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I’m trying out two different styles for object descriptions. 🔹 Left: black box, Disco Elysium style 🔹 Right: clean text, line animation Which one feels better for the game’s atmosphere? 🔍

37,574 views • 11 months ago •via X (Twitter)

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004/100 Buttons. A bit of the process on building an animation. When looking at a finished animation or in this example a finished button, it can look quite complex inside the CSS. But when building it, it’s more like a lot of simple steps, one after another. Here I had the idea to make some kind of text animation like the footer logo on the Osmo site. I try to add the base animation with no complex easing, for example transition: translate 0.4s ease. Starting with just moving the one text from bottom to top and the other text to top. Adding a stagger, play around with it. Searching for a way to make it more circular. On the research I found the sin() function inside CSS which can build a more smooth non linear curve for the stagger which creates this circular effect. And step by step adding more complexity like, different easing for hover/hover-out, opacity, 3D transform and more. I use also the sin() function to rotate the letters, so the middle ones are getting more rotated than the outer ones. Another thing which helps is to add a small delay on hover, for example 0.05s or 0.1s, you don’t really see the difference, but when you hover pretty fast on and out it doesn’t get that jumpy. I’m using here GSAP’s SplitText to split every char into spans. And then I’m adding a CSS index variable to every span, starting from the center. SplitText can provide CSS index variables, but you cannot tell it from which direction. For the sin() it’s also important to have a max length, so I add another CSS variable with the max char number on it. Crafting 100 Buttons with Osmo ⏳ Total time: 63h

Eduard Bodak

166,023 views • 2 months ago

$KNDX 🤖 Theres 3 big narratives that are sending coins left right and centre rn. 🚀 #AI, #Gamefi, & #NFTs 🔹Theres 50% mindshare for #AI. 🤖 🔹#GameFi mcap is hitting ATH's with #OfftheGrid, $XBG and $SUPER making spectacular moves. 🎮 🔹NFTs and the #Metaverse are making a strong comeback with $APE up 100% over the weekend. 🐵 What if there's a project that touches all these trending narratives with groundbreaking technology to disrupt all 3 of them? 🔥 💡- That's where $KNDX comes in. -💡 Kondux is a cutting-edge Web3 SaaS platform, combining NVIDIA’s Omniverse, AI, Blockchain, and dynamic NFTs to revolutionize secure asset management across industries. 👏 Their flagship product, kNFTs, are 3D digital assets usable across Metaverse and Gaming platforms, AR/VR/XR environments, and manufacturing applications. Kondux’s scalable model opens new revenue streams by enabling effective digital asset monetization. 💰 Kondux is the first Web3 project to integrate VFX pipelines with NVIDIA’s Omniverse and bringing it onto the Blockchain. ⛓️ It is also the only Web3 project with a *Select Status Partnership* with NVIDIA, operating under NVIDIA NDAs and working with them directly for more than 2 years. About their NVIDIA Integrations: 🤖 🔹There are three areas of the Kondux tech stack that coincide with three divisions of NVIDIA: 📡GDN (Graphics Delivery Network, the backbone of GeForce Now) 💡Omniverse for 3D aspects such as, geospatial data, real world physics, lighting, and raytracing 🤖NVIDIA AI Foundation, which covers many aspects of #AI, including inference and deployment scaling. The convergence of all these components lie within .USD file format . 🔹 They are the first blockchain project to integrate NVIDIA’s Omniverse Cloud and Graphics Delivery Network (GDN) to provide high-quality 3D content accessible on any device without requiring high-end hardware. 🔹 This setup streamlines content management, democratises access to resource-intensive 3D content, and enables real-time interaction with 3D NFTs. Now, I haven’t seen any crypto project so deeply connected with NVIDIA and NVIDIA technology. GDN is a HUGE competitive advantage. With it, the need for #GPU’s basically goes out the window. 🤯 Now lets take a look at some of the other main features... 👀 OpenUSD (Universal Scene Description): 📽️ 🔹 Kondux is leveraging USD technology, developed by Pixar and used by Meta, Apple, Microsoft and other industry leaders to enhance 3D graphics and interoperability within its creative ecosystem. 🔹 Originally created for high-end film production, USD now supports a variety of applications, including gaming and virtual reality, making it a key asset for Kondux. kNFT's: 🎨 🔹 Kondux is pioneering a new category of NFTs known as kNFTs, which aim to redefine NFT utility through innovative features. 🔹 A standout feature is the upgradeable aspect provided by Kondux DNA, allowing kNFTs to transform and combine with other NFTs, creating limitless possibilities in art, gaming, and music. 🔹Through the Kondux AI portal it will be possible to communicate with kNFTs. They can learn and adapt. This AI technology is revolutionary because it makes human to kNFT interaction possible, turning it into a unique, personalized experience. Check out the clip of kNFTs in Unreal Engine 5 gameplay below. 👇 Kondux is a very obvious utility play with huge upside because it’s multi narrative. 📈 It's seriously groundbreaking stuff that they’re about to launch. 🚀 After speaking with the team there’s no doubt in my mind this will do crazy big numbers in the next months. 🤑

