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Tuesday 21 July 2026
Driving Global Intelligence: Best AI Awards 2026 Wraps Up
The Ministry of Economic Affairs officialized the successful conclusion of the second annual Best AI Awards, held at the Taipei Nangang Exhibition Center Hall 2. This year's event witnessed an extraordinary surge in international engagement, drawing 1,487 competing teams from 36 countries across the globe, which represents a near two-fold growth in foreign participation compared to the inaugural edition. Out of 253 finalist teams, 100 awards were presented to recognize exceptional breakthroughs in artificial intelligence technology and integration.Leading Innovators Secure Top Honors Across Key Industry VerticalsThe competition highlighted highly competitive solutions spanning healthcare, information and communications technology, manufacturing, and education. Eight prestigious gold medals were awarded to outstanding organizations and academic institutions, including Delta Electronics, Kneron, BrainNavi Biotechnology, ZenTech, National Cheng Kung University, and National Formosa University, alongside pioneering international teams from Thailand and Poland. These entries showcased the practical implementation of artificial intelligence, bridging advanced research with market-ready products.Minister of Economic Affairs Kung Ming-hsin. Credit: TCAMinister Highlights Shift From Hardware Dominance to Practical Industry DeploymentDuring the ceremony, Minister of Economic Affairs Kung Ming-hsin emphasized that while Taiwan maintains a critical global advantage in foundational AI hardware such as semiconductors and servers, the next vital phase involves translating this power into practical applications across all sectors. Under the framework of the government's new major AI infrastructure initiatives, the ministry has established over 50 trial production sites with automated AI capabilities and developed models covering 23 core industries. More than 1,000 consultants have been deployed across the nation to actively assist over 2,600 enterprises in integrating artificial intelligence into their daily operations.Emerging Tech Trends Shape the Future of Edge and Agentic IntelligenceThe second edition successfully guided industrial investments toward the frontier developments of Agentic AI and Edge AI, shifting artificial intelligence from a passive responsive tool to an autonomous partner capable of independent judgment. Driven by strong local integrated circuit design capabilities, more than 430 projects focused on lightweight AI architectures to enable real-time processing directly within terminal devices and industrial machinery. Furthermore, 590 teams integrated open-source environments like GitHub and registered on Crunchbase, significantly elevating the international visibility of the technological ecosystem.Extended Business Matchmaking Initiatives Showcase Commercial Achievements at COMPUTEXTo foster substantial commercial partnerships, organizers featured a dedicated industry matchmaking zone during the finals to link venture capital with startup resources. This promotional effort extended into the COMPUTEX exhibition period, where exclusive matchmaking sessions successfully showcased the winning projects to connect the teams with international buyers and global investors. The Ministry of Economic Affairs plans to continue opening institutional pilot lines to support design verification, prototyping, and unified system integrations, ensuring businesses can seamlessly implement artificial intelligence without developing systems from scratch.The Best AI Awards celebrate global excellence in artificial intelligence and IC design, welcoming submissions from innovative companies and brilliant student teams. Following the success of the 2026 edition—advised by the MOEA, organized by DoIT, and executed by TCA—the prestigious competition is officially transitioning into an annual tradition.Offering substantial grand prizes and unmatched industry exposure, the countdown to Best AI Awards 2027 has already begun. Details on the next submission cycle, prize tiers, and eligibility rules will be released soon. Connect with on LinkedIn for the latest official updates and application alerts. Group Photo of the Best AI Awards 2026 Winners. Credit: TCA
Tuesday 21 July 2026
EDABK Brain: A chip in the ear measures heart activity
