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A visual comparison of HTML-in-Canvas vs rasterizing DOM to a canvas texture (side-by-side below, compare average capture times) Existing approaches to pull web content into canvas are slow and lossy: - Animations glitch, or don't play at all - CSS replication is imprecise - Clogs up the main thread,...

46,497 просмотров • 3 месяцев назад •via X (Twitter)

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New short course: Collaborative Writing and Coding with OpenAI Canvas! Explore new ways to write and code with OpenAI Canvas, a user-friendly interface that allows you to brainstorm, draft, and refine text and code in collaboration with ChatGPT. In the short course, created with OpenAI, and taught by , a research lead at OpenAI, you’ll learn to use Canvas to enhance your workflows. Canvas lets you go beyond simple chat interactions. It provides a side-by-side workspace where you and ChatGPT can edit and refine text or code collaboratively. This makes brainstorming, drafting, and iterating as you write feel more natural and effective. As the first major update to ChatGPT’s visual interface since its launch in 2022, Canvas gives a new, innovative approach to collaboration with AI. For instance, after writing the first version of your code, Canvas can review it and give suggestions for improvement. It can also help with debugging by adding logging, identifying problems to fix, and writing comments. In addition, you'll also learn what it takes to train the model for an interface like Canvas. In this video-only short course, you’ll: - Learn how to ask for in-line feedback and control the iteration of your work by directly editing selected areas of your text or code from the model’s output. - Learn how to access quick automation tools in a shortcut menu that allows you to modify your writing tone and length, enhance your code, and restore previous versions of your work. - Learn how to use Canvas as a research assistant tool with an example of asking the model to reason through the screenshot of a plot to write a research report, in which you can ask questions within the created report. - Ask the model to write Python code to replicate the graph seen on a screenshot image. - Go behind the scenes of how you can create a video game, such as Space Battleship, from scratch, edit it, and display it in one self-contained HTML file. - Get a real-world application example of creating a SQL database from the image of its architecture. - Understand the model training and design processes that power Canvas! Please sign up here:

Andrew Ng

128,180 просмотров • 1 год назад

Being able to move fluidly between Figma Make and the canvas is a pretty big deal Recent example 👇 1️⃣ Started exploring a minified recording toolbar directly on the canvas 2️⃣ Once I had some rough shapes I moved it into Make, imported my style guide, and started bringing it to life with expandable controls, hover states, and tooltips for keyboard shortcuts 3️⃣ A few prompts later, I had something interesting… but the layout wasn’t quite right. 4️⃣ So I jumped back into the canvas and made ~8 quick variations with a bigger video container. 5️⃣ Once I got somewhere interesting I brought that back into Make. All I had to do was copy and paste the frames for my default and hover state of the component and it pretty much nailed the core layout 6️⃣ Then I layered on the timer and made it interactive. But once I got it back into Make I thought "hmm... what if the toolbar layout was based on which quadrant of the screen the component was in 🤔" I was able to one shot this interaction and after playing with it a bunch I kinda love it? 7️⃣ Sent it to the team in Inflight so everyone could play with the prototype. 8️⃣ Brought the up to date UI back into the canvas to polish some of the tooltip details Before this, it always felt like I had to choose between two very different workflows. Now I can bounce between them seamlessly and it’s genuinely changing how I explore ideas.

