Linxens, a global leader in component-based solutions for authentication and traceability, and Dracula Technologies, a pioneer in ambient light energy harvesting, have announced a strategic collaboration to develop next-generation autonomous IoT solutions for traceability and smart labelling applications. This collaboration paves the way for smarter and more sustainable connected devices

BIOSTAR, a leading manufacturer of edge computing solutions, motherboards, graphics cards, and storage devices, proudly concludes a highly successful COMPUTEX TAIPEI 2025 showcase. This year's campaign drew significant attention from global media, industry professionals, and tech fans, highlighting BIOSTAR's strong presence across edge AI platforms, industrial edge computing, and next-gen AI PC solutions

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

Telemarketing, a conventional sales channel, faces substantial challenges, such as a persistent attrition of qualified personnel, elevated labor costs, variable sales quality, and obstacles in scaling operations, despite the widespread adoption of digital transformation in numerous industries.At the second "2025 AI Wave: Taiwan Generative AI Applications Hackathon," the "Cloud Science Network Management" team presented an innovative solution that merges AI with user-centric design to transform telemarketing. This groundbreaking approach won the Eastern Home Shopping & Leisure's "Next-Gen Retail" competition.The "Cloud Science Network Management" team comprises individuals from the departments of Electronics, Computer Science and Engineering, Information Management, and Electrical Engineering at National Yunlin University of Science and Technology in Taiwan. Break away from conventional thinking, they leverage their professional expertise to develop an intelligent sales system addressing market challenges. This system uses AI technology to resolve long-standing industry pain points, while maintaining a humanized interactive experience.The team discovered that traditional telemarketing is confronted with three significant challenges following extensive market research. Initially, corporate profits are significantly impacted by the high costs of labor and training. Secondly, the performance levels of salesmen are inconsistent, and it is exceedingly challenging to standardize sales scripts. Thirdly, personnel recruitment bottlenecks that severely limit sales expansion.Although telemarketing continues to be a significant promotional channel, market research indicates that consumers are evidently opposed to interactions that appear to be overly mechanical. Consequently, the optimal solution must strike a balance between the efficacy of AI and the humanization of interaction in order to establish a sales process that is both strategic and highly consistent, while also ensuring consumers cannot detect they are interacting with an AI system rather than a human representative.To address these challenges, the team developed the "AI Smart Salesperson," a sophisticated solution employing AI technology for telemarketing. The system transforms AI into a highly effective telephone sales representative by incorporating data-driven analysis, real-time emotional assessment, and natural voice interaction technology. The operational workflow consists of four phases: first, inputting basic customer and product information; second, developing personalized sales strategies based on customer backgrounds; third, initiating the calling process where the customer's voice is transcribed using speech-to-text (STT) technology, dynamic responses are generated through a dialogue large language model (LLM), and these responses are converted into natural speech using text-to-speech (TTS) technology; and finally, using an analytical LLM to simultaneously assess customer emotions and responses, enabling real-time adjustments to sales strategy based on immediate feedback.The "AI Smart Salesperson" substantially reduces labor and training expenses while ensuring uniformity and consistency in sales methodologies, significantly enhancing both sales success rate and customer experience. The system's technical architecture is built on Amazon Web Services (AWS) and leverages multiple innovative technologies to ensure reliability and natural interaction. The core technologies include large language models responsible for dialogue generation, strategy planning, and real-time analysis, along with bidirectional text-to-speech (TTS) and speech-to-text (STT) conversion capabilities.For the AWS implementation, the team utilized Amazon Bedrock, a fully managed service that makes high-performing foundation models, to integrate models such as Anthropic Claude for dialogue generation. They employed Amazon SageMaker for machine learning model training and inference, and Amazon Transcribe for automatic speech recognition to enable speech-to-text functionality. The solution's data storage uses MySQL databases, while Amazon CloudFront handles web request delivery. The entire infrastructure runs on Amazon Elastic Compute Cloud (Amazon EC2) instances, providing the scalability and reliability needed for production deployments.This groundbreaking approach received unanimous recognition from judges in Eastern Home Shopping & Leisure's "Next-Gen Retail" category. The system features natural voice simulation for a genuine interactive experience indistinguishable from human interaction, standardized speech, and dynamic adjustment capabilities to maintain consistent and adaptable sales quality, along with a data-driven recommendation mechanism that significantly enhances the likelihood of a successful transaction.Furthermore, customers can promptly activate the platform by importing product information and listings, without the need to construct additional complex infrastructure, as a result of the out-of-the-box design. These benefits not only resolve the telemarketing dilemma that contemporary enterprises encounter, but they also establish a new paradigm for the application of AI throughout the entire industry.

