？"Empowering the All Electric Society" – that is at the heart of electronica 2026, which will open its doors at the Munich Exhibition Center from November 10 to 13. The world's leading trade fair for electronics will once again present the industry's entire spectrum of technologies, products and solutions helping to pave the way for an All Electric Society. In this interview, electronica's new Exhibition Director Caroline Pannier provides an insight into the upcoming trade fair and the results of a long-term analysis of the industry's assessment of the economic situation.？There are still a good nine months to go before electronica 2026, but preparations are already in full swing. What can you already tell us about the upcoming trade fair, which you will be accompanying for the first time as Exhibition Director?？We are delighted that electronica 2026 will once again occupy all 18 halls of the Munich exhibition center, together with SEMICON Europa, taking place at the same time in two and a half halls. That means that electronica once again covers the entire spectrum of the industry, which makes it unique worldwide. To keep track of everything amid this diversity, we have made the hall layout even more coherent and clear. The semiconductor area has also been extended by an entire hall.As far as exhibitor registrations are concerned, we are at the same high level as for the previous event. All the key players are back on board. There will be a very strong European presence, and we are seeing significant growth in part, from France, Italy, Poland and the UK, for example. There's also been a high level of interest from exhibitors from the U.S. and Asia.？What topics will the trade fair focus on in particular?？In discussions with industry representatives, we have identified three overarching key topics that are currently in the spotlight and that all ultimately contribute to the All Electric Society: artificial intelligence, cyber resilience and energy efficiency. We are currently in the process of refining these themes and identifying sub-topics that are particularly relevant to the electronics industry right now from the user's point of view.？What will be new at the trade fair, and what highlights can you already reveal to us?？As you know, we attach great importance to offering a very extensive supporting program that leaves plenty of room for sharing expertise and ideas, and for networking. That's why the electronica stages, for experts to provide practical knowledge in talks on almost all fields of application, will once again be set up in the respective exhibition areas. A new addition, for example, is edge lab LIVE, a special area on edge computing that is very practice-oriented with workshops and lectures. There are also award ceremonies, pitch formats and several career initiatives. The CEO Roundtable with top-class speakers will kick off the event on Monday evening before the trade fair starts. The electronica Automotive Conference, where trends and challenges in the automotive value chain will be discussed, will also be held on Monday.？Messe München recently published a Future Monitor based on exhibitor surveys from the past 13 years. The companies were asked to assess the current and expected future economic situation in their sector. How do electronica exhibitors see the future?？The evaluation of the long-term analysis produced exciting results for our industry. The electronics companies surveyed are remarkably confident about the future and are far more positive about the economic prospects than the current situation. This optimism clearly shows the key role of the electronics industry. With its solutions and innovative strength, it is helping to tackle current social challenges. Our excellent booking situation underscores just how important world-leading trade fairs such as electronica are. They bring the entire world of electronics together in one place and offer a stage for new products, professional exchange and new impetus.？The next electronica takes place from November 10 to 13, 2026.Caroline Pannier is the new Exhibition Director of electronica. Messe München GmbH

？From November 10 to 13, 2026, the international electronics industry will gather at electronica. This year, the world's leading trade fair for electronics will focus, among other topics, on Artificial Intelligence. From Edge AI to AIoT and machine learning—in Munich, a spirit of innovation, key technologies, and industry expertise will come together in one place to showcase, discuss, and further develop the technologies of tomorrow.？Today, Artificial Intelligence (AI) ranges from Edge and Cloud AI to AI-powered quality control in manufacturing and robotics to smart mobility. AI has long become a strategic competitive factor, helping companies make their processes faster, more precise, and more cost-effective. At the same time, however, the demands on data quality, IT security, and integration into processes and products are increasing. The electronics industry is systematically driving the transformation through AI and strengthening its international competitiveness as a result. "This transformation is visible at electronica, which brings together top decision-makers and developers from around the world, and showcases the entire electronics value chain," explains Caroline Pannier, Exhibition Director of electronica.？Semiconductor industry benefits from AI boom？Recent studies confirm the trend that AI is emerging as the key driver of growth and innovation in the industry. The Capgemini study The Semiconductor Industry in the AI Era, for example, shows that the widespread adoption of AI and generative AI is driving up demand for semiconductors. At the same time, downstream industries expect chip demand to rise by 29 percent by the end of 2026. A study by McKinsey also shows that semiconductor segments that produced components for AI applications grew by 21 percent annually from 2019 to 2023, while the industry as a whole achieved growth of just 6 percent.？