Prasad Dixit

Get started with the fundamentals of vehicle development for student competitions like Formula Student using Simscape. Learn how to create a basic vehicle model with brakes, and simulate its behavior on a slope and more. #simulation

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Chladni Plate/Cymatics sim. I'm still working on a more effective model for specific pitches, chords, summation tones, resultants, etc. But I like how this prototype of a rising sine wave came out. Made in Blender using Geometry Nodes. #acoustics #technicalart #cymatics #chladniplate #simulation #mathematicalmodeling #math #physics #3dmodeling #3danimation #cgi #blender #geometrynodes

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I’ve just released a new YouTube video designed to help beginners understand the fundamentals of Sub-D modeling and how to achieve clean, efficient topology. This video is a sample module from my newly launched 3D Modeling and Topology Masterclass, giving you a glimpse into the workflows and techniques the course offers. 🔗Link: https://lnkd.in/gvSKhFkk #3dmodeling #subdmodeling #topology #autodeskmaya #blender #3dart #cg #vfx #gamedev

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This is one of the most elegant explanations of Entropy, visual means of explaining concepts is by far the most memorable.

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V67 updated turned #Quest3 into a #spatialcomputing device with at least one BIG difference from #VisionPro. Let me show you how to activate it and what it does: First of all, you need to have v67 as a software update After that remember to toggle "multiple windows" in the experimental settings One important #UX difference with #VisionPro is that windows have 2 hierarchies: - 3 windows positioned in front of the user that are clustered together and can be moved as a #digital floating 3-screens setup - All others that can be positioned and resized much more freely as I show in the video. That being said I don't think we can fully compare the #Quest3 Vs the #VisionPro and until we have the full capability to run multiple apps at the same time (thinking about you "augments") we still have different devices for different #productivity usecases. Agree?

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Learn why it's often unnecessary to model threads in 3D and how to add thread callouts to your drawings to improve manufacturing efficiency. 📈 Today's Onshape Tech Tip covers everything from starting an external thread feature to adjusting thread options like chamfers and undercuts, as well as how to visualize threads in your drawings 👉 http://onshp.co/gS

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Following up on the recent post, let's explore the QuestBuilder - a smart quiz creation and discovery solution powered by generative AI and machine learning techniques. How Does It Work? - AssemblyAI processes the video to detect chapters and generate transcripts. - FFmpeg splits the video into chapters, and OpenCV extracts the clearest still images. - Amazon Rekognition analyses the video for additional context, such as objects, scenes, and sentiment. - The video stills, transcripts, and insights are combined with the Da Vinci Quests Knowledge Base to form a comprehensive context and prompt message. - Anthropic Claude, integrated via the Amazon Bedrock API, takes this rich context to generate engaging quiz questions and answers. - A rigorous quality assurance process ensures the accuracy and relevance of the generated quizzes. - Amazon Translate ensures the quizzes are accessible in various languages. The Impact QuestBuilder streamlines the creation of interactive learning experiences by automating a time-consuming process. This allows us to focus on delivering high-quality educational content and enhancing the learning journey for our users. Previous post: https://lnkd.in/ekPAgQdN Stay Tuned for More! I'll be sharing more details about QuestBuilder's capabilities and its impact on our products in the coming weeks. #QuestBuilder #GenerativeAI #MachineLearning #Speech2Text #Image2Text #VideoAnalyse #ImageProcessing #Education #Innovation #DaVinciApp #AWS #SageMaker #Bedrock

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Just listened to my first episode of the Bg2 Pod and it was a good one on Tesla Robotaxi vs Waymo vs Uber - nice work Bill Gurley and Brad Gerstner ! As Bill mentioned, Waymo’s biggest issue will be whether to build to peak or build to average. Rideshare demand has huge peaks Mon-Fri during rush hour and on Friday/Saturday evenings (aka ‘The Party Hours’) so if you have enough Waymo robotaxis for those times, you’ll have way too many for Tuesday afternoon. Uber’s big unlock was the concept of ‘variable supply’ which means that not only do they NOT have to pay capex for their fleet, but they can unlock new supply with surge pricing during times of high demand. This works great because vehicle ownership in the US is high (for ex. CA has 2.3 cars per household!) and our cars have low utilization (‘cars are parked 95% of the time!’) so it’s easy to encourage people like me to get off the couch on Saturday nights when earnings are high and drive for Uber. Tesla is the only company that could be a viable robo taxi threat to Uber in the future because they already have millions of personally owned vehicles on the road. We know these cars are sitting empty 95% of the time so I would imagine many Tesla owners would be happy to support Elon and put their cars on the network for some or even a lot of time and earn $$ back. The big question with Telsa of course is IF/when their FSD software will ever get to 4 or even 6 9’s (99.999999% reliability). And of course, then they’ll need to go out and hire thousands of people to run/operate a rideshare business. What do you think about the threat of robo-taxis to Uber’s business model? Are you putting your money on Waymo or Tesla?

