive, integrated set of tools (some of them already available today), technical and educational examples, and an innovative, unified optimizer of embedded AI solutions called ST Edge AI Core Technology. The ST Edge AI Suite addresses the needs and requirements of different profiles, like Data scientists, embedded SW developers, and HW System Engineers. The suite is easy to use, with a simple and intuitive interface, available in different fashions (Desktop, CLI, Web, API).*ST Edge AI Suite works across multiple ST hardware platforms: will be working across: STM32 general-purpose MCUs, including the already announced portfolio with AI hardware acceleration, STM32N6 and STM32 MPUs built for industrial applications; Stellar automotive microcontrollers, supporting carmakers in their transition to software-defined vehicles with predictive maintenance of the electric powertrain to extend vehicle lifetime or battery management systems to maximize energy efficiency embedded intelligent sensors (based on intelligent sensor processing units, or ISPU, machine learning cores, or MLC, as well as leveraging Time-of-Flight sensors for advanced imaging), ideal for applications in industrial, automotive and anything from wearable accessories to high-end personal electronics applications. All are supported by a broad range of evaluation and development boards. *A critical component of the ST Edge AI suite is ST Edge AI Core which brings together all the SW and tools engineers need at each step of their project: The ST Edge AI Core can import ML and NN algorithms from the most widely used ML frameworks, provide a detailed analysis, optimize the algorithm for the selected devices (sensors, MCU, MPU), validate against the original model, and finally map the resulting embedded AI solution on the selected device. It will be possible to benchmark the same AI algorithm on different platforms, in pure SW or exploiting specific HW accelerators, to assess accuracy and inference time in a few clicks.*NanoEdge AI Studio autoML tool becomes free for STM32, and is now available for all ARM Cortex-M based MCUs: In parallel, ST's autoML tool NanoEdge AI Studio is getting an upgrade to the benefit of customers globally: its use will become free. The deployment of libraries created by NanoEdge AI Studio will now be at no cost for unlimited deployment on any STM32 microcontroller. In addition, as NanoEdge AI Studio targets all ARM Cortex-M-based microcontrollers, clients will now be able to build and deploy libraries, including unique on-device learning, on other ARM Cortex-M microcontrollers under a special license agreement.ST Edge AI Suite

Crypto Quantique, a leading quantum-safe cybersecurity solutions provider, is delighted to announce a strategic partnership with Blaitek, an AIOT smart-home technology company, as part of its strategic expansion in the Taiwan market.This newly formed commercial alliance is set to leverage the advanced capabilities of Crypto Quantique's QuarkLink software, facilitating secure connectivity for businesses seeking to integrate IoT products and utilizing Blaitek's cutting-edge (WiFi) technologies with cloud services. This collaboration presents a streamlined approach for customers to seamlessly incorporate innovative features into their products and conduct secure over-the-air updates throughout the entire life cycle of their devices. Notably, this is achieved without the need for substantial investment in engineering resources or acquiring in-depth knowledge of chip-to-cloud security.Proactively anticipating the quantum computing era, Crypto Quantique is enhancing the resilience of QuarkLink through the integration of post-quantum cryptography. These quantum-resistant techniques are designed to ensure the sustained efficacy of security measures, even in the face of potential quantum-powered attacks.In a landscape where over 20 countries worldwide are introducing stringent IoT security regulations, including the forthcoming EU Cyber Resilience Act, which mandates a baseline security level for compliance or risk financial penalties, Crypto Quantique's chip-to-cloud IoT security emerges as a crucial solution. This not only ensures compliance with evolving regulations but also mitigates risks across global supply chains.The collaboration between Crypto Quantique and Blaitek marks a significant stride toward providing robust, future-proof solutions in the rapidly evolving landscape of quantum-safe cybersecurity and IoT connectivity.

