Motion Design Animation Basics

Playful Visuals: The secret sauce of viral brands. Your customers will lose interest on your product if you communicate through dry, instructional visuals and static product presentations. But what if discovering a product felt as engaging and delightful as playing on a playground? +60,000x faster – Visuals are processed far more quickly than text. +2x more likely to be shared – Playful content spreads faster. +48% higher engagement – Gamified experiences captivate audiences. >>Your Product is an Experience<< Play evokes joy and triggers dopamine release, enhancing memory, motivation, and emotional connection. When beauty products are presented in a fun and interactive way, they transform from simple cosmetics into immersive self-care rituals. Imagine a vibrant scene: a user’s hands gleefully applying a rich, textured cream, colors swirling in motion, a splash of shimmer catching the light. The product is no longer just a cosmetic; it’s an invitation to creativity, emotion, and self-expression. This visual storytelling captivates the imagination, making beauty routines feel effortless and exciting. + 23% better recall – Learning by doing beats passive learning. + 89% engagement boost – Game-like elements keep users invested. + 22 x stronger memory retention – Story-driven visuals leave lasting impressions. → Hands: The Ultimate Storytellers. Hands express personality, movement, and playfulness, making them powerful tools in beauty marketing. + Hands delicately blending makeup create a sense of artistry and skill. + A playful splash of cream on the skin conveys freedom and fun. + Interactive gestures, swiping, dabbing, or mixing, draw viewers into the experience. By showcasing hands in action, brands create an instant connection between the product and the consumer, making beauty feel tangible, inviting, and alive. + 5% retention – Of what we hear. + 10% retention – Of what we read. + 75% retention – Of what we practice. → Visual Playfulness Sparks Curiosity Don’t be afraid to infuse whimsy into your beauty visuals. + Stop-motion animations can make beauty products come to life. + Bold, colorful visuals grab attention and inspire experimentation. + Gamification, badges, challenges, interactive features, creates excitement. + Humor, memes, and quirky animations make brands feel approachable. + Community engagement through challenges, stickers, and shared content. Final thoughts. Playful visual communication isn’t just about fun, it’s a strategic tool for engagement, brand loyalty, and virality. Whether through dynamic animations, interactive design, or immersive storytelling, beauty brands that encourage customers to play, experiment, and explore are the ones that stand out. Find my curated search of examples and get inspired for your next Hit. Featured Brands: Belif BigLip From This Island Glossier Glowery Ksuu Laniege Purpur Quick beauty Rhode Sundae Vaay #beautybusiness #beautyprofessionals #beautycommunication #beautymarketing

🚨You want a job? ❌You keep getting rejected over and over? Here’s the hard truth: 👇 ✅(1) Clarity Open your portfolio for one second. Can you immediately tell, with 100% certainty, what role you’re aiming for? Put yourself in the shoes of a recruiter who looks at hundreds of portfolios per day. For example, if you want to be hired as a Character Artist,⬇️ ➡️ ONLY post characters. ➡️NOTHING else. No props. No environments. No concept art. ✅(2) Presentation Imagine spending weeks, or even months, on a project, only to rush the renders in a single night.🤯 How much time do you spend on your renders? How many iterations before you land on something strong? 👉The answer is probably not enough. ➡️Sleep on it. ➡️Come back later. ➡️Get feedback. ➡️Study how your favorite artists render their work. ➡️What software do they use? ➡️ How do they frame and light their shots? 🚨The truth is: presentation can make a project look 100x better. 🔔 If you look closely, I added the same characters in both examples, but the twist is, in the first images, the renders were rapidly made and rushed. ✅(3) Background & Profile Picture ➡️If possible, give your portfolio a theme🎨 ➡️Something consistent. Something that catches attention. ❌ Not just random colors thrown together. ➡️The same goes for profile pictures: ➡️Use something professional or visually striking. ➡️Avoid random selfies, it looks unprofessional and can work against you. ✅(4) Less Is More You might be tempted to include every school or personal project. But often, that’s exactly what’s holding you back. ➡️Go through your portfolio and ask yourself: ❓If this was the ONLY piece in my portfolio, would I get hired? ➡️If the answer is no, cut it.  🚩Weak projects are like giant red flags. They pull attention away from your stronger work. ➡️Most artists need to remove 50–80% of what’s in their portfolio. ✅(5) Treat Your Portfolio Like a Job If your last project was posted 6–12 months ago⏳ your chances of getting hired are close to zero. ➡️Work on your craft like it’s a full-time job: ➡️Minimum of 8 hours a day, 5 days a week. ➡️Be willing to sacrifice. Many others already are, and they’re the ones taking the jobs. ➡️Post a major new project every 1–2 months. ➡️Share every step of your progress openly on LinkedIn. 🚨I can’t count how many times recruiters and lead artists reached out just because they saw how consistently I was producing. ✅(6) Connections, Connections, Connections The more people who see your work, the more opportunities you get. 👉Extreme example: ➡️Person A has 100,000 connections. ➡️Person B has 200 connections. ➡️They both post the exact same project. 🚨Person "A" has 500x more chances to get seen by a recruiter. So: send invitations. Comment. Talk to people. Do it daily. The snowball effect is real. 👉 That’s the difference between hoping and actually getting hired.