Edge AI and AIoT are becoming key factors in the electronics industry？The trending topics of Edge AI and AIoT, in other words, the use of Artificial Intelligence directly on devices and in connected systems, are currently particularly relevant for the electronics industry. Both approaches enable data to be processed in real time where it is generated, such as in sensors, controllers, or embedded systems. That reduces latency, takes the load off the cloud, and improves data privacy, energy efficiency, and reliability.？At the same time, AI and robotics are becoming increasingly important in industrial automation, above all in the field of AI-based quality control. Automatic detection of the smallest deviations and defects on components, printed circuit boards, or in production processes helps reduce scrap, speeds up inspection processes, and ensures more stable operation of production lines. Another focus is on AI on microcontrollers: Advances in TinyML and optimized embedded AI models make it possible to provide intelligent AI functions even on hardware with limited resources.？Bringing hardware and software closer together through AI？At electronica 2026, Infineon, STMicroelectronics, and NXP Semiconductors rank among the particularly relevant exhibitors in the AI sector. Infineon is primarily driving the development of Edge AI and IoT solutions for smart, energy-efficient devices. STMicroelectronics combines embedded processing, Edge AI, and mobility-related applications. NXP Semiconductors demonstrates how solutions for automotive, industrial & IoT, and communications infrastructure can be integrated into embedded systems, microcontrollers, and microprocessors. In the automotive sector in particular, the focus is shifting toward the AI-Defined Vehicle (AIDV): a vehicle in which AI not only optimizes individual functions but also increasingly shapes perception, assistance, interaction, and driving behavior. Together, these companies demonstrate that AI is increasingly being integrated directly into sensors, embedded systems, and industrial applications.？This semiconductor environment is complemented by traditional embedded systems providers such as Advantech and Kontron, which are driving the practical application of AI. Advantech explicitly describes its portfolio as the foundation for AIoT solutions—from sensor nodes to embedded PCs, gateways, and IoT cloud platforms. With its expanded portfolio of IoT, and industrial control and communication solutions, Kontron covers the entire spectrum from modules to complete systems, including software. Both companies are thus creating infrastructural conditions needed to operate AI-based solutions in industrial environments in a reliable, connected, and scalable manner.？A platform that brings together embedded computing, edge technologies, and IoT—as well as developers, decision-makers, and system architects—is edge lab LIVE, which is making its debut at electronica this year. It combines the latest embedded technologies with practical applications and allows visitors to interactively experience edge environments.？Knowledge transfer and networking？At electronica 2026, about 3,500 exhibitors from around 60 countries will showcase their cutting-edge applications and solutions that are paving the way to the All Electric Society. Visitors can learn firsthand about all aspects of Edge AI, AIoT, and related topics across 18 halls at the Munich Trade Fair Center. In addition, a top-class supporting program, featuring an Executive Event with CEO roundtable, expert lectures, or networking events, will contribute to knowledge transfer. The numerous forums, such as the IIoT Forum and the Circular Economy Forum, will also encourage open discussion. SEMICON Europe, taking place in parallel across two and a half halls, will offer insights into the entire semiconductor industry value chain. 

Corning's long-running intellectual property (IP) dispute with China-based IRICO has entered a new phase after the U.S. International Trade Commission (ITC) issued what Corning views as a fair and critical Initial Determination in the company's trade secret case.The ruling marks a critical legal moment in Corning's broader effort to defend its display glass compositions and fusion manufacturing technology against IRICO's unauthorized use of Corning's patented technology, the misappropriation of trade secrets, like engineering drawings, and the deployment of Corning's proprietary technology across its manufacturing lines.For Corning, the dispute is not merely a matter of one product line or one regional market. It is a direct defense of research, process expertise, and IP that underpin its position in high-precision display glass. "This latest decision from the International Trade Commission is clearly affirms our unwavering commitment to innovation," said Brendan Mosher, International Vice President and General Manager, Corning Display Technologies."We believe strong intellectual property protection, fair competition, and trusted partnerships are fundamental to a healthy innovation ecosystem. As a 175-year-old company, Corning is continuously advancing and protecting innovation so our customers across Asia can collaborate with confidence and compete successfully in global markets."April Wins Set the StageThe July 24 outcome follows two important legal wins for Corning in April. On April 7, an Administrative Law Judge at the ITC issued an Initial Determination in a separate glass-composition patent case, finding that IRICO infringed both asserted Corning patents and that the patents are valid.The determination also recommended a Limited Exclusion Order against IRICO, including certification requirements and a prohibition on importing IRICO-manufactured LCD glass substrates that fall within Corning's proprietary composition space, as well as products, such as LCD TVs and