Two subsidiaries of AUO Corporation—AUO Digitech and AUO Envirotech—are set to showcase a suite of AI-powered sustainability technologies at Automation Taipei 2025. Under the theme of data empowering sustainability, the companies will present integrated solutions spanning AIoT, energy management, carbon monitoring, and smart manufacturing, aiming to offer end-to-end digital transformation and decarbonization for the industrial sector.
White-collar roles face mounting risk from artificial intelligence (AI), but AI-powered robots remain unable to fully mimic human capabilities. The gap is pushing more Gen Z workers toward vocational and trade careers.
In a groundbreaking move signaling a new chapter in cloud infrastructure partnerships, Meta has reportedly signed a multi-billion-dollar, six-year agreement with Google Cloud, committing to spend over US$10 billion to accelerate its computing capabilities for AI development.
Taiwan is emerging as a new battleground for humanoid robotics, with Shenzhen-based Ubtech Robotics Inc. and Dobot Robotics entering the market through local distributor Aurotek Corp. They join Germany's Neura Robotics, represented by Kenmec Mechanical Engineering, and Taiwan's Techman Robot, which recently unveiled its first humanoid model, signaling intensifying competition in the sector.
Tesla's once-hyped Dojo supercomputer project—touted as a bold leap into custom-built AI infrastructure—appears to have reached a dead end. CEO Elon Musk confirmed via social media that the Dojo team has been disbanded, calling Dojo 2 a "dead end." However, he added that a potential "Dojo 3" could still emerge, possibly in the form of a single mainboard integrating a large number of AI6 system-on-chips.
Taiwan's MPI Corporation is set to benefit from a major shift in semiconductor testing, as global cloud providers ramp up custom AI chip development and drive demand for advanced wafer probe cards. Starting in 2026, Google and Amazon Web Services (AWS) are expected to lead a surge in CoWoS advanced packaging capacity, powered by their in-house AI application-specific integrated circuits (ASICs). These chips have already progressed from 7nm to 5nm and 4nm, with the next wave targeting sub-3nm nodes.