Ridd 🤿

27,665 просмотров • 9 месяцев назад

PROMPT DROP 🚨 for Creators & NFT Collectors. 🎨 Minting the Self: Genesis of the Living Canvas🪽 The prompt is optimised to inherit the style, colour palette, and personality of your character. 💀 Drop your creations below 🌐 Keen to see what you mint 👀 🚨PROMPT👇🏼 Use the provided PFP/NFT character as the primary reference. The character must remain fully recognizable and true to its original design—preserve exact facial features, proportions, textures, materials, color palette, accessories, and overall personality. All elements in the scene must adapt to and harmonize with the character’s unique visual style—whether that is cartoon, anime, voxel, hyper-realistic, or stylized 3D. Create a hyper-detailed fine art studio scene where the character stands before a massive canvas. The painting on the canvas is a fully completed, master-level version of the same character, rendered in a refined, elevated interpretation of its original style. The character’s signature identity feature (mask, face, helmet, eyes, or defining trait) must be 100% complete, sharp, and highly detailed—serving as the focal anchor of the composition. They hold a paintbrush dripping with material true to their world (oil paint, neon energy, pixels, liquid chrome, etc.), and the colors precisely match their original palette—visually linking the act of painting to the formation of their body. The studio environment subtly inherits the character’s aesthetic and personality: Color grading aligns with the character’s palette (dark, vibrant, pastel, neon, etc.) Props and materials reflect their universe (futuristic, street, fantasy, minimal, luxury) Lighting style matches their mood (soft cinematic, harsh contrast, neon glow, ethereal light) A large window casts natural or stylized light consistent with the character’s world, enhancing texture, depth, and atmosphere. Paint or material drips from both the canvas and the character, seamlessly blending creator and creation, reality and artwork. Style Output: ultra-detailed, cinematic composition, faithful to the character’s original art direction, enhanced with fine art realism and high-end 3D rendering, 8K resolution, museum-quality lighting, rich textures, depth of field, and tactile detail.

BiBi

11,129 просмотров • 4 месяцев назад

i did it. i vibe-coded my own vibe-noding app⚡️ lately every ai tool has been announcing some kind of node canvas. they’re all impressive in their own way, but each one solves a different problem, with a different logic, in a different universe. some are too technical, some are too rigid, most feel like they were designed by a backend engineer. so i built the version i actually want to use. over the last few days i hacked this together with Google Gemini and Google Antigravity. the tool is absurdly capable. i didn’t touch a single line of code. the result is a fully working app with smooth ui animations, smart interactions, and a workflow that doesn’t fight me. my focus isn’t on the models. Nano Banana 2 Lite is already strong enough to generate half a universe on its own. and a year from now, we won’t care about model juggling anyway. we’ll have one model doing everything. the real problem is the workflow. the interface. the flow state. so i optimized for that. the whole point is to keep the technical junk out of the way during ideation and iteration. i want to try an idea, branch it, remix it, explore it, all on a single canvas. every block is editable. every idea is forkable. every path is visible. the design isn’t perfect yet. some of the ui patterns are familiar on purpose. good ideas deserve to be stolen. i rushed it. i let a bunch of great ui decisions die for speed. but it works. and honestly, it feels great to use. future of creating is more organic and more fluid. not just chat bubbles. not rigid feeds. but an intelligent canvas where ideas can grow, split, collapse, or evolve without friction. where the environment quietly adapts to your workflow instead of interrupting it. this is my first version. just for myself, for now. but it’s a start.

Synthetic_soul

239,298 просмотров • 8 месяцев назад

Gemini 2.5 Flash demolishes my Galton Board test, I could not get 4omini, 4o mini high, or 03 to produce this. I found that Gemini 2.5 Flash understands my intents almost instantly, code produced is tight and neat. The prompt is a merging of various steps. It took me 5 steps to achieve this in Gemini 2.5 Flash, I gave up on OpenAI models after about half an hour. My iterations are obviously not exact. But people can test with this one prompt for more objective comparison. Please try this prompt on your end to confirm: -------------------------------------------------- Create a self-contained HTML file for a Galton board simulation using client-side JavaScript and a 2D physics engine (like Matter.js, included via CDN). The simulation should be rendered on an HTML5 canvas and meet the following criteria: 1. **Single File:** All necessary HTML, CSS, and JavaScript code must be within this single `.html` file. 2. **Canvas Size:** The overall simulation area (canvas) should be reasonably sized to fit on a standard screen without requiring extensive scrolling or zooming (e.g., around 500x700 pixels). 3. **Physics:** Utilize a 2D rigid body physics engine for realistic ball-peg and ball-wall interactions. 4. **Obstacles (Pegs):** Create static, circular pegs arranged in full-width horizontal rows extending across the usable width of the board (not just a triangle). The pegs should be small enough and spaced appropriately for balls to navigate and bounce between them. 5. **Containment:** * Include static, sufficiently thick side walls and a ground at the bottom to contain the balls within the board. * Implement *physical* static dividers between the collection bins at the bottom. These dividers must be thick enough to prevent balls from passing through them, ensuring accurate accumulation in each bin. 6. **Ball Dropping:** Balls should be dropped from a controlled, narrow area near the horizontal center at the top of the board to ensure they enter the peg field consistently. 7. **Bins:** The collection area at the bottom should be divided into distinct bins by the physical dividers. The height of the bins should be sufficient to clearly visualize the accumulation of balls. 8. **Visualization:** Use a high-contrast color scheme to clearly distinguish between elements. Specifically, use yellow for the structural elements (walls, top guides, physical bin dividers, ground), a contrasting color (like red) for the pegs, and a highly contrasting color (like dark grey or black) for the balls. 9. **Demonstration:** The simulation should visually demonstrate the formation of the normal (or binomial) distribution as multiple balls fall through the pegs and collect in the bins. Ensure the physics parameters (restitution, friction, density) and ball drop rate are tuned for a smooth and clear demonstration of the distribution. #OpenAI Sam Altman Greg Brockman AshutoshShrivastava Aidan McLaughlin