Cardiovascular disease – diseases of the heart or the blood vessels that move blood to and from the heart – were responsible for an estimated 32 per cent of deaths worldwide, or just under 20 million deaths, in 2022, according to the World Health Organisation. Their takeaway? "It is important to detect cardiovascular disease as early as possible so that management with counselling and medicines can begin."Electrocardiograms (ECGs), a series of peaks that represent each heartbeat, depict the heart's electrical activity over time. An abnormal ECG (compared to one's baseline) can be indicative of arrhythmias, the medical term for irregular heartbeats that, in most cases, are not serious but can sometimes lead to strokes, heart attacks, and death. Patients can wear Holter monitors to continuously measure their ECG, but that entails placing a large number of electrodes (between three and eight, and up to twelve for greatest accuracy) on the skin, and wearing a piece of recording equipment around the neck or waist. Not only can this be inconvenient, but up to half of all patients reported some sort of skin irritation due to the electrodes.Smartwatches can also be used to measure an ECG, but only when both hands touch the device – in other words, they cannot be used for passive, continuous heart monitoring. That's where integrated circuits can help. Students at the Hanoi University of Science and Technology (HUST) are working on an integrated circuit that can continuously monitor the heart's electrical activity through the ear. Such devices are already commonplace, with many people wearing hearing aids or smart hearables for at least some of the day. There are three physical connection points – both ears and one earlobe – the minimum required to measure an ECG.The ECG collected between the ears is useful only insofar as it can then reconstruct what lead-1 ECG, which is the electrical activity as would be measured by electrodes placed on the right and left arms. The lead-1 ECG is also a standard ECG measurement that is used for diagnosis and monitoring arrhythmias. There are generally similarities between the ear ECG and the lead-1 ECG – in particular, the peaks (representing the heartbeats) appear at the same location – but they are clearer in the lead-1 ECG than in the ear ECG.So while the algorithm on the chip must be able to recover the shape of the original lead-1 ECG with as little noise as possible, it should not smooth over any possible signs of abnormality – in other words, it needs to be sensitive enough to detect arrhythmias when they are present.The system is relatively unobtrusive and runs on low power, but using the ear also presents disadvantages. The signal-to-noise ratio is low. In fact, simply shaking one's head or talking will introduce noise into the measurements. Furthermore, special data privacy concerns when collecting biological signals – each user has a unique ‘heartprint’ and some users might be particularly wary of sending such data to another machine – make it imperative that any analysis is done on the chip itself.The user himself can measure his own lead-1 ECG using his two fingers (as proxies for the right and left arms), and measure his ear ECG with the devices touching his ear. All of this is done with electrodes attached to a sensor (with a built-in analog-digital convertor, or ADG) developed by Texas Instruments. Two datasets were created to train the AI calibration algorithm for the conversion between the ear and lead-1 ECGs. Firstly, the team collected its own dataset, measuring the ECGs for 45 patients for 10 minutes each. A synthetic public dataset was also created by modifying an existing large, open dataset of ECGs, the PTB-XL. This dataset doesn't include ear ECGs, so the team added noise to existing lead-1 measurements (in an attempt to emulate the ear ECG) and tried to recover the original, non-noisy lead-1 ECG. The team, which calls itself EDABK Brain, was able to bring the algorithm's latency, or delay time between receiving the ear ECG and producing the lead-1 ECG, down to below 50 milliseconds. Such short times obviate the need to store data from the ear-ECG, for instance. At the same time, they maximised the utilisation of the processing element, meaning that they worked hard to make sure the chip was effective.After prototyping a field-programmable gate array (FPGA) with their IC design, the team trained it on the self-collected dataset. On the two most important metrics, the signal-to-noise ratio and the correlation with the true lead-1 ECG, EDABK Brain slightly outperformed state-of-the-art algorithms. It was edged out by another algorithm – but the HUST model used fewer than a quarter as many parameters as that algorithm did.For another comparison, EDABK Brain's circuit used less power and was more energy efficient than BioGAP, a leading biosensing platform that can measure ECGs as well as other electrical signals in the body. However, BioGAP's circuit has a lower latency time and a high throughput (measured in operations per second).The team behind this chip design, the EDABK Brain Team (the EDA stands for electronic design automation, and the BK stands for Bách khoa, which is in the Vietnamese name of their university,  consists of Phuong Linh Nguyen, a student who graduated from their university last year and is now studying for a master's degree at Télécom Paris (one of the most prestigious French grandes écoles and part of the