![]() ![]() Mobile-friendly Frame Data for Mario in Super Smash Bros. You can find a few examples of shapecasting around: for example, if you check out SSBU frame data you can see that they have spherecasts in their animation frames which determine the hitbox: Ultimate Frame Data Mario - Ultimate Frame Data It’s also not completely consistent since some of our enemies are not mesh deformed, so we’ve had to make at minimum three different ways to raycast to catch all of our use cases appropriately. Our current method of slapping attachments all over the enemies isn’t sustainable in the long run and it’s slightly tedious to set up, especially with mesh deformed rigs. ![]() Since we don’t have shapecasts, we need to rely on other methods: several hundred or thousand raycast points, Touched (sort of ew to rely on physics for hitboxes), information from Bones to create raycast points and so on. Shapecasting would be really good for our use case since we have mesh deformed enemies as well as enemies that perform large scale attacks. Think raycasting but you aren’t restricted to a line. Please share any feedback you have with the team here. We have a bit of work remaining for accelerating some narrowphase routines, but the majority of the performance improvements should be visible in your maps right now! These changes have been rolling out slowly over the past few months, with one of the bigger changes (the broadphase rewrite) having just released a few days ago. You can expect between a 10x improvement on long rays in huge maps with many large parts, to a 0x improvement on a completely empty map. The performance difference varies based on the workload. Improved the memory layout of physics parts for better spatial locality.Started caching part bounding boxes directly on each part.Used hardware intrinsics ( SIMD) to speed up the most common tests, e.g.New top-down broadphase traversal algorithm.Add ray-OBB test for parts to reduce how many times we fall through to more expensive narrowphase.More optimal broadphase → midphase → narrowphase test ordering.We did a deep dive into the raycast systems and decided to go with a partial rewrite: Time invested in making these faster massively benefits the platform with improvements such as more performant avatars, cameras, etc. Developers use them for collisions, bullets, tracers, suspensions, lasers, and other things that need a high degree of customization. System Information Operating system: Windows-10-0-SP0 64 Bits Graphics card: NVIDIA GeForce RTX 2070 SUPER/PCIe/SSE2 NVIDIA Corporation 4.5.0 NVIDIA 496.13 Blender Version Broken: version: 3.0. Roblox uses them internally for Humanoid motion, BillboardGuis, Poppercam, ProximityPrompts, draggers, and other uses that need simple physical queries. Raycasts are the foundation for large chunks of our technical stack. We’ll be sharing the progress with you here along with some fun technical details.Īlso, the max distance of raycasts has been raised from 5,000 → 15,000 studs! Why Improve Raycasts? Groups that have adopted the platform are seeing significant increases in HCC-RAF (Risk Adjustment Factor) scores, which translates into millions of dollars in revenue.We recently made some big internal upgrades to improve the performance of raycasts (ie WorldRoot:Raycast). Navina has also proven itself to increase practice revenue. The round was led by Accel and Coatue with participation from angel. The company has been invited by the American Academy of Family Physicians to be part of its Innovation Lab. Raycast, a London, UK-based platform that provides developers quick access to their tools, raised 15m in Series A funding. Navina's AI-based insights bring potentially missed diagnoses to the attention of physicians, highlighting opportunities for better, more preventive patient care. The platform provides clinicians with precise data as well as offering recommendations. Software Category: AI-powered clinical platformĪbout the Company: Navina created the first AI-based model that understands the complex language of primary care patient data. The additional funding will allow Navina to accelerate investment in its AI technology, and expand within physician groups and the enterprise healthcare market.Īdditional Investors: Schusterman Family Investments (SFI) and Grove Ventures This brings the company’s total funding to date to $22 million, raised within 12 months after the commercial launch. ![]() The round was led by Vertex Ventures Israel, with Schusterman Family Investments (SFI) and existing investor Grove Ventures also joining the round. Navina, an Israel-based startup developer of an AI-powered clinical platform for primary care, secured $15 million in Series A. ![]()
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