Providing health workers with light and handy portable devices is becoming a key strategy for service improvement in the healthcare industry. ASUS has already developed a complete product roadmap in this field through its longstanding investment in smart healthcare. The recently released LU700/LU710 series of handheld ultrasound products in particular realizes the vision of mobile healthcare providing physicians with a lightweight, high resolution, and long battery life scanning solution suitable for a wide range of scenarios.Ultrasound is an indispensable medical imaging instrument for hospitals. The ASUS LU700/LU710 handheld ultrasound is a light, compact, wireless, and full-featured solution with 5 different probes that make Point-of-Care Ultrasound (POCUS) a reality. Health workers can now perform an ultrasound examination on patients in different medical scenarios such as the ambulance, emergency room, outpatient clinic, disaster area, or rural area to ensure they receive the best care. The improvement in treatment efficiency allows for the optimization of medical resources.Joe Hsieh, ASUS COO and Global Senior VP, said that medical resources and the time of people seeking treatment are both very valuable. In most outpatient clinics, patients must queue separately for an ultrasound exam. If every physician conducting outpatient clinics is equipped with an ASUS handheld ultrasound unit, they can be scanned during the consultation. This translates into great savings in treatment time and optimization of medical resources. The rapidly aging population of Taiwan means that ASUS handheld ultrasound units can also be in rural scenarios such as medical treatment, home care, and community care.The ASUS LU700/LU710 handheld wireless ultrasound unit incorporates several features designed for the requirements of the above healthcare scenarios including wireless lightweight design, long endurance, as well as support for the four major operating systems (iOS, Android, Windows, ChromeOS). The five probe types (Convex, Linear, Microconvex, Phased Array, Endocavity) satisfy the scanning requirements for most parts of the body. The product's innovative design has lent itself to a variety of applications. For example, ASUS partnered with the Yun-Lin Branch of National Taiwan University Hospital and the Yunlin County Government to make improvements to the first-aid process. Paramedics can now use the ASUS handheld ultrasound device to examine patients as they are being transported by ambulance to the emergency room. The ultrasound imagery is transmitted over 5G to the remote emergency room so that a physician can oversee the first-aid treatment. Once the patient arrives at the hospital, the physicians already have a full picture of the patient's condition. The seamless transfer of the patient greatly improves their chances of recovery.Another example is the regional healthcare services of the South-Link Medical Foundation. Rural physicians can now use the ASUS handheld ultrasound solution to provide local people with better treatment and diagnosis. Home visits and tele-consultations have been conducted by physicians working with the Foundation to improve the quality of rural care.Large hospitals have also used ASUS handheld ultrasound units to provide rural healthcare services. Shuang Ho Hospital and the Bureau of Health and Welfare, Lienchiang County formed a strategic alliance this year to dispatch health teams to Matsu. The lightweight and convenience of ASUS handheld ultrasound units were exploited by physicians to conduct carotid artery screening for local residents and safeguard public health.Hsieh noted that rural regions, islands, and ambulances are just some of the application scenarios for ASUS handheld ultrasound units. The convenience and high-quality imagery provided by the conduct meet the clinical requirements of many other scenarios as well. He then emphasized that ASUS handheld ultrasound units complement rather than replace large ultrasound instruments. Providing health workers with more options and more suitable tools has always been the goal of ASUS investment in the healthcare sector. ASUS has now completed development on the second generation of handheld ultrasound products. The 128-channel design of the new product will provide better image quality. The advanced AI-assistance function will be an invaluable aid for health workers. The product will allow hospitals to make further improvements to their mobile healthcare services.ASUS Handheld Ultrasound LU700 Series combines wireless portability with long battery life and supports multiple operating systems. It has been applied in various fields, including ambulance services and healthcare in remote areas.