Polytechnic Institute of Paris), and who spoke to DIGITIMES; and her two former classmates, Thanh Dat Do and Duc Tu Nguyen, both of whom are in their final year in the School of Electronics and Electrical Engineering at HUST; and their supervisor, Duc Minh Nguyen. Having the chance to participate in the Best AI Awards motivates Nguyen and her teammates. Being just students at the start of their scientific career, they were curious to know what industry professionals thought of their idea – does it have potential? Winning the bronze medal is confirmation that it indeed does have potential.Nguyen said that it was also a relatively rare opportunity for them to communicate their ideas in a non-academic setting. Their university was able to send three teams to the finals, which also entailed a trip to Taiwan and interactions with state-of-the-art AI and IC researchers.They will now focus on writing a paper – after all, they come from academia – and preparing patent applications. On the technical side, they want to reduce the number of bits in their resolution – in other words, see whether they can convert the analog signal to a digital one with a fewer number of bits and less accuracy – to reduce complexity and thereby power consumption. The team will also experiment with other electrodes.The Best AI Awards celebrate global excellence in artificial intelligence and IC design, welcoming submissions from innovative companies and brilliant student teams. Following the success of the 2026 edition—advised by the MOEA, organized by DoIT, and executed by TCA—the prestigious competition is officially transitioning into an annual tradition.Offering substantial grand prizes and unmatched industry exposure, the countdown to Best AI Awards 2027 has already begun. Details on the next submission cycle, prize tiers, and eligibility rules will be released soon. Connect with us on LinkedIn for the latest official updates and application alerts.
Tuesday 21 July 2026
Eko Agentic: AI-driven data analytics for optimising retail performance
Artificial intelligence is just an interesting theoretical problem for many scientists and engineers, but it is at its most useful when it directly responds to the needs of its users.That's why Amity Solutions, a component company of Thailand-based Amity Group, developed Eko Agentic, a data analyst for store managers. They were long-standing consultants to one of the biggest retail chains active in Thailand and Malaysia with thousands of stores in the region. Executives at this retailer told Amity Solutions that they had tried to use various AI tools to improve the efficiency of their store management, but that these tools were not adequate for their needs.Store managers, stock replenishers, and other frontline workers on the store floor have to handle numerous disconnected tasks on a daily basis. They might use dashboards to monitor various store performance metrics, but synthesising the disparate information into business decisions can be complicated, with store managers resorting to past experience and guesses. Inexperienced store managers, in particular, might be unable to respond effectively to new situations or to best implement requests from headquarters.What if AI could take over the data analysis from store managers? Amity Solutions developed Eko Agentic to do just this: It is trained with data on how the top-performing store managers across the retailer's large network would respond to various business situations, and then rolled out across other stores, taking into account each store’s particular characteristics. The goal is to reduce extra, unsellable stock; to avoid empty shelves; and to better time and set up promotions. This way, the retailer tries to make all stores as efficient as those run by the best store managers.In its first iteration of Eko Agentic, Amity Solutions identified those stores that consistently outperformed the average, both through looking at store performance metrics and by talking to headquarters. Positive outliers were also identified in different environments – for example, the best inner-city markets (which tend to be smaller) and the best rural hypermarkets (which tend to be larger) – in order to get the widest possible range of data.Amity Solutions then sent teams to perform interviews at each of these stores, asking frontline workers to explain how they would think through various situations. What would they do if sales dropped by 5 per cent year-on-year? Perhaps the store manager would first check the basket size, then check the average value of each item in the basket, and then check for the use of special promotions.AI – and in particular, a technique developed by Amity Solutions called reflective optimisation via automated debugging (ROAD) – then structured these interviews into decision trees that visualised the store managers' train of thought. Most optimisation methods so far rely on large data sets