Design Visualization Tools

What if you could fly through someone’s brain — and actually watch it think in real time? 🧠 This stunning 3D visualization makes that possible. It shows live brain activity mapped from EEG (electroencephalography) signals onto a realistic 3D model of the human brain. Each color represents a different brainwave frequency — from calm alpha and focused beta, to fast, high-energy gamma rhythms. The golden lines trace the brain’s white matter pathways, and the moving light pulses represent information flowing between regions — the brain communicating with itself in real time. How it’s built The process begins with MRI scans to create a high-resolution 3D model of the brain, skull, and scalp. Then, DTI (Diffusion Tensor Imaging) maps the brain’s wiring — the white matter tracts that connect its regions. Next comes EEG recording, captured using a 64-channel mobile EEG cap. Advanced software pipelines like BCILAB and SIFT clean the data, remove noise, and use mathematical modeling to “source-localize” brain activity — estimating where in the brain each signal originates. They also analyze information flow using a technique called Granger causality, revealing which brain regions are influencing others at any given moment. From Data to Experience All of this is brought to life in Unity, a 3D engine usually used for games. Here, the brain becomes a fully navigable world — you can literally fly through it using a controller and watch live signals flicker and flow. It’s data turned into experience — a fusion of neuroscience, art, and technology that lets us see the living mind at work. Why it matters By merging EEG, MRI, and DTI, researchers can study how the brain’s networks communicate, and how this connectivity changes in conditions like epilepsy, depression, or neurodegenerative diseases. This work also pushes forward brain-computer interface research — paving the way for future technologies that help restore movement, communication, or sensation through brain signals alone. Every flicker of light here represents a thought, a signal, a decision — the brain in motion. 🎥 Video Credits: Dr. Gary Hatlen

I find truly incredible how AI has transformed concept design from linear to dynamic, making it faster, more flexible and accessible. AI isn’t the designer, it’s the collaborator. Concept design is about translating ideas into form and function, and AI’s role is to amplify that process. With AI I have expanded my creative exploration. I am able to explore variations I wouldn't have considered which in turn generates new and unexpected ideas. AI speeds up iteration, what once took hours can now be visualised in minutes, and this helps refine ideas faster. It has also sharpen precision. When you use AI with intention and a clear strategy, fine-tuning prompts and parameters, you can create visual stories that align closely with your vision. One of the most powerful techniques in AI-driven concept design is Prompt Sequencing. Instead of relying on a single, all-in-one prompt to generate a final output, you use a sequence of prompts to develop, refine, and finalize your concept step by step. Here's how I do it: Step 1: Core concept generation Start with a simple, broad prompt that focuses on the core theme or feeling you want. Step 2: Focus on details Add layers of specificity to shape the environment or character. Step 3: Composition and style refinement Specify angles, colour palettes, and textures to align with your storytelling goals. When you sequence prompts like this, you move from ideation to refinement with control. Instead of hoping one mega-prompt gets it right, you’re directing the evolution of the design, much like a traditional concept designer refining sketches layer by layer. Give it a try. #HumanDriveAI #HDAI

Advances in #multiplexed super-resolution microscopy are enabling researchers to understand the cellular complexity and protein function by visualising the intricate interactions and locations of numerous proteins #spatially within a cell. #KeyAdvancements driving this progress: #CyclicImmunofluorescence:These methods, already widely used in tissue imaging, are now being applied to subcellular mapping, providing multidimensional insights into protein localisation. #SuperResolutionMultiplexedImaging techniques: Methods like Exchange-PAINT, FLASH-PAINT, and SUM-PAINT are revolutionising our ability to image multiple proteins at the nanoscale level within cells. SUM-PAINT has even achieved 30-plex super-resolution imaging in neurons. #Value: Information-rich #AtlasProjects and #OpportunityToIntegrate with tissue imaging with nanoscale details of protein architecture in every cell. Key Links: https://lnkd.in/eqEgM7Nn: This research tagged 75% of the yeast proteome with GFP to image protein locations. https://lnkd.in/eHMGpk5D, https://lnkd.in/eHMGpk5D, https://lnkd.in/ePiHn8j4, https://lnkd.in/ePiHn8j4: These studies used CRISPR-based gene targeting for similar efforts in human cell lines. https://lnkd.in/eKsSDYw5: This paper introduced Exchange-PAINT, a pioneering method for multiplexed super-resolution imaging. https://lnkd.in/eHTrdTYv: This article details the development of FLASH-PAINT for multiplexed imaging in cells. https://lnkd.in/eSYkZK5t: This research presents SUM-PAINT, a method for highly multiplexed super-resolution imaging. Got value from this? Share 🔄 #SingleCell #TranslationalResearch #MultiOmics