Altcoin Miyagi🇯🇵

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When strangers become big sisters in seconds. GPT Image 2 + Seedance 2.0 on Renoise prompt Create a clean, professional Pixar-style 3D character sheet of a 6-year-old girl, highly detailed, vibrant colors, polished family-friendly animation style. Character Description: Adorable 6-year-old girl with soft dark wavy hair tied in a cute high ponytail with a small pink bow. Big sparkling brown eyes, round expressive face, rosy cheeks, small button nose, and a warm friendly smile. She has a healthy, energetic child body type suitable for a 6-year-old. Outfit: Bright yellow t-shirt, light pink shorts, white ankle socks, and colorful small sneakers (blue and pink accents). Character Sheet Layout: A single clean vertical character sheet with multiple views of the same girl arranged neatly: Top Left: Full-body front view, standing naturally with hands on hips, smiling confidently. Top Right: Full-body 3/4 angle view, showing depth and personality. Middle Left: Full-body side profile view (facing right). Middle Right: Full-body back view. Bottom Center: Large close-up of her face showing 4 different expressions in small circles — Happy smile, Surprised, Shy/embarrassed, and Excited/grinning. Bottom Right: Small extra details — close-up of her ponytail with bow, shoe details, and hand poses. Style & Quality: Beautiful 3D Pixar animation style, smooth rounded shapes, expressive eyes, soft realistic textures, vibrant yet soft lighting, clean white background with subtle light shadows, highly polished, professional character design sheet, perfect proportions, studio quality, sharp details, warm and wholesome feel. 16:9 aspect ratio, ultra-detailed, cinematic lighting. #RenoiseCanvas

Sharon Riley

156,934 views • 1 month ago

Smooth Commute Ahead on Hebbal–Nagawara Stretch 🚶‍♂️...🛵... 🚗✨ A major clean-up and encroachment removal drive along the Hebbal–Nagawara–Allalasandra Bridge (Outer Ring Road) corridor is set to improve traffic flow, pedestrian movement and overall road safety. Over the past week, a large-scale sanitation and debris-clearing operation was carried out across this busy stretch, involving multiple civic and infrastructure agencies, along with local businesses, traders and community groups. 🔹 What was done? • Removal of construction debris and roadside waste • Clearing of encroached footpaths to restore pedestrian access • Beautification of pedestrian pathways • Elimination of long-standing garbage black spots 🔹 Key impact: • Around 1,200 tonnes of waste and debris cleared • Over 150 sanitation workers deployed daily • Use of JCBs, tractors, tippers and compactors • ~40 illegal shop extensions removed, freeing footpaths for public use 🔹 Local-level results: In Dasarahalli ward alone, 150 tonnes of waste were cleared and 80 metres of footpath was upgraded with the support of civic staff and volunteers. 🌱 Why this matters: Cleaner roads, safer footpaths and smoother traffic not only improve daily commutes but also encourage better civic habits, environmental responsibility and respect for public spaces. 📍 Location: Hebbal – Nagawara – Allalasandra Bridge (ORR) Bengaluru North City Corporation

