Rendered.ai

Having the best engineering tools to effectively generate synthetic data and train computer vision models in one place is a powerful thing! Learn about Rendered.ai's latest integration of inpainting services to leverage limited real data samples and quickly create the diverse training imagery dataset you need now: https://hubs.li/Q03h3wBn0 Inpainting services readily available in the platform enables you to take a small sample of real-world images and rapidly create a robust, highly diverse set of synthetic images that will boost the performance of your CV model. Want to hear from engineers about how the newest wave of AI inpainting tools measures up? 🎥 Check out this episode of Computer Vision Unlocked: https://hubs.li/Q03h3J9h0 #syntheticdata #computervision #artificialintelligence #machinelearning #PaaS

How fast could a computer vision classification model be trained if the right tools handled synthetic data generation, training, and testing—all in one place? 🤔 Using just 20% of a real-world dataset, a performant model was established in a matter of days, thanks to the efficiencies offered by the Rendered.ai PaaS. 🚀 Want to see exactly how this was accomplished? 👉 Get the full breakdown in our recent blog: https://hubs.li/Q03g_CRf0 #syntheticdata #computervision #artificialintelligence #machinelearning #classification #PaaS

SPIE Defense + Commercial Sensing is underway in Orlando! 📍 If you’re attending, now’s the perfect time to meet with the Rendered.ai team onsite to learn how synthetic data can accelerate AI/ML development for SAR, hyperspectral, multispectral, and satellite RGB applications. 📅 Book a time to connect with us: https://hubs.li/Q03g_fnS0 Our team is also presenting throughout the event on topics like generating synthetic HSI and MSI data using Rendered.ai's PaaS and the Rochester Institute of Technology's DIRSIG™ simulator, enhancing object detection models through best practices in configuring and post-processing synthetic satellite imagery, and generating high-fidelity synthetic SAR imagery using the MECA method and NVIDIA's OptiX ray tracing. Stop by our sessions to learn how Rendered.ai is helping shape the future of remote sensing and synthetic data generation. ❓ Not attending the event? Schedule a personalized demo of the Rendered.ai PaaS anytime: https://hubs.li/Q03g_jlY0 #SPIEDCS #syntheticdata #computervision #artificialintelligence #machinelearning #SAR #satelliteimagery SPIE, the international society for optics and photonics

🤯 Imagine having an AI agent generate effective synthetic datasets for you with basic human language prompts. Agentic frameworks are driving the next wave of AI innovation, and to help companies generate high-quality synthetic data exponentially faster, we’ve deployed an MCP server enabling AI agents to run tasks directly with the Rendered.ai PaaS. This breakthrough helps us provide tailored, diverse datasets for unique computer vision use cases at lightning speed—accelerating model training and improving performance. Agentic frameworks are transforming automation, and we’re already seeing the impact. Want to see what’s possible? Request a demo of the Rendered.ai PaaS integrated with AI code editors like Codeium's Windsurf: https://hubs.li/Q03ggVq80 #syntheticdata #computervision #artificialintelligence #machinelearning #AIagents #PaaS #agenticAI

🚀 New AI tools come out EVERY DAY, but what’s actually working? The Computer Vision Unlocked series lets you listen into real conversations with engineers testing emerging AI technologies to help solve real-world model training challenges. No fluff, just real solutions for computer vision. 🎥 Watch the first 8-minute video covering text-to-3D synthetic data generation tools now: https://hubs.li/Q03fRsfp0 In this episode, Rendered.ai CEO Nathan Kundtz sat down with Lead Solution Architect Matt Robinson to break down a classification challenge he encountered firsthand. Faced with an underperforming object class, Matt used text-to-3D tools like Microsoft's Trellis 3d to generate new 3D models, then leveraged the Rendered.ai PaaS to create and refine a synthetic dataset—boosting model accuracy in a fraction of the usual time. Stay tuned for more episodes, where we’ll continue to dive into the tools and techniques that are powering the future of computer vision, straight from the engineers who are making it happen! #syntheticdata #computervision #artificialintelligence #machinelearning #3Dmodeling

⚡ Trusted synthetic data generation is proving vital to the rapid evolution of national security. Mark Hogsett was onsite at Marlinspike's latest summit to share Rendered.ai's insights on fast approaching innovations for the DoD and other agencies. 🛰️ See firsthand how the Rendered.ai PaaS combines unlimited synthetic data generation, machine learning & post-processing engineering tools, and agentic AI in one place with a platform demo personalized for your use case: https://lnkd.in/gNsvqrb8. #nationalsecurity #syntheticdata #defense #intelligence #agenticAI #aerospace Palantir Technologies Anduril Industries cDAO Inc Defense Innovation Unit (DIU) National Geospatial-Intelligence Agency National Reconnaissance Office (NRO) Defense Intelligence Agency