monitors, containing such glass.Corning stated that it sought the ruling to protect its proprietary display glass substrates and technology and enforce its intellectual property against infringing products imported into the United States.Corning secured another favorable result in Europe. On April 16, a judge at the Unified Patent Court in Germany ruled in a composition patent case that IRICO infringed Corning's patent and further confirmed the patent's validity. The ruling allows Corning to seek damages and enforcement of an order that could block televisions using IRICO's infringing glass from entering Germany.Together, the April rulings gave Corning added legal momentum ahead of the July 24 trade secret determination and reinforced its stated position that its display glass IP portfolio remains valid, enforceable, and strategically important.Trade Secrets Case Expands the StakesThe trade secret case carries broader significance because it goes beyond a single glass composition. According to Corning, the company had expected a favorable result based on what it described as clear evidence that IRICO stole engineering drawings and improperly used Corning's proprietary technology across its manufacturing footprint.Corning also stated that the trade secret case is important because it could restrict imports of all IRICO glass compositions manufactured using Corning technology, including the 616 composition that closely mirrors Irico's 615 composition found to violate Corning's patents.With the latest ITC ruling now in place, the dispute moves from a composition-patent fight toward a broader question of manufacturing know-how.In advanced materials, this distinction matters. The value of a technology platform is rarely limited to a formula or a finished product; it is embedded in process control, equipment engineering, production discipline, and accumulated know-how developed over decades.A favorable trade secret determination therefore strengthens Corning's ability to argue that the dispute concerns the core of display glass manufacturing, not merely the outer boundary of one patent claim.IP Protection as an Industrial DisciplineCorning's robust legal defense reflects a broader IP philosophy. The company states that invention and innovation have been central to its success for 175 years, and that its leadership in the LCD industry is built on investment, innovation, collaboration, and trusted customer relationships.It also emphasizes that IP protection is not only about safeguarding invention; it is about defending the long-term R&D investment that enables industry-changing products, sustainable customer success, and technologies that enhance people's lives.With a global patent portfolio spanning more than 30 countries and decades of experience and investment in technology commercialization and compliance, Corning frames IP protection as a foundation for trusted innovation in high-standard global markets.This is also where Corning draws a hard line. Its IP philosophy states that when the company finds unauthorized use or misappropriation of its technology, it will take action and will not tolerate situations where its IP is compromised or infringed.And Corning's message to the industry is direct: advanced materials innovation depends on intellectual property protection and fair competition.From Fusion Process to Industry-Wide ImpactThe dispute ultimately points back to the technology at the center of Corning's display glass leadership: the fusion process. Developed more than 60 years ago, the process was created to solve one of the most difficult challenges in precision glassmaking — how to produce large, thin, exceptionally flat glass sheets at industrial scale without compromising surface quality.Unlike conventional glass-forming approaches that may require contact with forming surfaces or extensive post-processing, Corning's fusion process allows molten glass to flow over both sides of a forming structure, meet at the bottom, fuse in midair, and be drawn into a pristine sheet. Because the exterior surfaces remain untouched during formation, the process can deliver the surface quality, dimensional stability, and thickness control required for advanced display manufacturing.Over decades, this manufacturing platform became a key enabler of the flat-panel display industry. Fusion-formed glass helped support the transition from bulky cathode-ray tube (CRT) displays to thin, flat, high-resolution screens, while giving panel makers the precision substrate needed for increasingly complex LCD and TFT processes.Its impact was not limited to material performance. By enabling larger substrates, higher productivity, and more advanced panel architecture, the fusion process also helped change the economics of display manufacturing.For Corning, defending the IP behind fusion-based display glass is therefore not a peripheral legal exercise. It is a direct defense of the technological foundation that helped reshape the global display industry.

Communication – for whatever purpose, be it trying to persuade the electorate to vote for you, to convince your audience to buy whatever product you're selling, to manage client relationships, or simply to become famous online through creating engagement – is, at its heart, an exercise in storytelling. In today's visual-first world plagued with short attention spans and what can seem like an infinite number of e-mails and ads diverting our concentration, being able to fashion compelling video-based stories is increasingly crucial to successful communication. Attempts to automate communication can also seem generic and devoid of empathy and personalisation, consigning them to failure.EQX Lab and its product, EQX Flow, aim to use artificial intelligence to enable the masses to successfully grab others' attention. By inputting a very simple text prompt, users will be able to generate videos that have the potential to go viral. Corporate