Handling real-time data? Make sure your pipeline is built for it. Unlike traditional databases, time series data plays by different rules—it’s all about constant updates, fast queries, and time-based analysis. If your pipeline isn’t built for it, you’ll hit performance bottlenecks FAST. Here’s how to set it up the right way: ✅ Pick the right DB – InfluxDB > relational DBs for time series ✅ Design for time-based queries – Use tags & fields wisely ✅ Ingest data from all sources – API + historical CSVs for full context ✅ Optimize queries – Flux makes slicing & analyzing time windows easy ✅ Visualize it – Grafana dashboards make insights interactive I built a hands-on "Storing & Visualizing Time Series Data" project that walks you through all this step by step. If you’re tired of static reports and want real-time, high-frequency insights, check it out! 🚀 ⚠️ Link to the full course in the comments!

Architectural Exploration and AI PROOF OF CONCEPT / NEW WORKFLOW As someone developing in-house technology with the intersection of AI and architecture, I've been fascinated by how emerging technologies are democratizing visualization processes. What once took weeks can now be accomplished in minutes, shifting our creative possibilities dramatically. My recent explorations have revealed promising developments: - No reason to learn Grasshopper, Just Chat. - 3D model generation through LLM integration with Grasshopper - Near-instantaneous conceptual visualization - High-fidelity rendering through AI assistance - Rapid design iteration capabilities Perhaps most significant is that many of these tools are becoming accessible and more EASY through open-source communities, creating opportunities for practices of all sizes to benefit. This acceleration isn't just about efficiency—it fundamentally alters our behavior in ideation workflow. When visualization barriers fall, we can allocate more resources to exploring the "Vison" that inspires truly innovative architecture. I'm documenting these developments and building a community of practice around these techniques. If you're conducting similar research or implementing these approaches in your work, I'd value connecting to share insights and expand our collective understanding. #AIinArchitecture #ArchitecturalResearch #DesignComputation #OpenSourceAEC #Grasshopper #ComputationalDesign #GenerativeDesign #GrasshopperAI #LLMsinDesign #TextTo3D #ArchViz #DigitalTransformation #ArchitecturalInnovation #AIResearch #DesignTechnology #ParametricDesign #AECTech #AIPrototyping #ArchitecturalVisualization #DesignWorkflow #FutureOfArchitecture #RhinoGrasshopper #AECInnovation #DesignAutomation #AITooling

3D Gaussian Splatting (3DGS) is becoming the new standard for 3D reconstruction, rapidly transforming fields like Robotics, Autonomous Vehicles, AR/VR, Gaming, and VFX. With its ability to deliver photorealistic, real-time rendering while capturing large-scale scenes with minimal artifacts, 3DGS is solving complex problems across industries—all without relying on neural networks. In this article, we break down the Gaussian Splatting paper, explore the key equations, and explain how it achieves its unmatched performance. We also guide you through training your own data using nerf-studio's gSplat and share tips to get the best results. If you're working on 3D reconstruction or visual computing, this is the resource you need to stay ahead! https://buff.ly/3ZKhzrG

💡 What if we could relight a video—after it was already shot? Imagine shooting a scene in bad lighting and later fixing it perfectly—without needing 3D models or complex software. That’s exactly what DiffusionRenderer does. It’s a neural rendering model that extracts scene properties from videos and then reconstructs photorealistic images—with accurate shadows, reflections, and relighting! 🎥 No reshoots. No manual 3D work. Just AI. ✅ Relight scenes dynamically without new footage ✅ Change material properties (like roughness & metallic) ✅ Insert objects seamlessly while keeping realism intact ✅ Forget manual lighting adjustments—AI handles it We’ve seen AI change photography, design, and content creation. Now it’s doing the same for rendering. 🚀 #0to100xEngineer #Day113 #AI #Genai 