RameshR

247,923 просмотров • 1 год назад

here's what i vibecoded today: punchingface 🥊 an app to make Hugging Face models fight each other on coding and canvas challenges, built with qwen3.6 35b a3b in 24 hours! benchmarks numbers don't mean anything anymore, we need a way to visualize what the models are actually capable of, and canvas are one the best way to showcase it imo. why? because one single error in the code and everything breaks it shows the differences in a matter of seconds, way easier than manually reviewing the quality of the code produced for a complex project; much needed in the space with all the new finetunes dropping everyday! i did a little demo here with qwen3.6 vs qwopus glm 18b merged, the frankenstein model from Kyle Hessling the winner is clear here, qwen is crazy good and has nothing to prove. that said, qwopus 18b isn't terrible at all; the result isn’t the prettiest to the eye, but hey… it works! i've seen so many models just output a blank page (completely non-working code) so this is already a win frankenstein talks and thinks but he needs some extra brain surgery 🧠 results were expected (it's a very experimental model) but love the effort in the 18b direction from jackrong and kyle! the app was entirely vibecoded with qwen3.6, i didn't edit a single file manually. i can say with confidence that it really has the intelligence of claude sonnet 4.5 at a speed of 125tok/s on an rtx 5080 which models should i make fight next?

left curve dev

19,114 просмотров • 3 месяцев назад

“blank canvas problem” figma says raw and unformed feelings… this should not be shared. * Look, I love AI! I lead and design products for AI & Data Solutions in one of the largest firms in the world. I use these tools every day. I’m one of the biggest advocates of AI. I do NOT fear it. I leverage it. I appreciate what Figma is trying to do here. Good intentions to help designers build faster. Make the design easier and accessible for everyone. And of course, meanwhile, profit from It. it is a business after all and it is perfectly fine. While I was watching Dylan generate detailed designs from a prompt, I started seeing aspiring designers getting attached to these tools and having everything easy, ready, quick… and a series of questions started to arise in my mind; * ➟ Are we going to see a generation of designers who lack resilience and love/appreciation for craft? ➟ Designers who are easily hurt and seek help from AI tools every time a client raises a criticism for the proposed design? ➟ Are these designers going to blame AI tools for the outcome and not take accountability for it? ➟ Perhaps they will go back to the AI input and generate 20+ options for clients in 5 mins without thinking instead of talking to the client, understanding the product positioning and actually thinking/exploring/working for the best design solution? ➟ Are we going to see lazier designers? and weak, giving up, getting frustrated easily? * Dylan says ”This tool helps us to get past the blank canvas problem” Blank canvas is one of the best parts of this work. A new fresh start with endless possibilities. Staring at the blank screen and reflecting on our past experiences, our conversations with the client, transforming these thoughts on screen pixel by pixel… That’s how we truly understand the problem at hand and grow as designers. You may say I’m being a romantic, trying to stay in the past. No. Again, I build these tools and encourage everyone to leverage them. However, yes, I have concerns. Not about the efficiencies this technology brings, Concerns about; AI may raise a generation of weak-minded designers who lack an appreciation for the craft. * It is 2:14 am, I should go to sleep. I should not share this writing. this is not meant to be for others but for me. just thinking in writing… thinking…. thinking… …

Oykun

38,358 просмотров • 2 лет назад