Are you heading to SPIE Defense + Commercial Sensing in Orlando next week? 🌍📡 Pop into sessions led by Rendered.ai's team of experts diving deeply into the power of synthetic data to efficiently and effectively train various AI/ML applications for hyperspectral, multispectral, satellite RGB, and SAR imagery. Here’s where you can find our team onsite: 🔹 April 15 | 3:40-4:00 PM EDT – Matt Robinson, Lead Solution Architect, shares how Rendered.ai's PaaS and the Rochester Institute of Technology's DIRSIG™ simulator advanced synthetic HSI & MSI data generation for Planet and helped OGC establish a standard for Analysis Ready Data (ARD) for the geospatial sector. 🔹 April 15 | 4:00-4:20 PM EDT – Dylan Harkness, Software Engineer, discusses best practices for configuring and post-processing physics-based synthetic satellite imagery to improve object detection models. See a preview of one of the topics Dylan will present–using inpainting services on the Rendered.ai PaaS to quickly customize backgrounds for synthetic data generation in this episode of Computer Vision Unlocked: https://hubs.li/Q03fRCBH0 🔹 April 16 | 9:40-10:00 AM EDT – Michael Blazej, Lead Simulation Engineer, presents a SAR simulation framework integrating the MECA method and NVIDIA's OptiX ray tracing to generate high-fidelity synthetic radar imagery. Want to learn more? 📅 Schedule a dedicated meeting with our team before the event: https://hubs.li/Q03fRCCC0 ❓ Not attending? Connect with our synthetic data generation experts to explore the Rendered.ai PaaS anytime: https://hubs.li/Q03fRCxX0 #SPIEDCS #syntheticdata #computervision #artificialintelligence #machinelearning #SAR #satelliteimagery SPIE, the international society for optics and photonics

Struggling to get diverse, high-quality training data for different modalities to build performant computer vision models quickly? 🔍 Delve into the art of the possible with rapid synthetic data generation with the right tools in Rendered.ai's Synthetic Imagery Lookbook: https://hubs.li/Q03dL0Zt0 Here you see just a small sample of the diversity possible with a data engineering tool like the Rendered.ai PaaS—including simulated satellite RGB, SAR, hyperspectral, multispectral, and x-ray imagery. These examples of synthetic imagery generated with the Rendered.ai PaaS showcase the power of physics-based data engineering powered for streamlined domain adaptation by leading simulators like the Rochester Institute of Technology's DIRSIG™, NVIDIA Omniverse, and Quadridox, Inc.’s QSIM RT. 💡 Ready to fast-track synthetic data generation for your computer vision needs? Connect with our experts today: https://hubs.li/Q03dL5_L0 #syntheticdata #computervision #artificialintelligence #machinelearning #PaaS

Computer Vision Engineers—this one’s for you! Learn how to use the Rendered.ai PaaS to rapidly generate physically accurate synthetic imagery, find the right mix of real and synthetic data to train a classification model, and reduce both development time and cost in the process: https://hubs.li/Q03dLc_z0 Want to try it out for yourself? A synthetic data generation and model training workspace is now live on the Rendered.ai Platform, giving you access to all of the 3D assets, datasets, and the classification model used in this instance. Inside the workspace, you'll find: 🔹 A test dataset of real imagery open-sourced from Kaggle 🔹 The NVIDIA TAO v5.5 classification model 🔹 3D assets and pre-configured synthetic data generation workflows To access this workspace, sign up for a free trial of the Rendered.ai PaaS and use content code MARINECLASS: https://hubs.li/Q03dL5_K0 #syntheticdata #computervision #artificialintelligence #machinelearning #PaaS

🤔 What if you could quickly scale a handful of real-world image samples to a diverse training dataset for high-performance computer vision? Watch Rendered.ai's latest episode of Computer Vision Unlocked to discover which emerging AI tools effectively make this happen! 🎥 Watch Episode 2 now: https://hubs.li/Q03d_60B0 In this episode, Nathan Kundtz, CEO of Rendered.ai, sits down with Dylan Harkness, Software Engineer, to explore the use of tools like Inpaint to accelerate synthetic data generation by repurposing the real-world data scientists already have in-hand. Hear about Dylan’s tests with Inpaint and other tools to remove and replace hundreds of objects in real-world imagery to quickly create countless variations of training scenarios in a fraction of the time and speed up AI/ML model training. 📢 Did you know? Inpaint services are now available in the Rendered.ai PaaS adding another powerful tool to help engineers generate highly effective synthetic data for computer vision. Request a personalized demo today: https://hubs.li/Q03d_2w40 #syntheticdata #computervision #artificialintelligence #machinelearning #imageprocessing #techinnovation #emergingtechnologies