𝐋𝐢𝐯𝐞 𝟑𝐃 𝐈𝐦𝐚𝐠𝐢𝐧𝐠 Medical images like MRIs and CT scans usually live on screens, but what if they could come to life right on the patient’s body? It´s possible now! This technology turns flat, complex scans into real-time 3D visuals that overlay on the patient during care. What this means: ▶️ Doctors see anatomy in three dimensions, not just slices ▶️ Real-time guidance at bedside improves accuracy ▶️ Complex cases become easier to understand ▶️ Enhances communication between teams and patients ▶️ Speeds up decision-making and treatment This blend of technology and care could change how we see and treat the body. 𝐻𝑜𝑤 𝑚𝑖𝑔ℎ𝑡 𝑟𝑒𝑎𝑙-𝑡𝑖𝑚𝑒 3𝐷 𝑖𝑚𝑎𝑔𝑖𝑛𝑔 𝑐ℎ𝑎𝑛𝑔𝑒 𝑦𝑜𝑢𝑟 𝑣𝑖𝑒𝑤 𝑜𝑓 𝑚𝑒𝑑𝑖𝑐𝑖𝑛𝑒? 👇 Share your thoughts below 𝐁𝐞 𝐁𝐨𝐥𝐝, 𝐔𝐧𝐟𝐨𝐥𝐝 Video Source: Medivis

🔥 Multi Omics Visualization Is Getting a Major Upgrade 📈 The study “MultiModalGraphics: an R package for graphical integration of multi omics datasets”, published in BMC Bioinformatics by Foziya Ahmed Mohammed, El Hadj Malick Fall, Kula Kekeba Tune, Rasha Hammamieh, Marti Jett and Seid Muhie, introduces a tool that turns complex biological data into visuals that actually make sense. 📌 Brings p values, q values, fold changes and feature counts directly into your plots so results speak for themselves 📌 Transforms heatmaps and volcano plots into intuitive, insight packed visuals for multi omics and multimodal datasets 📌 Lets you spot pathways, patterns and outliers in seconds instead of hours 📌 Connects with Bioconductor workflows so preprocessing, stats and visualization flow naturally 📌 Allows fast creation of multimodal figures that look polished and informative without extra coding 📌 Works across pan cancer datasets, mouse brain time series and multi tissue studies to reveal hidden biological signals 📌 Makes quantitative annotation accessible to everyone, even if you are not a visualization expert 📢 Join the Conversation 📢 Share your ideas, methods, and tools in the comments! 👇 💬 👉 Follow my blog for more https://lnkd.in/dvppv8uc

Sketch → xFigura → Nano Banana Pro → Kling → VEED With ZERO 3D Modelling !! Most commercial building visualizations still take 6–12 hours across modeling, rendering, entourage, revisions, and post-production. And the painful part isn’t “design” — it’s the repetitive production work. Sketch → client-ready animation in under 5 minutes. Sounds unrealistic? It’s exactly what most AEC teams need right now. In this video, I’m showing my AI-first visualization pipeline that took a commercial building from: What gets generated in this one flow:  1. Realistic massing + material interpretation  2. Populated scene with trees / context  3. Exploded view for clarity + storytelling  4. Technical front elevation style output  5. A stitched animation sequence ready to share with a client Important detail: ✅ No 3D models were made for this video. No Revit/SketchUp massing, no manual modeling, no heavy rendering setup — just a fast AI pipeline for early-stage visualization. Results I consistently see with this workflow:  • 90% faster turnaround (hours → minutes)  • 5–8 iterations possible in the time it usually takes to render 1  • 60–70% reduction in back-and-forth during early-stage approvals Cleaner communication because the client can “see” the idea immediately This isn’t about replacing architects. It’s about replacing the most time-consuming parts of visualization production. Want the exact workflow + prompts + tool settings? Comment “Workflow” and I’ll share the link for this workflow in our upcoming Visualization Masterclass. #AI #AEC #Architecture #Visualization #Design #GenerativeAI #Workflow #BIM #InteriorDesign