sales teams will also be able to automate the creation of personalised, cinema-quality videos for client retention purposes.EQX Lab is the brainchild of Benjamin Cheung. He studied computer animation at the Savannah College of Art and Design in the state of Georgia and then moved to Hollywood, where he worked for many of the major animation studios – Square, Disney, DreamWorks, Sony, and Lucasfilm – for roughly 15 years. He worked on Square's Final Fantasy: The Spirits Within, which came out in 2001 and was the world's first photorealistic computer-animated film (where the animated images appear as real-to-life as possible); and when he was at Sony Imageworks, on 2007's Beowulf.But Cheung always knew that he wanted to return to Asia, and so he moved to Taiwan in 2010 to work for an animation company that counted some of his former employers as major clients. He was then poached by a cloud-computing company in China whose president at the time was Taiwanese. Cheung stayed with this company, which specialised in rendering (using a computer to generate [usually 3-D] images) for almost seven years. During this time, he grew the company’s staff count by roughly seven times and its revenue by a factor of 30.Cheung had been the technical director for most of his projects in Hollywood – he was constantly using new tools and had to develop their back-end integration himself. This gave him enough confidence in his technical abilities to launch EQX Lab. He realised that even though there were already plenty of AI video-generation models, they all required a detailed prompt and only generated a somewhat passable video.Instead, what if you could make a professional-quality video with just a simple click, or a single word, or a short sentence? That's what EQX Flow aims to do.The tool is powered by the company's NEXES Engine, an AI pipeline that, from a single piece of user input, generates prompts, writes a script, composes a storyboard, and finally outputs a video. Chain-of-thought reasoning is used to come up with an emotional arc and narrative to the story. The system handles everything internally, so that the user doesn't need any technical knowledge to produce a cinematic result. Moreover, the engine creates five stories and, again using AI, measures how gripping they will be, choosing the best one to increase the chances of the chosen story going viral. (The engine pays particular attention to optimising the first three seconds of the clip, as these are the seconds that decide whether users continue watching or not.)In the current prototype, users input a story idea (something as simple as "play tennis"), and then specify from a list of options the gender of the protagonist; the type of video (e.g., a sports/fitness video); its niche (e.g., a glow-up video); the length of the clip; the type of person that the creator himself/herself is (e.g., a no-nonsense expert); and the 'look' of the clip (e.g., commercial realism, cinematic realism, cyberpunk, vintage film, or anime). Cheung intends to add a 'director's cut' option in a later incarnation of the story engine, where users will be able to emulate, for example, Christopher Nolan's aesthetic.EQX Flow will have two modes: fast and professional. The latter will be more sophisticated and, as a result, also more expensive (in his current prototype, it is about 2.5 times as expensive as the fast model). A tennis ball hitting a player in the face would look passably realistic in the professional-mode video; the fast mode would instead produce stylised visuals in a fraction of the time. Cheung says that directors often prefer the fast mode because it can produce unexpected scenes that they consider to be spontaneous.The tool is also modular: users will be able to stop after each stage (e.g., script generation), tweak things, and then move onto the next stage. Directors who already have a script and storyboard might not need the story engine at all – instead, they will only use EQX Flow’s back end to generate the shots and make the actual video. EQX Flow currently uses Google's generative AI models. This does not allow for the creation of violent, graphic, or adult material, a limitation that is in line with EQX Flow's business model and vision. They are also developing a model-agnostic pipeline, and plan to integrate additional leading AI video models to expand their creative possibilities and to reduce platform dependency.The company's Face-Lock technology can also incorporate photos that users upload of themselves or their desired characters into the videos.If non-specialists can now produce videos, should directors be worried about the future of their profession? Cheung doesn't think so. He says that average directors who don't learn how to use AI tools and don't improve the quality of their work might very well be replaced – but a good director can't be replaced by AI because directing is an art form and good films are unique products that cannot simply be reassembled from pre-existing films. Although Cheung is appreciative of the award, he is aware that he needs more than just the money it brings to fully launch EQX Flow. He is drawing on his network to expand his core technical team, growing his corporate presence in Taiwan, and actively seeking venture capital investors. In particular, he would like to raise three years of funding for research and development, which he will carry out in Taiwan. Cheung says that Taiwan provides a stable environment for his company, with a robust legal framework for intellectual property rights, top-tier engineering talent, and unfettered access to services such as Google.But despite its physical presence in Taiwan, Cheung is focussed on the North American market. Hollywood has the most advanced technology and the most resources for storytelling; Google works best in English; and the story engine has also been developed in English.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.

