Designers often encounter friction when animating static SVG graphics, especially when the visual structure does not match the desired level of motion detail. Existing tools typically depend on predefined groupings or require technical expertise, which limits designers' ability to experiment and iterate independently. We present Decomate, a system that enables intuitive SVG animation through natural language. Decomate leverages a multimodal large language model to restructure raw SVGs into semantically meaningful, animation-ready components. Designers can then specify motions for each component via text prompts, after which the system generates corresponding HTML/CSS/JS animations. By supporting iterative refinement through natural language interaction, Decomate integrates generative AI into creative workflows, allowing animation outcomes to be directly shaped by user intent.

Christopher Tidy was 10 years old the first time he took apart an engine. The carburetor--the block of machinery that supplies a gas engine with fuel and air and helps to spark ignition--was a mess. It was blocked with thick layers of congealed fuel and dust. Tidy saw the problem and just happened to have some tools nearby and a burning curiosity about how exactly this thing worked and what he could do to fix it. That quickly turned into an attempt "to assemble a kind of Frankenstein engine" out of the parts of many discarded petrol engines. He disassembled the rumbling machine piece by piece until he found the offending parts, then doused the carburetor in gasoline, followed by water and dish soap, then scrubbed it clean with a toothbrush.

Did you know TNW Conference has a track fully dedicated to exploring new design trends this year? Check out the full'Sprint' program here. "Our intelligence is what makes us human, and AI is an extension of that quality." The human species has performed incredible feats of ingenuity. We have created beautiful sculptures from a single block of marble, written enchanting sonnets that have stood for centuries and landed a craft on the face of a distant rock orbiting our planet.

Artificial intelligence and conversational computing platforms are no longer the sole domain of big businesses. Voice-computing technology can help a small or medium-sized business owner make interactions with customers more valuable. For one thing, voice computing technology can help improve customer service and efficiency by allowing customers to quickly and easily have a conversational experience with a business without the need for in-depth technical expertise. In the simplest terms, conversational computing is when you talk to a device and it talks back to you. Chris Messina, product designer and the inventor of the hashtag, has a bird eye's view of changes in the way we have conversations. We can use a variety of interfaces (voice, screen, messaging, etc.) and then carry the conversation to other interfaces without losing a beat or starting over.

We propose a new low-cost machine-learning-based methodology which assists designers in reducing the gap between the problem and the solution in the design process. Our work applies reinforcement learning (RL) to find the optimal task-oriented design solution through the construction of the design action for each task. For this task-oriented design, the 3D design process in product design is assigned to an action space in Deep RL, and the desired 3D model is obtained by training each design action according to the task. By showing that this method achieves satisfactory design even when applied to a task pursuing multiple goals, we suggest the direction of how machine learning can contribute to the design process. Also, we have validated with product designers that this methodology can assist the creative part in the process of design.

Artificial intelligence (AI) has a perception problem, as many people think of the technology primarily as a job killer. However, collaboration between humans and AI opens the opportunity of putting the design and manufacturing of goods of all kinds on a new, better foundation by curating intelligence. That's why we should rethink our expectations for machine intelligence and how it will affect our future. The role of a human as the most intelligent creature on earth may not last much longer. Technologies like artificial intelligence and machine learning are taking on operations that could previously only be conducted with human intelligence – and in some cases they're doing even better than we do.

Yury leads a team comprising UX and visual designers at one of the largest Russian Internet companies, Mail.Ru Group. Upgrade your inbox and get our editors' picks twice a month. Digital products are getting more and more complex. In this article, Yury Vetrov explains why we need to support more platforms, tweak usage scenarios for more user segments, and hypothesize more. I've been following the idea of algorithm-driven design for several years now and have collected some practical examples. The tools of the approach can help us to construct a UI, prepare assets and content, and personalize the user experience. The information, though, has always been scarce and hasn't been systematic. However, in 2016, the technological foundations of these tools became easily accessible, and the design community got interested in algorithms, neural networks and artificial intelligence (AI). Now is the time to rethink the modern role of the designer.

In 1990 Tim Bernes-Lee began writing the World Wide Web, an innovation that changed the world as we knew it forever. But as a five-year-old, my mind was being blown by a dancing flower. My brothers, friends and dog were all mesemerised by this incredible new toy that came to life and "danced" (jiggled) when music was played – it genuinely felt like sci-fi magic. Almost thirty years later and our dancing flowers have evolved into AI powered devices like Google Home, Amazon Echo and the new Apple HomePod - able to turn on lights, order pizzas and even tell us jokes. We've replaced dancing flowers in pots with talking bots that look like plant pots.

The rise of artificial intelligence (AI) continues to drive changes in how enterprises innovate and communicate their business. But for the humans and consumers interfacing with products affected by this technology, what will an AI-empowered future look like? What will it feel like? Empowered by rapidly advancing machine intelligence, product designers are rethinking the fundamental principles that guide the way they work. Faced with an evolving and exciting set of problems, product designers are asking a new set of questions to reinvent the model of human-computer interaction. How do we empower people rather than overwhelming or terrifying them?

The rise of artificial intelligence (AI) continues to drive change in how enterprises innovate and communicate their business. But for the humans and consumers interfacing with products affected by this technology, what will an AI-empowered future look like? What will it feel like? Empowered by rapidly advancing machine intelligence, product designers are rethinking the fundamental principles which guide the way they work. Faced with an evolving and exciting set of problems, product designers are asking a new set of questions to reinvent the model of human-computer interaction. How do we empower people rather than overwhelm or terrify them?