The exhibition is scheduled to continue through Friday. Rapidus, Japan's government-backed semiconductor developer, is betting on artificial intelligence-enhanced design tools to give it an edge over its competitors, in an effort to speed up its chip-design process and minimize costs. The firm made the announcement during Semicon, a semiconductor-industry event being held in Tokyo from Wednesday to Friday at the Tokyo Big Sight convention center. Rapidus' newly announced suite of offerings, which will be rolled out next year, includes Raads Generator, an AI-assisted design tool modeled on large-scale language models -- AI systems trained on datasets -- and optimized for 2-nanometer chip manufacturing. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Natural organisms utilize distributed actuation through their musculoskeletal systems to adapt their gait for traversing diverse terrains or to morph their bodies for varied tasks. A longstanding challenge in robotics is to emulate this capability of natural organisms, which has motivated the development of numerous soft robotic systems. However, such systems are generally optimized for a single functionality, lack the ability to change form or function on demand, or remain tethered to bulky control systems. To address these limitations, we present a framework for designing and controlling robots that utilize distributed actuation. We propose a novel building block that integrates 3D-printed bones with liquid crystal elastomer (LCE) muscles as lightweight actuators, enabling the modular assembly of musculoskeletal robots. We developed LCE rods that contract in response to infrared radiation, thereby providing localized, untethered control over the distributed skeletal network and producing global deformations of the robot. To fully capitalize on the extensive design space, we introduce two computational tools: one for optimizing the robot's skeletal graph to achieve multiple target deformations, and another for co-optimizing skeletal designs and control gaits to realize desired locomotion. We validate our framework by constructing several robots that demonstrate complex shape morphing, diverse control schemes, and environmental adaptability. Our system integrates advances in modular material building, untethered and distributed control, and computational design to introduce a new generation of robots that brings us closer to the capabilities of living organisms.

As soft robot design matures, researchers have converged to sophisticated design paradigms to enable the development of more suitable platforms. Two such paradigms are soft-rigid hybrid robots, which utilize rigid structural materials in some aspect of the robot's design, and architectured materials, which deform based on geometric parameters as opposed to purely material ones. In this work, we combine the two design approaches, utilizing trimmed helicoid structures in series with rigid linkages. Additionally, we extend the literature on wave spring-inspired soft structures by deriving a mechanical model of the stiffness for arbitrary geometries. We present a novel manufacturing method for such structures utilizing an injection molding approach and we make available the design tool to generate 3D printed molds for arbitrary designs of this class. Finally, we produce a robot using the above methods and operate it in closed-loop demonstrations.

Designing user-centric mobile applications is increasingly essential in educational technology. However, platforms like MIT App Inventor-one of the world's largest educational app development tools-face inherent limitations in supporting modern UI/UX design. This study introduces the Figma-Enhanced App Design (FEAD) Method, a structured framework that integrates Figma's advanced design tools into MIT App Inventor using an identify-design-implement workflow. Leveraging principles such as the 8-point grid system and Gestalt laws of perception, the FEAD Method empowers users to address design gaps, creating visually appealing, functional, and accessible applications. A comparative evaluation revealed that 61.2% of participants perceived FEAD-enhanced designs as on par with professional apps, compared to just 8.2% for baseline designs. These findings highlight the potential of bridging design with development platforms to enhance app creation, offering a scalable framework for students to master both functional and aesthetic design principles and excel in shaping the future of user-centric technology.

This paper introduces CADgpt, an innovative plugin integrating Natural Language Processing (NLP) with Rhino3D for enhancing 3D modelling in computer-aided design (CAD) environments. Leveraging OpenAI's GPT-4, CADgpt simplifies the CAD interface, enabling users, particularly beginners, to perform complex 3D modelling tasks through intuitive natural language commands. This approach significantly reduces the learning curve associated with traditional CAD software, fostering a more inclusive and engaging educational environment. The paper discusses CADgpt's technical architecture, including its integration within Rhino3D and the adaptation of GPT-4 capabilities for CAD tasks. It presents case studies demonstrating CADgpt's efficacy in various design scenarios, highlighting its potential to democratise design education by making sophisticated design tools accessible to a broader range of students. The discussion further explores CADgpt's implications for pedagogy and curriculum development, emphasising its role in enhancing creative exploration and conceptual thinking in design education. Keywords: Natural Language Processing, Computer-Aided Design, 3D Modelling, Design Automation, Design Education, Architectural Education

Microsoft is taking its superb AI art / visual designer tool, Microsoft Designer, and opening it up to the general public today. The company is also publicizing its intelligent features: AI-generated captions and hashtags, new image formatting for social media, and AI-powered editing tools. We called Microsoft Designer nearly an AI masterpiece when we went hands-on with the tool several months ago, and now you have a chance to try it out for yourself, too. While Designer doesn't fall into the category of the best AI art generator tools, it stands nearly alone with Canva and Adobe's design tools as a way to develop a holistic design from the ground up. You can try Microsoft Designer here.

Open AI, Stable Diffusion and the likes have enabled a range of products to bring AI-assisted copywriting, image creation, and even coding to our fingertips. It was just a matter of time until generative AI made its way over to User Interface design. What if we could generate User Interfaces automatically? To take it even a step further, what if we could predict UIs? It's only recently that these AI-driven interface design tools are becoming commercially available. There's Galileo, Genius, Magician, and probably many more to come. This current wave of'generative AI' might seem pretty new for UI design, but work in this area has been ongoing for years, with notable progress back in 2020.

AI-based design tools are proliferating in professional software to assist engineering and industrial designers in complex manufacturing and design tasks. These tools take on more agentic roles than traditional computer-aided design tools and are often portrayed as "co-creators." Yet, working effectively with such systems requires different skills than working with complex CAD tools alone. To date, we know little about how engineering designers learn to work with AI-based design tools. In this study, we observed trained designers as they learned to work with two AI-based tools on a realistic design task. We find that designers face many challenges in learning to effectively co-create with current systems, including challenges in understanding and adjusting AI outputs and in communicating their design goals. Based on our findings, we highlight several design opportunities to better support designer-AI co-creation.

Over the last few months, I've been captivated by the incredible advances in Artificial Intelligence (AI). From DALL-E's photorealistic artwork to ChatGPT's human-like conversation, AI's potential to revolutionize our lives is something I've been contemplating a lot lately. In one of my recent articles, I discussed the power of AI and its implications for designers. We already see AI being used in products like Photoshop, where it can recognize faces in photos and offer editing suggestions. But it is very rare to find basic design tools that use AI to assist in creating user interfaces.

Artificial intelligence is one of the biggest trends in our industry. Overlooking it might have a huge impact on your efficiency and position in the market. It will help us to create the design very easily and quickly which will also reduce the time. AI tools will be very beneficial for us and will helpful for designers. There are some rumors that Al might take jobs from some people, but the truth is we will need to learn how to use these tools to become better designers in the future. Uizard is a start-up that has developed an AI-powered design tool that enables users to create high-quality designs quickly and easily using natural language input.