Clientron (TW code: 8119), a pioneer automotive electronics enterprise, has been honored with the "2024 Taiwan Excellence Award" for its groundbreaking "Smart eCockpit of Electric Vehicle." The award ceremony took place on December 6 in Taipei City, where Clientron's innovative product stood out among 948 participating entries. The award, akin to the Oscars of Taiwan Industries, meticulously selects high-quality and innovative products that meet the highest standards. Clientron's success, rooted in advanced research and integrated technologies, secures its consecutive win and solidifies its position as a frontrunner in the automotive electronics industry.Clientron Smart eCockpit features Taiwan's domestic chips at its core; this revolutionary system seamlessly integrates independent technology solutions from both upstream and downstream sectors in Taiwan, offering a wide-ranging suite of features such as the Smart Meter Cluster System, Vision Assistance System, Steering Wheel Control, E-shifter, vehicle control/diagnosis, infotainment systems, and C-V2X applications. At the heart of this innovation is the modular/platform design architecture, with Software Defined Hardware (SDH) serving as the design core. This forward-looking approach empowers manufacturers with the flexibility of secondary development and highly customized services, allowing for the creation of a personalized smart eCockpit that aligns with individual customer needs.The minimalist design seamlessly blends technology and modern aesthetics, featuring a sleek, streamlined mold structure that has passed rigorous vehicle tests. Prioritizing safety, the Electric Vehicle surpasses automotive test requirements for EMC/EMI, reliability, functionality, and safety. The award-winning Smart eCockpit boasts sophisticated features - a stylish 15.6" In-Vehicle Infotainment System, a 12.3" Smart Meter Cluster, a 7" Vision Assistance System, along with Steering Wheel Control and E-shifter - engineered for high performance, stability, and quality, enhancing the overall driving experience.The esteemed "Taiwan Excellence Award," initiated by the Ministry of Economic Affairs, is a resounding endorsement of the dedication to advancing Taiwan's global industry presence. For two consecutive years, Clientron's electric vehicle products have received acclaim from judges, highlighting the brand's commitment to "pursuing innovation, intelligent, and safety." This recognition reinforces Clientron's ethos, encapsulating a design philosophy prioritizing "technological innovation with a people-centric approach.""Clientron has leveraged its extensive experience and system integration technology, integrating diverse industrial resources in Taiwan. This strategic approach aims to craft a smart eCockpit and driving environment, delivering innovative, secure, and reliable solutions to domestic and international automotive industries. Clientron is steadfast in its commitment to pushing the boundaries of technology, solidifying its role as a pivotal player in delivering forward-thinking solutions for the automotive industry." – Kelly Wu, President and CEO of Clientron Corp.The "Taiwan Excellence Award" promotes the brand spirit of "Only innovation can bring changes to life" through AI and sustainable development. Winners are elevated to the national brand team, showing Taiwan as a trustworthy global partner. The award aims to showcase innovative products as models for Taiwan's industry, demonstrating excellence and reliability on the world stage.Demonstrating success in automotive electronics products for e-vehicles, Clientron garners the Taiwan Excellence Award again

The AI revolution is reshaping the world, impacting every industry. AI being rapidly put to use has spurred surging demand for critical components. In particular, GPU being in constant shortage has many supply chain ramifications. Taiwan-based startup AIRA has developed a solution that stands out from its peers on the market to circumvent the GPU shortage. It uses Intel CPUs instead of GPUs to perform precise and instant face recognition, which allowed AIRA to receive the Intel Gold Partner status within just nine months after the company was founded, making it a rising AI star.According to AIRA project manager Chia-Hsuan Hsieh, endeavoring smart image recognition technologies, AIRA introduced airaTrack, a face-tracking solution that captures the entire field in 2022. Its unique security implementations provide intelligent and complete protection for residential buildings, commercial complexes, offices, construction sites, and factories. Distinguished from the market, airaTrack uses Intel CPUs to carry out face recognition with no need for GPUs with ever-increasing prices, enabling significant savings in what it costs to have a system in place.Hsieh added that AI-based face recognition solutions running on GPUs have a slew of challenges to overcome, the first being the cost. A 32-channel video surveillance server comes with a price tag of at least NT$300,000. Including routine maintenance fees, the operating expenses add up. Secondly, the system architecture is complicated. A face recognition system has to integrate multiple software development kits (SDK) to incorporate the functions it provides, requiring considerable time and effort for system development and integration. The third challenge lies in the acceptance check. For a face recognition system to deliver the specified accuracy, the software and hardware must synergize and exert their capabilities to the fullest. A system newly coming online can hardly perform up to standard and pass acceptance checks.Running on Intel CPUs, airaTrack addresses all the above challenges. The SDK-based airaTrack enables significant reductions in the cost and