The perfect fusion of the world’s smallest fan and advanced thermal-optimized SSD technology for AI computing applications

As global electricity demand accelerates - driven by rapid AI computing growth, rising corporate decarbonization commitments, and increasing focus on grid stability - the power supply industry is evolving from standalone components into a foundational enabler of energy efficiency and intelligent system management. In response to this transformation, MEAN WELL, a leading global brand in standard power supplies, will present a comprehensive portfolio of solutions at COMPUTEX 2026. The showcase will extend beyond traditional power products to include smart lighting and integrated energy management systems, designed to help enterprises enhance energy efficiency, strengthen operational resilience, and advance intelligent and sustainable development

Technology news, product launches and show highlights from the event attendees available for download (PDF).

Mecademic Industrial Robotics, a Montreal-based robot manufacturer in Canada, is redefining the landscape of precision manufacturing through its pioneering work in micro-automation. At the heart of their innovation is the Meca500, a six-axis industrial robot designed with a footprint so compact that it matches the size of a standard sheet of letter paper when in its shipping pose. "Everything that has gone into this design has been aimed at achieving the highest possible precision," said Naveen Krishnan, Director of Application Engineering at Mecademic. "For us, five microns is the ultimate goal." While traditional industrial robots often rely on bulky external cabinets, Mecademic's architectural simplicity integrates the controller directly into the robot's base. This plug-and-work system eliminates the need for large external hardware, saving critical floor space in capital-intensive environments like clean rooms.Unmatched PrecisionMecademic specializes in micro-automation, addressing a market segment that requires extreme precision in a small footprint. Their flagship Meca500 achieves a repeatability of five microns - thinner than a red blood cell. According to Naveen Krishnan, this level of precision is the result of a "ground-up" design philosophy. Unlike systems built from commercially available off-the-shelf (COTS) components, Mecademic vertically integrates its mechanical, electrical, and software designs, using specialized harmonic drives and high-precision encoder systems to ensure reliability and performance.An Open and Accessible ArchitectureAs noted above, one of the company's most significant innovations is the integration of  the controller directly into the robot's base, eliminating the need for bulky external cabinets. This "plug-and-work" architecture allows system integrators to replace complex, fixed Cartesian systems with a  single, more flexible manipulator.Furthermore, Mecademic has adopted an open, language-agnostic approach to programming. Instead of forcing users to learn proprietary languages, the robot can be operated via a TCP/IP interface using modern languages like Python or C#. This lowers the barrier to entry for New Product Introduction (NPI) teams and process engineers who may not be traditional automation experts. For industrial users with a requirement for industrial real-time fieldbus protocols, there is native support for Ethernet/IP, EtherCAT, and Profinet built into the standard system.Targeted Applications and Market StrategyMecademic targets high-tech verticals where miniaturization is the dominant trend, specifically within the semiconductor, medical device, and optics sectors. The Meca500 is particularly effective for tasks that involve handling very small parts typically managed by human operators using tweezers under a microscope, such as assembling medical implants or characterizing sensors. To further address niche demands, the company introduced the Meca500-OB, which uses specialized finishes and light-absorbing materials to reduce reflectivity during sensitive measurement tasks involving lasers and interferometers.Key industries include: 1. Electronics & Semiconductors: Handling small parts for testing, assembly, characterization, and sensor validation. 2. Life Sciences & MedTech: Lab automation, sample handling (microplates/vials), and medical device assembly. 3. Optics & Photonics: Sensitive measurement tasks using the Meca500-OBto prevent reflectivity during laser interferometry.Looking Toward COMPUTEX 2026As Mecademic prepares for the InnoVEX, the company aims to educate the market on how micro-automation can bridge the gap between manual labor and full-scale industrial robotics. Philippe Beaulieu, CEO, and Ammon Liu, Sales Director ASEAN, are expected to represent the firm in Taipei.By replacing capital-intensive manual processes with repeatable, high-throughput robotic solutions, Mecademic provides the essential hardware platform necessary for the next generation of AI-driven, high-precision manufacturing.

As the global technology industry descends on Taipei for COMPUTEX 2026 this June, a Canadian startup is preparing to challenge the fundamental architecture of modern processing. Irreversible, a Montreal-based firm with deep roots in quantum computing, is unveiling a "physics-first" analog in-memory computing architecture that promises a staggering 1,000x reduction in power consumption compared to conventional digital processors.Unlike many silicon startups that originate in traditional chip design, Irreversible’s journey began in the highly constrained world of quantum physics. The core team originally specialized in quantum computing, where they were forced to solve computing problems within the extreme limitations of a dilution refrigerator - an environment where even the slightest heat or noise can destroy a fragile quantum state. Co-Founder Dominic Marchand explains that this background led them to become a "computing company that found its way to designing chips," rather than the reverse. This unique DNA pushed the team to strip away decades of architectural abstractions and return to the most basic laws of physics to find the most energy-efficient ways to process information.The current industry obsession with massive Large Language Models (LLMs) has created a significant energy crisis, particularly at the "extreme edge" where devices must operate on microwatt-class power. Irreversible addresses this by sidestepping the Von Neumann bottleneck, the energy-intensive movement of data back and forth between memory and the processor. By performing calculations directly in memory and maintaining a fully analog signal path, Irreversible also eliminates the power-hungry digital-to-analog conversions that often limit hybrid AI chips. This approach recognizes that while digital logic offers noise protection, the energy required to strictly maintain ones and zeros is a luxury that edge sensors can no longer afford.A critical point of differentiation is how Irreversible compares to other innovators in this space. Marchand notes that while he is proud of the Canadian leadership in analog in-memory compute, Irreversible maintains several distinct advantages. First, the company is memory-agnostic, meaning they are not tied to a single proprietary memory technology and can instead utilize various non-volatile memories and emerging RRAM roadmaps. Second, the company places extraordinary emphasis on its software and simulation tools, which allow their hardware and software teams to work in lockstep. Their proprietary hardware-aware training ensures that neural networks remain accurate by accounting for the inherent variability of analog circuits during the initial training phase.For their up-coming visit to Taipei, Irreversible has set clear strategic objectives to integrate with the world's leading semiconductor ecosystem. A primary goal is establishing high-level connections with semiconductor foundries to gain privileged access to specific memory cells, which are essential for their "physics-first" custom designs. Additionally, the company is actively seeking partnerships with OEMs and solution integrators. By bringing intelligence directly to the sensor site, Irreversible aims to enable "previously impossible" use cases, such as deploying sophisticated AI on small drones or always-on wearable devices that cannot support a traditional GPU. Ultimately, Irreversible arrives in Taipei not just to showcase a chip, but to advocate for a shift in how the world thinks about intelligence. By trading the rigid certainty of digital bits for the natural efficiency of physics, they are proving that the future of AI isn't just about more power - it's about more efficient computing.