By now, it's common knowledge that artificial intelligence has sped up coding and is now replacing junior software engineers. But can you really trust the code that AI produces?The answer is a clear no. Programmers are still needed to review the code for bugs of all sorts. Maybe the code hallucinates, meaning that it has the right syntax and looks plausible but attempts to, for example, import a library that doesn't exist. Maybe there are functional bugs, where the code simply produces the wrong result because of a faulty algorithm and these are just the simple errors.Moreover, companies are naturally hesitant to release sensitive or proprietary information, such as customer data, to an AI coding tool.Inferara wants to solve these problems. It wants to give you code on which you can rely, free from any vulnerabilities, and it does this by reformulating the code into mathematical notation. This is all done on the user's own computing infrastructure, so that no code or data is ever shared externally.Georgii Plotnikov is the CEO and CTO of Inferara. Originally from Russia, Plotnikov had been working as a software developer for a decade after graduating from university. Roughly five years ago, he started learning more about static code analysis, which can be likened to a real-time spell-checker for code: it is, essentially, early detection for any bugs or security vulnerabilities in the code.He started developing an idea for a new way to turn static code analysis into a mathematics problem at the end of 2023. Around the same time, he started to explore where he could settle down and legally incorporate his company. Plotnikov decided on Japan, sent his business plan and other documents to the country,s government, and after being awarded a startup visa, moved there in the summer of 2024. (Inferara is a relatively young company, incorporated only in October 2024.)Unlike many AI companies, which focus on their product and want to get them out to market as quickly as possible, Inferara is proud to call itself a research-first company. Its main product is not the code checker but rather Inference, which he describes as "a programming language that uses mathematics to ensure code works exactly as intended".This is also known as formal verification, and being formally verified gives programmers and users an additional layer of assurance that, for instance, cryptographic protocols will keep data secure, or that compilers for programming languages will not make mistakes. It's also important for mission-critical processes, such as those in automated (driver-less) driving systems, financial systems, energy plant controls, and medical devices.In a nutshell, formal verification examines all possible states that the (usually finite number of) variables or parameters can take, in order to ensure that the logic is sound. In contrast, simply testing the system with common values that the variables might take might not reach all possible states, especially as the number of variables increases, and it will definitely not reach all possible states when there are an infinite number of variables (or values that the variables can take).Mathematical proofs can group variables together and reduce the total number of states that need to be explored. They can even use mathematical induction to verify an infinitely large number of states.Traditionally, programmers have needed a sophisticated understanding of mathematical logic to manually perform formal verification. Inferara's Inference programming language performs formal verification as one codes (or as AI codes) and makes it possible for even those with no understanding of mathematical logic to guarantee their code's fidelity. Inference's diagnostics are also developed so that both humans and AI coding agents can interpret them and, thus, use them to improve the code's reliability.Inference builds upon and improves the user experience of using Rocq, a piece of software that can assist in mathematical proofs. Plotnikov says that Inference sets itself apart by working what appears to be slowly. Instead of writing code as quickly as possible, it continually checks the code's correctness as it is being generated. This takes more time but, in the end, is more cost-effective, since it requires fewer calls to AI later on. Plotnikov likens this to the slower, more rational and conscious system of thinking described in Daniel Kahneman's bestselling book Thinking, Fast and Slow.Inferara has now taken the next step beyond Inference: It has created Vibe Checker, an operating system that can encapsulate the entire AI-led code-development process. In addition to its own desktop AI agent, Vibe Checker is compatible with the existing, widely-used coding agents of Claude Code, Gemini, and Codex.Most companies currently using AI-assisted coding typically do so via the cloud (i.e., off-premises). Although the code and data is stored under the programmer's domain, all that information traverses multiple external barriers when being run. Vibe Checker provides its own gateway, comprising its own server and the user’s own cloud computing security model (also known as bring-your-own-encryption, bring-your-own-key, or BYOK). Vibe Checker's most data-secure services will host everything on users' own infrastructure, and is appropriate for those users who have the resources to buy their own hardware. There is total data sovereignty: no data ever leaves the user's infrastructure, nothing is ever uploaded to Inferara's servers, and everything can be run even without internet access. An audit trail also logs every action taken by a coding agent.Vibe Checker does more than just check code. It's a multifunctional checker, or task-agnostic, and can audit any AI-generated system for functional errors and security vulnerabilities. Law firms can use it to summarise case files and contracts; researchers and policy analysts can use it to verify their database queries; finance departments can check their tax filings; hospital clinicians can manage their patient records; and banks and insurers can double-check their regulatory submissions.Privacy is essential in all of these aforementioned applications, and Vibe Checker enables on-premise analysis with links and citations referring back to the original source of the information – in other words, no hallucinations.Plotnikov says that Inferara will clearly benefit from the 500,000 NTD prize money from the Best AI Awards. However, the most important reward is the valuable feedback from those working in the industry, telling them that what they are doing makes sense and has commercial value. The award will also help Inferara get its name out and allow them to approach and demonstrate their technology to potential partners; in fact, Inferara is currently in discussions with several companies in Taiwan. In particular, they are interested in working with Taiwan's semiconductor and chip industry, which can provide the hardware supply chain for their product.In the next few months, they plan to deploy Vibe Checker to several companies who will serve as beta-testers, including several Taiwanese companies. They also intend to establish a legal entity in Taiwan, and have plans to work with the Centre of Industry Accelerator and Patent Strategy (IAPS) at the National Yang Ming Chiao Tung University.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.