for testing and calibration, but these interviews with store managers at Lotus's produced a smaller data set, something that ROAD's algorithm could work with. This was especially important in the Thai context because most large language models are trained on Western datasets, but differences in culture and the business environment between the West and Thailand (e.g., in the availability of parking lots) meant that other models, trained on larger data sets, weren't necessarily immediately applicable.The model was then applied to each individual store, generating a strategy that had been optimised for each one. Reinforcement learning (a paradigm within machine learning that seeks to optimise the impact of an agent's actions based on continual feedback to that agent from those impacts) is then used to further optimise store managers' strategies.Despite this rather simplistic description (and its correspondingly smaller size), Eko Agentic has been remarkably effective in data analytics. It is cheaper than many other AI tools (such as Claude and ChatGPT), and outperforms other state-of-the-art LLM and AI data analysis agents in an industry-standard set of real-world problems, the Data Agent Benchmark for Multi-step Reasoning (DABStep). It achieved 41 per cent accuracy in resolving DABStep tasks – the highest amongst all such agents – whilst its nearest competitor, Microsoft, only achieved 32 per cent accuracy; Anthropic's, OpenAI's, and Google's systems lagged even further back.Eko Agentic is also now able to outperform human analysts working at the Thai retailer. A blind test was conducted, wherein both Eko Agentic and a human analyst performed an analysis on various real business problems. Store managers then select the better of the two responses, without knowing who composed each one. The first versions of Eko Agentic still performed below a human analyst, but the latest version – the fifth – gives, on average, suggestions that are favoured over those from a human analyst. There are only a few supermarket chains in Thailand, and Amity Solutions is, of course, unable to work with the competitors to the retailer it currently works with. However, their methodology is applicable to other retail applications – and in fact, Amity Solutions is currently using Eko Agentic to help a telecommunications giant in Thailand manage its mobile phone shops. Amity Solutions is also looking for opportunities to apply Eko Agentic to supermarket chains in other Southeast Asian countries.A potential limitation with basing decisions on what the best store managers would do is that one might be limited to – and thus not be able to improve on – how well the best store managers do. In other words, you can interpolate performance but it is uncertain whether you can extrapolate to even superior strategies.Thus, as one of its next steps, Amity Solutions is creating a large behavioural model (LBM) that serves as a stand-in for customers. It is a digital twin that simulates customer behaviour, and models that respond to this LBM can potentially outperform the current best store managers.Amity Group, with offices in Thailand, Malaysia, Singapore, Australia, India, the United Kingdom, and the United States, employs 800 staff members over five companies in various realms of AI. Amity Solutions, the business unit that commissioned Eko Agentic through its long-standing collaboration with the aforementioned retailer, is based in Bangkok and employs 150 employees. However, it was Amity's AI Research and Application Center (ARAC), whose small team of just 15 staff members deploys generative AI solutions across all of Amity's daughter companies, that developed the technology behind Eko Agentic. Currently based in Thailand, they aim to stay at the forefront of developments in AI, says Touchapon Kraisingkorn, the chairman of ARAC and the executive director of Amity – and thus they have plans to expand ARAC to Singapore.Winning at the Best AI Awards is, says Kraisingkorn, validation that they are "one of the world-class labs that creates an effective product and solves real-world problems". The earnings from this award will help them jump-start hiring in Singapore. They are also open to opportunities for collaboration with Taiwanese companies in chips and robotics. The Best AI Awards celebrate global excellence in artificial intelligence and IC design, welcoming submissions from innovative companies and brilliant student teams. Following the success of the 2026 edition—advised by the MOEA, organized by DoIT, and executed by TCA—the prestigious competition is officially transitioning into an annual tradition.Offering substantial grand prizes and unmatched industry exposure, the countdown to Best AI Awards 2027 has already begun. Details on the next submission cycle, prize tiers, and eligibility rules will be released soon. Connect with us on LinkedIn for the latest official updates and application alerts.