As global manufacturing accelerates its smart-factory transition, computer vision is taking on an increasingly critical role in industrial quality inspection. Canadian AI startup DaoAI, on the strength of its innovative AI vision technology, has secured partnerships with international heavyweights including Siemens and BASF. Co-founder and CTO Xiaochuan Chen explains how DaoAI uses "Feature Cognition Inspection" to solve the high false-call rates and time-consuming programming pain points of traditional Automated Optical Inspection (AOI), and reveals plans to actively pursue deeper partnerships with Taiwanese equipment makers and distributors during COMPUTEX 2026.From Academic Research to Industrial Practice: Bringing AI to the Electronics Manufacturing FloorDaoAI CTO Xiaochuan Chen has been working in AI and vision research in Canada since 2014 - right at the inflection point of deep learning. In 2017, he co-founded DaoAI in Vancouver alongside a partner with a track record of successful entrepreneurship, leading a top-tier AI vision team drawn from University of British and University of Waterloo and focused squarely on industrial automation.Chen sees enormous potential for AI in manufacturing across both North American and Asian markets. DaoAI's technology not only lifts production yield but also protects enterprise data sovereignty through its on-premise data architecture. "We understand that in any digital transformation, the security and ownership of data is a core interest for manufacturers - and that's the foundation our technology is built on," Chen says.Solving the Long Programming Cycles and High False-Call Rates of Traditional AOITraditional AOI algorithms running on PCBA (printed circuit board assembly) inspection lines are notorious for high false-call rates. Chen explains that conventional algorithms rely heavily on color matching or pixel-level comparison - when, for example, a resistor and the board substrate are both black, traditional algorithms struggle to tell them apart.DaoAI's core technology is Feature Cognition Inspection. The model is pretrained on a dataset of more than one million images, abstracting what the AI sees into a specialized feature space. The advantages show up at two levels: 1. Multi-dimensional differentiation: the AI no longer compares colors - it precisely distinguishes whether a defect is present on a component within feature space. 2. Continuous learning: the system mirrors how humans learn. If the AI gets a call wrong on the first pass, the inspector's feedback is fed into its memory system, so the next time a similar component appears, the same mistake doesn't recur."We pretrain a PCBA-specific inspection model on real production-line data," Chen explains. "All the customer needs is a single 'reference board.' Without any CAD file or component library, the AI identifies the location of every component, automatically generates inspection regions, and automatically calculates thresholds. Programming can be done in seconds or minutes - the AI takes over the part of AOI that historically required the most human intervention."This kind of fast programming is especially well-suited to high-mix, low-volume production. It dissolves the bottleneck that NPI (new product introduction) phases used to hit, where modeling was slow and dependent on dedicated programming engineers.Solving the Compute-and-Sovereignty Trade-off Without Cloud DependenceFor data sovereignty and information security issues that customers care about deeply - DaoAI runs 100% on-premise. To deliver high performance within the limited compute budget of edge hardware, DaoAI takes a "pretraining + rapid fine-tuning" approach: customers run a pre-tuned, optimized specialty model locally while keeping their data fully secure.Cross-Border Partnerships and the COMPUTEX Strategy: Complementing Taiwan's Supply ChainDaoAI has already established deep partnerships with Siemens (electronics manufacturing and automation platform integration) and BASF (vision analysis applications in chemicals). Looking ahead, Chen is bullish on the Taiwan market and announced that DaoAI will participate in COMPUTEX for the first time this year.DaoAI positions itself as a vision-AI application company, Chen says, and the trip to Taiwan has two strategic objectives: 1. Hardware integration: partner with local Taiwanese equipment manufacturers to combine DaoAI's AI software algorithms with Taiwan's high-quality hardware, delivering customized solutions. 2. Distribution expansion: identify professional distributors and service partners in Taiwan to get closer to local electronics manufacturing customers.Beyond Surface Mount Technology line inspection, DaoAI is also strongly interested in semiconductor packaging and testing and is looking to co-develop new applications with Taiwanese probe and inspection equipment makers - pushing the boundaries of vision AI further still.