Many people have asked me about the process and tools I used to create my spatial interaction animations, so I thought it would be helpful to share a bit of my workflow. On the left is the viewport in Blender, where I modeled, animated, and rendered the core of the interactions. Some elements missing in the 3D—like the 2D UI in the first scene and the clouds in the second one—I added or tweaked later in After Effects. I also used Figma to create some of the UI elements and then imported them into AE. When communicating a vision of an experience, I like to leverage multiple tools rather than just one for everything. I found that this allows me to be faster and enables my creativity to flow more smoothly. Maybe one day I’ll create a more detailed tutorial and full breakdown. But for now, I hope this is helpful. 🙂 #xr #3D #design #motion

AI timelapse is quietly reshaping how we communicate construction… …and I see from your reactions that these posts really resonate. So here comes another strong example, this time from a studio in Brazil 🎥. They built a dynamic time-lapse visualization for a client of the Reserva Jacuípe Prime development, showing every construction stage from raw terrain to final residences. And here’s the twist: the real works hadn’t even started. Yet the client could already see the full build sequence, risks, interfaces, and pace long before mobilization. Why these timelapses work: • They translate complex phasing into a single clear narrative. • They help teams align on sequencing, logistics, and site flows. • They boost client confidence by visualizing outcomes before groundbreak. • They reduce misunderstandings early, when changes are still cheap. Engineering is clearer when we can literally watch decisions unfold over time. How are you using AI visuals to improve early-stage construction planning? 🎥 by Vertikal Drones

Let's reverse engineer this demo. You need 3 things: (1) robust hardware and motor designs that treat simulation as first-class citizen; (2) a human motion capture ("mocap") dataset, such as those for film and gaming characters; (3) massively parallel RL training in GPU-accelerated simulation. Last October, our team trained a 1.5M parameter foundation model called HOVER for such agile motor control. It follows this recipe, roughly speaking: (1) Simulation used to be an after-thought. Now, it has to be part of the hardware design process. If your robot doesn't simulate well, you can kiss RL goodbye. Hardware-simulation co-design is a very interesting emergent topic that only becomes meaningful with today's compute capability. (2) Human mocap dataset to produce natural-looking walking and running gaits. That's one huge advantage of using humanoid robot - you get to imitate from tons of human motions that were originally captured for movies or AAA games. At least 3 ways to use the data: - For initialization: pre-train the neural net to imitate human, and then finetune it into the robot form factor with physics turned on; - For reward function: penalize any deviations from the target pose; - For representation learning: treat the human poses as a "motion prior" to constrain the space of robot behaviors. (3) Shove the above into Isaac sim, add a lot of randomization, pump it through PPO, throw in a bunch of GPUs, and then watch Netflix till loss converges. If you have an urge to comment this is CGI, let me save you a few keystrokes — many academic labs now own the G1 robot in the flesh. Read about our team's HOVER work: https://lnkd.in/gfKW9K5U

Rarely do I miss an opportunity to apply techniques from work to things I enjoy doing in my free time. Often that thing is cycling, the greatest sport in the world. But when autumn comes around and the streets turn cold and dark, I prefer the iron of the weight room over the carbon of the road. A technical sport like Olympic weightlifting is of course best mastered with the guidance of an experienced coach. To the less fortunate or ambitious, video analysis may help hone skills and track progress. Various apps offer basic video tools, but I’ve yet to find one that provides the data I am truly interested in: ground reaction forces (GRFs), forces applied to the barbell, accurate kinematics, and mechanical power output. That is why I developed my own weightlifting video analyzer. The demo below is the result of several techniques from work combined: AI & computer vision (Raidyn), state-input estimation & multibody dynamics (KU Leuven Mecha(tro)nic System Dynamics (LMSD)), and biomechanical impact modelling (Classified Cycling). At the core is a flexible multibody model of the barbell that feeds into a combined state-input-parameter estimator to infer the forces applied to the bar. With accurate barbell forces, GRFs can be estimated  with higher precision than methods based solely on accelerations derived from video. In addition, the model unlocks a virtually unlimited supply of synthetic training data for the AI model, ensuring robust segmentation of barbell motion and deformation. Initially I cast myself as the hero of the demo, but I soon realized that a video starring the Pogačar of weightlifting would make for a more spectacular analysis. Enter Bulgarian Karlos Nasar, 20 years of age at this year’s European Championships in Moldova, lifting a record-breaking 229 kg overhead. Running my analyzer on Nasar’s low-resolution YouTube video allowed me to test its performance on a subject it hadn’t seen before in training, with frame rate and resolution far below what I use in my own sessions – and yet the algorithms didn’t miss a beat. Sure, it helps that weightlifting consists of only two precisely defined movement patterns, but I was still pleasantly surprised. The demo below is just the start. Belgium’s cold season still has a way to go and I’ve got plenty of ideas to improve and expand the algorithms. Next up: joint and muscle force estimation. 