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Get started with the fundamentals of vehicle development for student competitions like Formula Student using Simscape. Learn how to create a basic vehicle model with brakes, and simulate its behavior on a slope and more. #simulation #simulink #matlab

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Thanks for the mention, Oskar! https://lnkd.in/gyaSwrMB While some of our competitors claim to be "the fastest solver," maybe have a look at this comparison of InsideOpt Seeker with Gurobi on the quadratic assignment problem. Timeout: 60 seconds (it does not get much better for Gurobi after 1 hour either, though). Benchmark: Taillard Instances from https://lnkd.in/gmDz6HHt. Cores: 4. Gap in terms of best-known solution per the webpage above. #insideopt.com

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Thanks to Tom Scott, I came across this wonderful list of 45 engineering maxims. A few favorites include: 9. Not having all the information you need is never a satisfactory excuse for not starting the analysis. 14. (Edison's Law) "Better" is the enemy of "good". 20. A bad design with a good presentation is doomed eventually. A good design with a bad presentation is doomed immediately. https://lnkd.in/eM7i4SyE

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Optimal designs faster than ever before? That's right. ✅ Gregor Judex tells us all about the benefits of unifying modeling and simulation (MODSIM). Check out how MODSIM helps design and virtually test the floor panel of electric vehicles. ⬇️🚘

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Boundary representation is the democracy of 3D CAD: it’s the worst form of geometry representation except for all those other forms that have been tried from time to time. So what is b-rep? Why is it so great and so terrible at the same time? 👇 B-rep is the mathematical foundation of how CAD systems represent geometry. B-rep represents shapes as parametric curves and surfaces that are connected to each other. Unfortunately, parametric surfaces [s(u, v)=…] don’t necessarily have boundaries and don’t have a way to represent holes, like a plane (infinite in the u and v parameters) or a cylindrical surface (periodic in the v parameter, infinite in the u parameter). B-rep solves this by adding boundaries and holes defined as curves laying on the surfaces. A face is a set of curves (that define the inner/outer boundaries of the surface) and a single surface (on which the curves lay), and an edge is a curve segment of the boundary of the face (a trimmed curve, laying on the surface as part of the outer boundary or the inner hole). For example, a square with a circular hole in the middle is a planar surface, bounded by four lines laying on the plane, and a circle laying on the plane in the middle of the square. This is a sheet body, with open edges, not a solid. We often need to connect multiple faces to create a solid body, unless we have a closed surface, like a torus. When two faces are connected, an edge is the intersection of the two surfaces. B-rep has some excellent properties: 1. The parametric surfaces and curves are extremely accurate and can be used for manufacturing high-precision parts. 2. The concept of faces and edges is natural and easily understood by humans. Operations like “make this edge rounded” or “move this face by 2mm” align with how humans think. And b-rep has some absolutely terrible intrinsic properties: 1. The representation doesn’t guarantee that the topology and the geometry are consistent. A couple of examples: -a face structure where one of the four lines of a square is missing -a face where a boundary is self-intersecting 2. Tolerances. Since b-rep works with floating-point numbers and numerical algorithms, equality is defined with tolerances: two geometries are the same if they are closer than a small number (typically 10^-6 meter or less). This means that a b-rep kernel maintains two data structures: the topology (what is connected to what) and the geometry. While the two data structures are independent, what they represent is not. Thus, the kernel continuously needs to do double bookkeeping of two complex data sets. Welcome to b-rep hell. 🔥😈🔥 The role of a b-rep kernel (like Parasolid) is to ensure that every operation creates consistent data. Writing a kernel a bit like self-driving cars: it’s fairly easy to get to 99%, but the remaining 1% takes forever. Robustness requires millions of users running into all the of these issues for decades, and fixing them one by one. There is no easy way to achieve that.