Bengaluru Post

13,060 views • 7 months ago

🚀 Introducing EgoExo Forge - built on top of Rerun, Gradio, and Hugging Face hub (I’ll be in San Francisco July 21–29 — if you’re into robotics, egocentric AI, large-scale data collection, or just want to chat, DM me!) In my opinion, large-scale, diverse, and high-quality data is still the largest bottleneck for generalized robotics deployment. I believe that some version of imitation learning from human examples will be the most scalable + clean way to train humanoid robots 🤖 (similar to what Tesla did for Full Self Driving). Teleop is too expensive to collect a large enough dataset in a reasonable manner, so passive collection via egocentric (and in certain cases, exocentric) views feels like the right bet. Over the past few months, I've been trying to build out the scaffolding for this and using Rerun as my underlying infrastructure. Data being collected needs to be easily inspectable + time series and rerun provides the right tooling for this. My goal is to first build out a ground truth representative dataset from already existing open source data, generate some reasonable baselines, and then go out and collect my own data that adheres to the defined schema. 🔍 Starting with open-source datasets 1. EgoDex from Apple 2. HOCap from Nvidia and the University of Texas at Dallas 3. Assembly101 from Meta All these different datasets have different sensor configurations + annotations, so my goal with egoexo-forge is to have one consistent labeling scheme + data layout. I built a data pipeline that aligns all of the different datasets in one general schema assuming the COCO133 keypoint layout that allows for exo+ego, ego only, or exo only Since the scaffolding is already there, it becomes MUCH easier to add other datasets. So the next ones that I'll be including are HD-EPIC kitchens dataset, HOT3D, and finally my own personal iPhone + insta360 go collection method. Once I have a diverse variety of datasets, I'll double down on what I believe to be the key algorithms required to make useful data for imitation learning 📊 1. Camera Pose estimation via SLAM/SFM for ego perspective (and automatic calibration for exo) 2. Human pose estimation for both egocentric + exocentric views 3. Metric 3D reconstruction + object tracking I'll be setting up reasonable open-source baselines for each of these to validate that these datasets work, and then finally try to use the generated datasets for some imitation learning via the pi0-lerobot repo I've been working on. I plan on making a blog post + providing more info on all of this in the near future so stay tuned

Pablo Vela

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Household Chores Motion-Based Reference Prompt for ChatGPT Image 2.0 / Seedance 2.0 on Yapper Prompt: Create a monochrome grayscale 4×4 instructional storyboard showing a full household chore sequence. Use a clean white background, soft studio lighting, and high contrast to emphasize posture, movement, and object interaction. The character must match the provided reference image in face, skin tone, proportions, and overall likeness, with natural makeup, a soft expression, and consistent identity across all 16 panels. The character should wear a modern modest outfit: a fitted crop top with a clean neckline, high-waisted straight or slightly wide-leg jeans, and optional minimal sneakers or barefoot indoor styling. Keep fabric movement natural with subtle folds and tension. Each panel must be the same size, separated by thin black lines, and clearly numbered 1 to 16. Show a full-body pose in each frame performing a different chore in a minimal environment with only essential props. No clutter, no complex background, no extra characters. Include in every panel: top-left step number and task title, center full-body action pose, bottom-left 3–4 short instruction lines, and motion arrows or guides showing movement flow. Use this chore sequence: Make the Bed, Tidy the Room, Dust Surfaces, Vacuum Floor, Sweep Floor, Mop Floor, Do Laundry, Hang Clothes, Fold Clothes, Clean Kitchen Counter, Wash Dishes, Take Out Trash, Water Plants, Clean Bathroom, Organize Shelves, Final Room Reset. Use motion indicators appropriately: curved arrows for wiping and folding, straight arrows for movement, and circular arrows for scrubbing and mopping. Style should be highly detailed 3D, smooth grayscale shading, soft shadows, clean linework, and polished concept-art quality. No color, no revealing clothing, no extra background detail, only the subject, props, and instructional elements.

WasifAI

18,752 views • 2 months ago