Pursuing a PhD might have been the most lucrative decision that Tomasz Matusiak has ever taken.Whilst studying at the Wroclaw University of Science and Technology in Poland's third-largest city, he developed chemical sensors made from ceramic materials based on microplasma generators, and electrical components made from a paste of glass and graphite. Now, Matusiak is using this research to solve a bottleneck that plagues the cutting edge of AI development: moving data between where it is stored in memory and where it is handled in the processing unit (for example, the central processing unit [CPU], which handles arithmetic and logical operations; or more specialised graphics processing units [GPUs], which handle computer graphics and digital images) wastes both time and (electrical) power. This limits the extent to which AI models can be scaled up and, of course, harms the environment.What if one could perform all of the computational tasks right where the data are stored? Matusiak thinks his material can do this, and he has started a company, SemiQa, and produced a system inspired by the human brain, the Analog Neural Network (ANN). Unlike conventional chips, which can reach 80°C and require a cooling system, his ANN system only reaches a maximum of 40°C. SemiQa's goal since its inception at the start of 2025 has been to conquer the universe of data centres, replacing their graphic cards (and the GPUs that power these graphic cards) with ANNs.Matusiak wants to bring back analog processing for its computational advantages. He uses the analogy of a train ride through the countryside. One might look outside the window and see a forest pass one by, followed by a short section alongside a river, before heading back into the forest again. A human brain – the analog system – would see a forest and then not think about it again until it sees a change in the environment (the river), and then once again not actively register the river again until the river has been replaced by the forest. It only processes the changes.But a digital system would constantly process what is outside the window. Analog processing thus saves on energy as it doesn’t process when there hasn't been any change.Likewise, digital processing might allocate a large number of bits to a small integer – for example, even though the number 5 can be expressed in binary with just three bits (101), it might be stored in an 8-bit or a 16-bit structure, where most of the surplus bits are zeroes. Many of the operations performed on these small integers will also result in small integers, so most of the leading zeroes will not change. A lot of memory is wasted.Analog processing can get around this problem by simply storing the 5 in a memory cell as a 5 instead of in eight memory cells as 00000101. (Analog memory cells, unlike digital memory cells, can take on more values than just 0 and 1.)The neural approach is based on a special electrical component called a memristor (short for memory resistor). A traditional resistor follows Ohm's Law, which states that the current (the rate at which electric charge flows) through a conductor is proportional to the difference in voltage (or the difference in electric potential energy, or the work it would take to move a unit of charge provided by, for instance, a battery) across that conductor. Mathematically, Ohm's law is V= IR, where V stands for the voltage, I for the current, and R for the resistance of the conductor, a proportionality constant that indicates how difficult it is for charge to move. The higher the resistance, the lower the current (for a given level of voltage).In a traditional resistor, the resistance doesn't vary with current (or voltage). In a memristor, though, the resistance depends not just on the current (or voltage) but also on the past levels of current running through it (or voltage controlling it). In other words, if the voltage goes up and then goes back down to its earlier level, the current and resistance might not return to their original levels. This ability to take on a range of values of resistance also mean that the memristor can be analog – in other words, that it can represent a range of values and not just a 0 or a 1.In addition to its superior thermal properties, SemiQa's ANN1000 is more power-efficient than other chips, being able to carry out more than 30 TOPS (or 30 trillion operations per second) per Watt of power; standard GPUs or NPUs (neural processing units, which are specialised for AI applications) can only carry out 1-2 TOPS per Watt. (The chip consumes 2.5 Watts of power, and so can carry out roughly 75 TOPS.)It is also naturally faster – ANN1000's latency (the time delay between when the processor requests something from memory to when the processor retrieves it) is 50 times shorter than that of a conventional GPU or NPU.The next step is, of course, commercial-scale production of their chips. They already demonstrated a proof-of-concept of their memristive technology at last year's SEMICON Taiwan, an annual trade show and Asia's largest semiconductor event. They will now create a neural network on silicon and hope to have a product-ready chip tailored to specific applications by the end of 2027. The memristive material, a mixture of organic and inorganic parts, is compatible with CMOS (complementary metal-oxide-semiconductor) technology, which is commonly used in foundries to fabricate chips. Matusiak envisions SemiQa's chips in mission-critical applications where efficient power consumption and processing is highly advantageous. These include autonomous systems, such as drones to be used in war and marine robots. Electric cars can also benefit: GPUs currently account for roughly half the cost of driverless vehicles, and replacing conventional GPUs with SemiQa's chips could reduce the price for consumers whilst maintaining manufacturers' margins. SemiQa also plans to add B2B applications such as data centres to the aforementioned B2C applications. They will tackle this through the ANN2000, a matrix of a thousand smaller ANN1000s.The prize money from the Best AI Awards pales in comparison to the 3 million EUR in pre-seed funding that SemiQa has already raised in Europe. But Matusiak is most grateful for the recognition that the judges have given his company's achievements since they started it just a little more than a year ago. This will also facilitate their collaboration with potential partners – in fact, they are already in talks with two local foundries to deepen their co-operation and scale up production of their chips."If you want something special, you need to work with the special forces," says Matusiak. "Everyone knows that Taiwan is the best in the world."SemiQa also plans to set up a branch office in Taiwan and will potentially hire two business developers in the country in the short term. They also know that they will need more funding, and are looking into perhaps raising money from Taiwanese investors. SemiQa already has a strong relationship with Taiwan, being a member of the Taiwan-Poland Chamber of Commerce and having signed memoranda of understanding with several Taiwanese businesses.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. 

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.