time needed to get the system online, cutting the system setup cost to as low as NT$100,000. Moreover, the lower CPU operating temperature compared to GPUs allows airaTrack to adopt a fanless design, giving rise to higher flexibility in server space utilization and ease of maintenance. More importantly, as an integrated system combining completed software and hardware designs, airaTrack delivers the specified accuracy as soon as it comes online.For its near-perfect accuracy and powerful capabilities, airaTrack is being used in wide-ranging application scenarios. The solution performs face recognition using more than a thousand feature points. Unless the subject has undergone major facial plastic surgeries, airaTrack can deliver high-accuracy face recognition regardless of appearance changes such as makeup and age.Another key feature of airaTrack is continuous face tracking. For example, AIRA's solution targeting factory and retail applications can track faces across cameras. It can identify each face captured in a video frame and archive it as an index. For any selected target, it can search the face archive and find a match in an instant. In the example Hsieh presented, it took airaTrack only about ten minutes to search video footage totaling two to three hours captured by 16 cameras. This can be used to find a missing child in a retail setting and detect worker movements on a factory floor. Not only can the face recognition solution prevent trespassing and ensure factory security, but it can also replace badge access control and enable all kinds of smart employee benefits applications.AIRA also has a solution to address privacy concerns around face recognition. There is no need to import face data before face tracking. The face feature values generated during face tracking are encrypted and protected against reverse engineering. Only AIRA's systems can decode and do crosschecks, thereby guaranteeing privacy.For its high level of privacy protection, system setup flexibility, and system integration, on top of friendly cost, airaTrack is enthusiastically embraced by the market. AIRA is working with multiple international companies and among them, Amazon Web Services (AWS) is a key partner that provides complete technical support in cloud-based AI. Joining forces with AWS, AIRA has developed an AI and IoT integrated solution, to target factory security and smart manufacturing applications going forward. The partnership will enable AIRA to accelerate time-to-market and safeguard enterprise security.AIRA's airaTrack, a full-field face-tracking solutionPhoto: AIRA

Raising productivity and quality is the top priority when manufacturers of all sectors endeavor to boost revenue and competitiveness. To manufacturers, whether in traditional manufacturing or high-tech industries, the most effective way to raise productivity is to constantly look for bottlenecks in the production process, find the causes, and resolve them. By harnessing the power of data, manufacturers can get to the root of the bottleneck and figure out a solution. PowerArena, a startup specializing in deep learning, has developed core algorithms, coupled with big data analytics and prediction, to digitize and visualize human factors that may have been difficult to detect in the past and thereby help manufacturers enhance their overall equipment effectiveness (OEE). According to PowerArena marketing director Dave Chu, humans are still essential workers in manufacturing today, especially on assembly lines. Despite the transition to data-driven decision-making, the complexity of sorting and tracking the massive and intricate process line data makes it challenging for manufacturers to improve production quality and efficiency. It is particularly difficult to quantify the human factors entangled in the data. AI is the solution to these problems.Human factor data are gathered from workers performing tasks on the assembly line. Chu commented that with the rapidly increasing IoT popularity, manufacturers are able to collect complete production equipment data. However, they still have difficulty uncovering the underlying cause of the bottleneck on the process line and in the human workflow. For example, if a process step of a PCB assembly station taking too long is found to be the main reason affecting the station's productivity, current IoT systems can only collect data from the entire station with no detailed information for the managers to make decisions and improve the efficiency.Leveraging AI technologies, PowerArena's solution analyzes the workers' movements captured on surveillance cameras commonly found on factory floors and then helps factory managers identify factors hindering productivity such as overly complex procedures and unhandy tools. It also makes use of the factory's existing mechanisms to help resolve the bottleneck and subsequently connects to the backend ERP system to do the production efficiency analysis for every work order to thereby raise productivity. Not only can PowerArena's solution raise productivity, the same implementations can also be used to improve quality. For example, a Taiwan-based motorcycle manufacturer recently adopted PowerArena's AI system to monitor whether its production equipment thoroughly lubricates the gears and exactly completes each procedure to guarantee its products are of consistent quality and up to standard. If any step or task is not performed exactly according to the SOP, the system will raise an alert to the workstation manager. PowerArena's solution will help the manufacturer uphold its brand reputation and lower future repair and maintenance costs, enabling a win-win situation for the manufacturer and motorcycle buyers. Chu added that manufacturing industries have been able to boost