Companies have begun to incorporate generative AI models with CAD drawings, design specifications, simulation data, and other information in order to improve design efficiency and accelerate innovation in response to the increasing competition in the commercial sector and volatile consumer demand. This facilitates the rapid generation of initial design drawings or concepts, reduces the length of product development timelines, and maintains the brand's essence.At the "2025 AI Wave: Taiwan Generative AI Applications Hackathon," "Famous on the Board" (a team name referencing PC hardware culture)unveiled an AI-assisted PC case design platform that addresses user pain points to achieve three objectives: "expediting the design cycle," "maintaining brand consistency," and "enhancing innovation efficiency and diversity of inspiration." This innovative platform combines image generation technology and natural language processing to convert user-defined requirements into structured specifications. This encompasses color, style, shape, material, ventilation, lighting, features, environment, and more, and it delivers high-quality rendered images in real time.The platform reduces communication disparities within the development team, enhances interactivity through real-time previews, enables version management for process traceability and restoration, and supports multiple models to increase rendering flexibility, thereby further alleviating the workload. Furthermore, it received recognition from the jury of Cooler Master's "PC DIY Innovation" category and was granted the Excellence Award.Famous on the Board wins Excellence Award with their AI-powered PC case design platform that blends speed, creativity, and brand identity. Credit: CompanyDriving inspiration diversity and enhancing innovation efficiencyThe "Famous on the Board" solution is distinguished by its ability to automatically document each attribute modification and rendering outcome, generate a visual design process timeline, and allow users to generate a PC case design from inception through the inspiration generation module. This allows users to scrutinize and trace discrepancies among multiple versions, enabling them to immediately revert to any historical version for iteration and optimization with a single click.The design of platform functions prioritizes fundamental features such as inspiration discovery, market trend analysis, design prompt generating, version control, and project collaboration management. A machine learning-generated database includes six key attribute databases essential for PC case design: design style, case material, color style, distinctive design, presentation form, and background atmosphere, helping designers rapidly produce design drafts that align with brand positioning.The AI-assisted PC case design platform employs Amazon Nova Pro, Anthropic Claude 3.7 Sonnet, Amazon Nova Canvas, and Stability AI's Stable Image Core on Amazon Bedrock, a fully managed service that makes high-performing foundation models from Amazon Web Services (AWS). It simultaneously supports natural language processing and creative image generation capabilities, thereby augmenting the intelligence and automation of the design process. React and TypeScript are employed in front-end development, complemented by Tailwind CSS to build a responsive user interface that supports internationalization (i18n). The backend architecture utilizes FastAPI and PostgreSQL 17.4 to guarantee data processing efficiency and reliability, while accommodating extensive asynchronous workloads."Famous on the Board" concluded that the essence of its success is rooted in the team's diverse composition. The team comprises development engineers with technical expertise and individuals from various sectors, particularly the gaming industry, each providing distinct perspectives on the application and conceptualization of AI. The challenging work was completed in under 30 hours through collaborative brainstorming and idea exchange, garnering unanimous recognition from the jury for the team's technical expertise, creativity, and degree of completion.

Smart manufacturing has become a global consensus in the manufacturing industry due to the rapid changes in consumer market demand. The implementation scenarios that incorporate generative AI technology are anticipated to further enhance the efficiency of production lines.At the "2025 AI Wave: Taiwan Generative AI Applications Hackathon," the victor of Chang Chun Group's "Smart Petrochemical Manufacturing" category, "Cloud Ninjas," adeptly developed an intelligent assistant system capable of promptly processing natural voice commands from on-site operators by integrating three key technologies: speech recognition, semantic comprehension, and task scheduling. This unique approach digitizes important operational experience and significantly enhances the natural fluency of human-machine communication via voice-driven operations.The "Cloud Ninjas" proposal's acknowledgment by the judges is ascribed to three primary features: "intuitive," "real-time," and "expandable." This transformation of human-computer interaction from a conventional one-way operation to a reciprocal comprehension and immediate response is facilitated by these attributes, which render the machine that "understands," "delivers," and "learns rapidly."The team meticulously defined a variety of command types, situational actions, and operational scenarios that were derived from real-world industrial contexts during the system design process. These scenarios included traversing from point A to point B, retrieving object A, activating button A, and articulating and reiterating content A. The scenario setting program simulates human operational modes through three state transitions: standby, pondering, and speaking. By employing the aforementioned rigorous designs, this AI machine assistant is capable of not only comprehending language but also autonomously executing the most appropriate action options based on the context.The "Cloud Ninjas", which was initially unfamiliar with one another, resolved to form a group to compete after attending a generative AI workshop from Amazon Web Services (AWS). They specifically targeted the manufacturing industry, which was more familiar to them. Despite the fact that all members possess a level of programming expertise, they are not acquainted with cloud tools, artificial intelligence, or other related technologies. Fortunately, they were able to demonstrate their results in the "2025 AI Wave: Taiwan Generative AI Applications Hackathon" after completing a series of pre-competition training courses from AWS and becoming more familiar with the use of a variety of tools.Throughout the development phase, "Cloud Ninjas" utilized several AWS generative AI services, including the generative AI-powered assistant, Amazon Q Developer to expedite program writing for software development, and Amazon Nova Pro, the multimodal model on Amazon Bedrock —a fully managed service that makes high-performing foundation models available—to attain precise semantic comprehension, response generation, and function calling. Simultaneously, it integrates the automatic speech recognition service, Amazon Transcribe, to convert speech to text, and the AI voice generator and text-to-speech tool, Amazon Polly, to provide natural and fluent vocal responses, thus creating an intelligent voice conversational robot."Cloud Ninjas" also integrates a real-time query response demo to autonomously search the Internet for user questions and return detailed information and related links in terms of generative AI technology. The team anticipates that these capabilities will expand to include high-value applications, such as immediate decision-making recommendations and operation manual searches.The global manufacturing industry is anticipating the attainment of more flexible operational objectives and increased efficiency through smart manufacturing as the world undergoes a tide of digital transformation. The "Cloud Ninjas" solution is a prime example of how generative AI is employed to develop AI assistants, serving as a key engine driving digital transformation in manufacturing.