"Integrated circuit" is a fancy term for the chips that control the electronics that make our modern life possible. They are composed of hundreds of thousands or even millions of tiny components, such as transistors, capacitors, and resistors. These components are so tightly linked together on a tiny piece of silicon that, for all intents and purposes, the chip is indivisible – you can't separate it into its individual components.Any mistake in a chip's circuitry could thus render the entire chip unusable. The process of transferring the as-yet theoretical chip design to the fabrication plant (also known as a foundry or chip fab) to produce a photomask (the template that will later be used to create chips en masse) is known as the tape-out, and costs in the tens of millions of dollars.So chip designers have a strong financial incentive to get their designs right on paper before any silicon is involved.But research conducted for Siemens in 2024 showed that only 14 per cent of chips experienced what is called first-silicon success – when the first tape-out results in a photomask and a physical chip that reliably works. This research also noted that this was the lowest success rate over the past two decades. One reason for that might be that many companies are now bringing chip design in-house instead of contracting out to experienced, specialised chip designers.That's where Vincent Bligny's company, Aniah, steps in.Based in Grenoble in the French Alps, Aniah uses artificial intelligence to conduct electrical rule checks (ERCs) for integrated circuits. These checks examine the electrical connections between different components and verify that the chip design can be made, will work, and will continue to work over time. For example, ERCs look for short circuits, when current flows with very little resistance between two components that it was not supposed to flow between; and they look for open circuits, the opposite of a short circuit, where the circuit is not a closed loop and current therefore cannot flow.ERCs also look for large voltage drops (often because of high resistance in the circuit), leading to overheating, noise, and reduced efficiency; and they look for voltage violations, where two components operating at different voltages are connected, potentially damaging the chip (level shifters are necessary to get around this problem). Traditional checkers, such as the industry-standard simulator SPICE (Simulation Program with Integrated Circuit Emphasis), examine how the chip might behave under different voltage, current, or temperature conditions. However, they are unable to sample every potential configuration of the circuit’s components and might miss corner cases (the rare cases where the parameters are at the limits of their expected range). Aniah's OneCheck, on the other hand, covers all of these potential configurations. If there are N components that can take on either high or law values (e.g., N power domains that can be switched on or off), OneCheck will examine each of the 2N potential states to make sure that the chip will still run correctly. It will go over all possibilities, catching problems such as conditional high-impedance (floating) nodes and electrical-overstress violations in chips that mix high- and low-voltage domains. Unlike traditional checkers, OneCheck doesn't depend on luck: it is a static, simulation-free method. Moreover, traditional checkers might find the first instance of a particular type of violation and immediately report back that this violation is present. The designer might fix this one violation, but many other instances of this violation could still remain. OneCheck, on the other hand, will look for all instances of the violation, so that the designer can fix them all at once and not have to rerun the checker.Not only is OneCheck more comprehensive than traditional electrical rule checkers but it is also faster, giving results in minutes instead of days. There is a trade-off, of course: OneCheck finds more false positives than traditional checkers. In other words, it flags more violations that really aren’t violations at all. However, this is something that most chip designers can accept, especially because of another product that Aniah released earlier this year, Amigo.Amigo is an AI agent that goes hand-in-hand with OneCheck. OneCheck flags potential violations and groups them into roughly fifty clusters, organised by their root cause. Amigo then provides users with an explanation of these violations, and takes advantage of natural language processing – users can simply enter "Explain this violation" – to allow users to query and thus debug these violations. But Amigo's support for chip designers goes further than that. It also provides concrete suggestions for how to fix the violations that it has identified, which the chip designer can then validate. It also tells chip designers which violations are the 'lowest-hanging fruit,' whose correction would lead to the greatest increase in the likelihood that the chip will be ready for tape-out. In fact, Amigo quantifies for users just how ready a design is for tape-out, and can quickly adjust this valuation when changes are made (instead of running the entire checking process from scratch).OneCheck and Amigo are therefore a newer, AI-enabled system for electronic design automation (EDA), and Aniah has ambitious plans for developing this EDA technology over the next two years.  They intend to implement parallel fixing by the end of 2026, where the checker can make corrections as it checks. This is a prelude to delivering results in just seconds by next year.Aniah next wants to go beyond OneCheck and simply electrical rule checking to full circuit sign-off – in other words, it wants to be able to verify that physical design constraints are respected. In the long term, Aniah wants to enable continuous sign-off, whereby all electrical rules and physical constraints are constantly satisfied. Currently, sign-off is a hectic scramble at the end of the design process, where bugs are easy to overlook.Their bronze award at the 2026 Best AI Awards came with a prize of NTD 500,000 (USD ~$16,000). The money itself won't help Aniah a lot – they've already raised more than USD $11 million in funding and expect to open a new funding round soon – but the award will open doors with Taiwanese companies and investors, said Allen Chen, Aniah's director of applications engineering. Chen, who is based in Taipei, added that Bligny, Aniah's CEO, has long held Taiwan's technical prowess in semiconductor manufacturing – its world-leading foundries and design houses – in high esteem. This is why Bligny plans on expanding their Taiwanese team, said Chen, who joined the company three years ago and is currently Aniah’s only employee on the island.Aniah currently has one Taiwanese customer, Novatek, but also supports the 200-strong Taiwanese team of Nvidia, an American company. These clients are loyal to Aniah because OneCheck and Amigo offer the fastest running time and the smallest number of false positive alerts, and because Aniah is quickly adopting AI to improve its service.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.