production efficiency thanks to rapid advances of technologies and process techniques. However, after they have increased productivity and quality to a certain level, it becomes significantly more challenging and costly to keep raising the bar. PowerArena's solution makes use of AI to find the human factors in the details and clearly identify the problems so as to effectively bring production line output and quality to a new level.To support manufacturers' edge computing needs, PowerArena's AI system is based on an on-premise cloud hybrid architecture, combining the strength of Amazon Web Services (AWS), which includes Amazon Route 53 and AWS Fargate for enhanced system performance. Amazon Route 53 is primarily used for domain name system (DNS) routing. AWS Fargate is used for building container images. Those are ways of optimizing cross-department collaborations within an organization while satisfying manufacturers' requirements on confidentiality and instantaneity.PowerArena's AI-enabled smart manufacturing solution is a powerful tool for production line engineers. It has been adopted by multiple Taiwan-based heavyweight manufacturers, including Lite-On, Wistron, and Delta Electronics, to largely boost their productivity and quality. Chu noted that in line with the AI in manufacturing trend, PowerArena will continue to strengthen its system performance to help users uncover human factors in the details and optimize the value of assembly line workers.In comparison to traditional management, AI vision enables accuracy, proactivity and instantaneity while eliminating human errors and data gapsPhoto: PowerArena

The online course model, developed over several years, has witnessed unprecedented growth in the past three years, driven by the global pandemic. Various degrees of pandemic prevention measures implemented worldwide have resulted in a significant surge in demand for online courses, attracting professionals from diverse fields to enthusiastically enter the online education sector.Existing social media and e-commerce platforms are not specifically designed for online courses and lack comprehensive management tools. This often puts creators (instructors) at a disadvantage when it comes to customer management. Drawing from its own experience, Havbeat Technology has introduced Havppen, an all-in-one online course system, to address the management challenges faced by creators and effectively convert their website traffic into money.With Havppen, the distinctive all-in-one online course system, Havbeat Technology has been invited to participate in the Startup Terrace Kaohsiung AWS Joint Innovation Center (JIC). This exclusive platform not only grants us access to free cloud resources from Amazon Web Services (AWS) but also enables our IT team to undergo complimentary training, earning certifications in cloud technologies and cybersecurity. This initiative lays a robust foundation for our company's long-term development."Being invited to participate in the AWS JIC program gave us two significant advantages," said Allison Chiu, Co-founder and CEO of Havbeat Technology. "Firstly, the access to free cloud resources and educational training courses has greatly assisted in reducing our operational costs and enhancing the skills of our IT team.""Secondly, the program has enabled Havbeat Technology to establish connections with industries in various regions, fostering a positive cycle of monetizing knowledge. This, in turn, helps enterprises drive digital transformation, aligning with the trends that promote sustainable economic growth, such as SDGs and ESG."Powerful CMS with a deep understanding of member needsSpecializing in helping creators and businesses establish their own online teaching websites within 3 minutes and initiate course sales instantly. Havbeat Technology's all-in-one online teaching system, Havppen, utilizes a no-code approach and incorporates marketing analytics tools. This aids branding companies in seamlessly integrating their online and offline, virtual and physical businesses, facilitating digital transformation.This system, akin to a content-centric storefront, features a comprehensive front-end and back-end for independent management of listings and configurations. This empowers creators and businesses to utilize diverse forms of selling exclusive knowledge, expertise, and experiences, thereby creating greater value and revenue.Enning Yu, Co-founder and Chief Operating Officer of Havbeat Technology, revealed that when they launched the highly praised online sports course platform, HAVBEAT, they observed creators struggling to monetize their expertise. Faced with a lack of integrated tools, these creators were limited to generating revenue solely through YouTube ads. "They reached out to us, inquiring about the possibility of collaboration," said Enning Yu.In response, we decided to introduce Havppen, an all-in-one online teaching system. This platform encompasses features such as article subscriptions, course sales, appointment scheduling, online consultations, live streaming, physical events, and bundled e-commerce. This comprehensive solution aims to address the challenges creators face in monetizing their knowledge while catering to the huge demands of consumers.Since the system launched, it has quickly garnered interest from various customers from different fields, including language education, generative AI, investment, programming, and NPOs. Furthermore, it has even been adopted by schools and small to medium-sized enterprises for remote learning and employee training.In addition, leveraging the robust subscriber data management function of a powerful CMS system, comprehensive data analysis is utilized to segment target audiences. This involves implementing marketing strategies