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#Flash3D: Feed-Forward Generalizable 3D Scene Reconstruction from a Single (Monocular, RGB) Image Project page: https://lnkd.in/ghASmc3s It’s worth noting one can achieve something similar using #opensource #depthmap creation tools. A static image can be converted into a GLB/GLTF one can then import into #AfterEffects, and get a similar range of motion from what seems a bit like a projection effect. One can use #Photoshop as well, selecting the “neural filters” option to generate the depth map. It would be nice, however, if this were a straightforward process one could execute within PSD and/or AE, #Adobe. For example, what #ZoeDepth does, should be possible in both, or at least, one: https://lnkd.in/gceGyynC This isn’t new, really, the automation part of it is, but if you check back, I had posted about this last year. If you want to keep pace, I share such discoveries such as these regularly (where media collides with tech), you just need to follow or connect (I am an open networker). Cheers! _ #ImageTo3D

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New #ApplicationNote! As part of the build-up to Formnext - Where ideas take shape I have made a series of five new application notes to show how X-ray CT can be used in #AdditiveManufacturing. These are some new examples of "frequently asked questions", to show you the latest methods in Dragonfly software for this application field. Today's application note is all about automated porosity analysis - using automatic tools for thresholding and making the analysis based on that. The full application note covers three examples and has a "how-to" video to go with it. Get the full app note here: https://lnkd.in/dUw_rQU9 The video below (one of the examples in the app note) is from a research paper I collaborated on with Simone Murchio, Matteo Ing Benedetti, Devid Maniglio and Valerio Luchin. It shows a mini-tensile sample with as-built surface used in the study (and some internal pores) Read the full paper here: https://lnkd.in/d4CcgEBN #Additive #Manufacturing #Quality #Inspection #Evaluation #Porosity #Xray #Tomography #microCT #IndustrialCT

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There are rumors that Meta is getting rid of VR/MR (Quest) hardware design. And they're significant enough that The Information is reporting them. The Information deals in sourced rumors, nothing random. They're interesting giving how much money Meta/Facebook is losing on VR manufacturing and sales. And that I've heard similar rumors earlier this year. where there is smoke, there is fire. Facebook still is largely run by former web developers. And has never really treated hardware engineers as more than second class citizens. They may be ready to start outsourcing hardware. ----- TheInformation: "Meta to Farm Out Design for Mixed Reality Devices, Shift Some Production From China." (Kalley Huang, Wayne Ma and Juro Osawa) TheInformation: https://lnkd.in/gw9W-Rwg ----- UploadVR: "Meta Denies Claims It Plans To Outsource Quest Headset Design To China" (David Heaney) "Meta's CTO Andrew Bosworth denied claims that Quest headset design will be outsourced to Goertek, the company's Chinese manufacturer. The claim first emerged last week as a rumor spread by former VR developer Cix Liv. Liv claimed Meta's headset design team "is gone", and that Goertek would take over the role "100%". Bosworth directly and publicly denied this in a reply on X. Liv further claimed this would be followed up by mass layoffs in the Quest segment of Meta's Reality Labs division in Q1 2025, as part of a shift away from VR to AR, which Bosworth also denied. The central claim reemerged today, in a far less outlandish form, in a report from The Information which claims that Meta plans to offload much of its Quest hardware development process to Goertek in the future. Meta has worked closely with Goertek to understand the constraints and costs of different approaches since the original Oculus Rift, as part of the design for manufacturability (DFM) process. But The Information claims that Meta plans to shift "the design of components such as lenses and displays to Goertek", and that Goertek has "started designing the outer shell" of future Quest headsets. It even makes the significant claim that Meta wants Goertek to fully design Quest headsets by 2030. However, Meta CTO Andrew Bosworth publicly and directly denied the claim of Quest headset design being outsourced in a series of posts on X, and suggested that the idea was pushed to The Information by the same person who suggested it to Liv. "We continue to design our headsets in house as we have and have no plans to change that," Bosworth writes. "We always partner with our manufacturers to a degree but nothing material is changing there." "Goertek is a great partner and as parts of our stack are more mature and used from headset to headset we're glad to have them carry the designs across which has always been true", Bosworth continued, "But this isn't a change from how we've done business with them even as we scale it up". UploadVR: https://lnkd.in/gz_qf4Ya #xr #vr #ar #mr #spatialcomputing #facebook #oculus #meta

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