Six months into 2026, the story isn't whether the electronics supply chain has stabilized. It has, broadly. The real story is that it has split into two distinct markets moving in opposite directions, and most procurement teams are still planning as if there's just one. The AI-driven leading edge remains capacity-constrained and pricing-positive, while the mature-node segment is loosening into a genuine buyer's market. Knowing which side of that line each line item on your BOM sits on is the single most useful thing you can do heading into the second half of the year.The Two-Speed Market, BrieflyTSMC is reportedly preparing to raise prices 3–10% on its sub-5nm offerings, and with Nvidia and Apple having already locked in large blocks of capacity through year-end, second-tier buyers are increasingly competing for allocation that may not exist in H2. Memory tells a similar story. Combined output from Samsung, SK Hynix, and Micron is expected to grow sharply by 2030, led by a projected rise in HBM production, but that new capacity doesn't meaningfully arrive until 2027. In the meantime, DRAM and HBM remain the tightest categories in the entire component ecosystem.Mature-node wafer pricing has actually returned to pre-pandemic levels, down 5–8% year-over-year, as Chinese fab capacity comes online and automotive/industrial utilization climbs into the 80–85% range. Consumer electronics demand is stabilizing too, which is easing pressure on mature-node semiconductors and passives.What This Actually Means for Your Procurement StrategyThis is where most H2 outlooks stop short. Here's what to actually do with this picture, category by category.1. Segment your BOM by risk profile, not just by part number.Advanced logic tied to AI-adjacent applications faces a fundamentally different supply reality than commodity discrete or mature-node passives. Treat these as two separate procurement strategies, not one blended approach. A BOM review that groups parts by constrained, stable, or loosening rather than by function or supplier will surface where your actual exposure sits, and it's often not where teams assume.2. Use the mature-node buyer's market now, not later.If you were forced into single-sourcing during the 2021–2023 shortage years, H2 2026 is the window to qualify second sources for those mature-node components while pricing and availability both favor you. This window won't stay open indefinitely. As automotive and industrial utilization keeps climbing toward capacity, the leverage shifts back to suppliers.3. Be strategic, not reactive, on memory buys.Memory is not one uniform story. Leading-edge densities tied to HBM demand carry a real price premium, but previous-generation DDR4 and LPDDR4 may still offer value while pricing is structurally supported mainly at the high end. If your designs can tolerate a prior-generation module, this is the year to lock it in rather than wait and hope for relief that isn't coming until 2027.4. Watch for new procurement categories forming in real time.Optical networking components for AI data centres are moving from niche to mainstream as AI clusters push toward much higher bandwidth per rack. If your roadmap touches high-bandwidth AI infrastructure at all, get ahead of this now. Procurement categories that don't exist yet in your sourcing playbook have a way of becoming urgent overnight once a design win locks them in.5. Rebuild safety stock around true risk, not blanket buffers.Broadly increasing inventory across the board is expensive and imprecise. The more effective move is targeting buffers at the small percentage of components, often a single connector, capacitor, or legacy memory module, that actually drive downtime risk if they disappear. Combine that with forecasting discipline: suppliers increasingly prioritize allocation and pricing based on how credible and consistent your rolling forecasts are, which means forecast accuracy is now a negotiating asset, not just a planning exercise.6. Don't sleep on non-obvious demand drivers.Rising defense spending across Asia-Pacific is quietly adding a new, non-cyclical source of demand for industrial and mature-node electronics, one that doesn't show up in most consumer-electronics-driven forecasts. If your end markets touch defense, aerospace, or industrial automation, factor this in as upside demand pressure, not background noise.The Bottom Line for the Rest of 2026H2 2026 doesn't call for a single supply chain strategy. It calls for two, running in parallel. Where you're constrained, the priorities are allocation planning, forecast credibility, and locking in what capacity you can. Where you're not, the priority is using the current leverage to diversify, qualify alternates, and rebuild resilience before the window closes. Teams that treat this as one undifferentiated “stabilizing market” will miss both opportunities.If you're navigating either side of this, securing allocation on constrained parts or taking advantage of loosening mature-node availability, that's exactly the kind of sourcing challenge our team works through with customers every day. Reach out to your Fusion Worldwide representative and let's talk through your BOM.(Article Sponsored by Howard Tan, Director of Purchasing, China Fusion Worldwide)

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