that foster interactions, aiding creators and enterprises in effectively overseeing their subscriber base. Simultaneously, it establishes consumer journeys and enhances customer experiences. This approach extends the monetization of knowledge beyond online courses, delving into integrated realms of both online and offline platforms to create diverse revenue streams."In 2024, our focus is on continually introducing new features while actively promoting the Havppen brand, " said "Firstly, we are set to launch a Marketplace-style platform, collaborating with third-party partners to integrate various tools for enhanced selective purchasing and modular options.""Secondly, we will initiate the Starship Project, aiming to collaborate and promote with representative companies from various industries across Taiwan. By synergizing these two strategies, Havbeat Technology anticipates a robust expansion in its user base.Utilizing a no-code approach and equipped with marketing analytics tools, Havppen, the all-in-one online course system, assists branding companies in seamlessly integrating their online/offline and virtual/physical business, facilitating digital transformationPhoto: Havbeat TechnologyHavppen, the all-in-one system of online courses, aims to address the management challenges faced by creators, transforming website traffic into revenuePhoto: Havbeat Technology

Avilon Intelligence, a leading drone manufacturer, has introduced its new service for solar panel inspection. Through collaboration with Qualcomm, Avilon has developed a proprietary flight control and navigation system integrating cutting-edge electronic chips to create drone products with excellent performance and reliability. Avilon's solution offers a complete end-to-end service for solar inspection powered by its autonomous drone and AI technology, ensuring that from the initial data collection to the final report, every step of the process is handled seamlessly and efficiently. In a recent milestone, Avilon's solar inspection services have been selected by the top five solar energy companies in Thailand using their autonomous drone technology. This strategic approach has resulted in proven outcomes, with Avilon detecting issues in over 7% of the total solar panels inspected. This allowed the company to promptly proceed with maintenance and repairs, which not only significantly reduced inspection costs but also contributed to increased profits from ensuring the efficiency of electrical power generation of solar farms. A highlight of drone inspections is its ability to detect anomalies that might not be visible to the human eye. This level of detail is crucial for timely maintenance and repairs. As a result, the customer can maintain the optimal performance of its solar panels, maximize energy output, and increase return on investment (ROI). This attention to detail not only safeguards the longevity and efficiency of the solar panels but also demonstrates the commitment to providing comprehensive, innovative solutions that truly meet the needs of clients in the renewable energy sector.Avilon's solution offers a complete end-to-end service for solar inspection powered by its autonomous drone and AI technologyPhoto: Avilon intelligenceAvilon's Autonomous drones for solar inspection are equipped with high-quality dual cameras, including both thermal and RGB, to capture detailed imagery essential for an Avilon Solar Inspection in Thailand thorough inspection of solar panels. Once the drone has collected the data, artificial intelligence (AI) utilizes precision-trained data models to accurately detect and identify any anomalies in the solar panels on the detection platform. The data is then autonomously compiled into a report which facilitates the identification and resolution of any issues related to heat distribution and panel efficiency. This method guarantees a comprehensive inspection process, significantly improving the efficiency and reliability of the inspection process.Avilon Intelligence is a member of the 2023 Yawan Cloud Platform × Microsoft for Startups Program and is capable of processing huge amounts of solar power inspection data by leveraging Azure cloud resources and AI processing provided by Microsoft Taiwan while offering maintenance analysis reports to the operators.Customers benefit from the automated anomaly reports as details of the detected anomalies are categorized according to the type of anomaly and the locations of defects are identified in the reports so that the customers can take further action. Customers are also able to access the data and report through the user-friendly online platform, which also has API integration to ensure a smooth and efficient data transfer to the customer's existing platforms.Furthermore, with the support from the Southern Taiwan Industry Promotion Center (STIPC), the joint implementer of Yawan Cloud Platform × Microsoft for Startups Program, Avilon Intelligence was able to establish partnerships with Taiwanese solar power companies and verify the inspection of approximately 14877 m2 of solar energy demonstration site in the southern reign of Taiwan. In the future, Avilon Intelligence is planning to utilize such experiences to provide services in Thailand and Southeast Asia.Contact Avilon Intelligence now to enhance solar panel project efficiency with advanced solar panel inspection drone technology.Through Microsoft Taiwan's Azure cloud resources and AI capabilities, Avilon is able to process large amounts of data Photo: Avilon IntelligenceAvilon's autonomous drones for solar inspection are equipped with high-quality dual cameras, utilizing AI-trained data models to precisely detect and identify any anomaly on the solar panels through the detection platform Photo: Avilon Solar.