Ever want to literally tear a website to shreds? Now you can. 📄💥 Daniel Beauchamp at Shopify dropped an incredibly satisfying web demo: a fully interactive webpage that you can tear apart like physical paper. 🔗 Try it here: https://lnkd.in/gHpiMtWx When you first load the page, it looks like a standard UI with text inputs, sliders, product cards, and toggles. But click and drag (or use two fingers on mobile) and the page dynamically rips with realistic jagged edges, paper curling, and physics-based tear propagation. Some technical details behind the Illusion 🪄 The most impressive part of this demo is how it handles interactivity while being destroyed. According to Daniel, the project was born out of a desire to let people experience what this concept feels like before native HTML-in-canvas support is available everywhere. Here is how he pulled it off: - Rather than relying on heavy frameworks or waiting for future web standards, Daniel used a clever SVG -> Canvas approach to flawlessly simulate the DOM elements. - The simulation is so good that it fools you into thinking you are interacting with the native DOM. You can type in the inputs, slide the toggles, and click the buttons - right up until you rip them in half. - The realistic tear propagation, mesh deformation, and paper curling are all driven by a highly optimized, JavaScript-based physics simulation. It works beautifully on desktop via mouse, but is also worth trying multi-touch on mobile, making the two-finger tearing gesture incredibly satisfying. It is a masterclass in creative coding, web physics, and UI simulation. Go give it a try and see how long you can resist shredding the entire UI! #programming #softwareengineering #web

🫧  Moving pixels from A to B is easy. Making them feel physical is hard. So, I over-engineered a Jetpack Compose "soap bubble" component so you don't have to. 👉 Full API in the first comment 🧮 Euler Springs: Standard animations look robotic. We bypass them entirely using raw velocity, stiffness, and damping math so the UI squishes and snaps with actual momentum. 🫧 AGSL GPU Shaders: No static gradients here. This calculates Snell’s law in real-time to simulate thin-film optical interference (colors shift based on simulated fluid thickness and gravity). 🚀 Zero-Allocation 120fps: Heavy math usually melts the Garbage Collector. We bypass Compose recomposition entirely using Modifier.graphicsLayer and primitive arrays to keep frames perfectly locked. You don't need a physics degree to make UIs feel alive. Grab the math or the shader, and drop it into your codebase. #AndroidDev #JetpackCompose #Kotlin #MobileDevelopment #UIUX #SoftwareEngineering #AndroidWorldwide #BuildInPublic #Android #Animation #AndroidDevelopers Android Developers

Google just shared the design system behind Gemini, and it’s a great example of how visual language, motion, and systems thinking come together for AI products. A few things that stood out: 🔹 Visuals are not decoration, they explain how the AI thinks and responds 🔹 Gradients act as directional cues, guiding attention and signaling energy 🔹 Motion is intentional, showing progress, listening, and synthesis 🔹 Shapes and containers borrow from Google’s design DNA to create familiarity 🔹 The system is built to evolve, just like the AI itself The goal isn’t to make AI look “smart”. It’s to make it feel approachable, predictable, and trustworthy, even as it keeps changing. This is a strong reminder that designing AI products is less about screens and more about building mental models through systems. 📖 Full article by Google Design: https://lnkd.in/eXnNr5-v Curious how other teams are approaching visual systems for AI. What patterns are you seeing work well? Drop your thoughts 👇 #DesignSystems #designsystem #AIUX #UIUX #UXUI #VisualDesign #MotionDesign #ProductDesign #UXDesign #GoogleDesign #AIProducts #DesignOps #AI #GenerativeAI

I’ve often been asked how I create those animated explainers that go viral 👀 The truth is, I used to build them manually in PowerPoint. Each took 10+ hours of manual animation using flow paths. I tried AI image and video generation to speed things up. The problem is that making small changes becomes almost impossible. If you need to adjust a color or move an element, you often have to regenerate the entire video. It gets expensive, results are inconsistent, and you lose control over the details. Then I realized the real answer is code. Code is not just for apps and backends. It can generate music, visualizations, and motion graphics. With Figma Make, I can prompt my way to animated motion graphics, add reference images, and get results that stay editable and consistent without starting from scratch every time. This is what AI assisted creativity actually looks like. 🔗 Try Figma Make: https://lnkd.in/d6rd4z_H Tip: Try uploading image references for the best result after the first prompt 👌 P.S. Share your favorite AI content creation tips! #AItools #GenAI #FigmaPartner #AITips