#SIGGRAPHAsia2024 🔥 Replace your Marching Cubes code with our... Occupancy-Based Dual Contouring to reveal the "real" shape from either a signed distance function or an occupancy function. No neural networks involved. Web:show more

I've been digging into what Roblox is working on... with Terrain. There's an ongoing effort to switch from an occupancy model to a SDF model (signed distance field) In practice voxels aren't stored as a [0 to 1] value anymore, it's a [-1 to 1] value.show more

If your AI can't call a function or hit... an API, it's not really an agent (it's a chatbot). Vision Agents makes it simple to connect MCP servers and function calling so your model can interact with its surroundings: running code, fetching data, and automating tasks. Step-by-step implementation from Stefan in thread ⬇show more

🔥 TypeScript Tip 🔥 Here, we build a function... that creates zod schemas from your own interfaces, with full autocomplete. The lesson? It's often really hard to get autocomplete when your function _accepts the results of another function_.show more

Flexible Isosurface Extraction for Gradient-Based Mesh Optimization paper page:... This work considers gradient-based mesh optimization, where we iteratively optimize for a 3D surface mesh by representing it as the isosurface of a scalar field, an increasingly common paradigm in applications including photogrammetry, generative modeling, and inverse physics. Existing implementations adapt classic isosurface extraction algorithms like Marching Cubes or Dual Contouring; these techniques were designed to extract meshes from fixed, known fields, and in the optimization setting they lack the degrees of freedom to represent high-quality feature-preserving meshes, or suffer from numerical instabilities. We introduce FlexiCubes, an isosurface representation specifically designed for optimizing an unknown mesh with respect to geometric, visual, or even physical objectives. Our main insight is to introduce additional carefully-chosen parameters into the representation, which allow local flexible adjustments to the extracted mesh geometry and connectivity. These parameters are updated along with the underlying scalar field via automatic differentiation when optimizing for a downstream task. We base our extraction scheme on Dual Marching Cubes for improved topological properties, and present extensions to optionally generate tetrahedral and hierarchically-adaptive meshes. Extensive experiments validate FlexiCubes on both synthetic benchmarks and real-world applications, showing that it offers significant improvements in mesh quality and geometric fidelity.show more

"There is no basis under federal law to get... the post office involved in monitoring the security, or monitoring who is casting ballots. That's that's always been a state function. It's not a function of the federal government. And Donald J. Trump, by directing the Postal Service to issue a regulation, can't make it an issue that's governed by federal law. It has to be done either by the Constitution, I think, or by Congress—if the Constitution authorized Congress to do that, and I'm not sure it does."show more

This video, created by my dear coauthor Mahdi E... Kahou for our teaching and papers, shows how overparameterized neural networks produce smooth function approximations even in the context of the Runge phenomenon. Some background. Imagine you want to approximate the Runge function using polynomial interpolation at equally spaced points. It is well known that, despite targeting an infinitely differentiable function, such a polynomial approximation produces oscillatory behavior that worsens with the degree of the polynomial. In other words, higher-degree polynomial approximations might not improve accuracy. Instead, approximate the Runge function with a neural network (here, two layers are just to make the example concrete; nothing fundamental depends on it). As you increase the number of parameters well above the 11 training points (in our example, a two-layer neural network with 128 nodes each), you nicely converge to the target, without wild oscillations. Yes, this has much to do with double descent and benign overparameterization, but the main punchline of this post is that neural networks are really very different types of animals than polynomial approximations. And yes, Chebyshev nodes and splines exist, and in this case, they will prevent the oscillations. But that's not the point. Chebyshev nodes and splines still confront Faber’s theorem, which states that for any system of polynomial interpolation nodes, there exists a continuous function whose sequence of interpolating polynomials diverges as the number of nodes grows to infinity. Faber’s theorem does not apply to neural networks because they are not polynomials. The notebook, if you want to check the details, is here: Stay tuned for more on this 👀show more

No more forgetting tasks from the last Anno session... or why you sent your ship to this random place on the map! With the note function of the upcoming update, you can set yourself handy reminders.show more

we live in a $TAO simulation in a few... months we went from a whitepaper, a concept, a dream (kinda) to now generating 3d simulations based on our own neural network (that we’re training using Celium btw) this is what Score - Subnet 44 is about: > collecting visual data > creating visual models > generating a ‘real time’ positional value function aren’t you entertained? I love this game!show more

Bangladesh polls At the moment, Bangladesh is supposed to... function on the basis of its existing constitution, which is the 1972 Constitution. There is absolutely no provision in it for either a referendum or an interim authority: Subir Bhaumik | Senior Journalist & Author #NewsToday | Rajdeep Sardesaishow more

Function calling is a powerful way to extend the... capabilities of LLMs and AI agents by letting them use external tools. Our new short course Function calling and Data Extraction with LLMs, created with @NexusflowX and taught by Jiantao Jiao and Venkat, demonstrates how to prompt LLMs to form calls to external functions. You'll work with NexusRavenV2-13B, a 13B parameter open-source model that excels in function calling tasks while still being small enough to host locally. Learn to use function calling to extract structured data from unstructured text and access web APIs, and build an end-to-end application that processes customer service transcripts. You'll learn how to build LLM-powered applications that can analyze feedback, automate data entry, and enhance search. Please get started here:show more

Let's start the new year with an Airdrop based... on your 𝕏 account age coming to $SOL!💧 🟢 Claim Now: 🎁 Get your Mystery Code: Leave a comment and send your comment link in our DM to get your code. (First 1000 people)show more

Is the "light at the end of the tunnel"... actually a trap made to keep our soul stuck in the 3D simulation? Could the fact that there's been an explosive uptick in children reporting past-life memories...be a hint that the memory-wiping function of this soul-recycling system has been either weakened, or destroyed? 🤔show more

How to Create a Spinning Globe 🌍 with Your... Own Data Layers (No Coding Required) Learn how to create a spinning 3D globe map without writing any code using a simple web-based tool. In this step-by-step geospatial tutorial, you'll see how to build an interactive spinning globe, overlay raster and vector data layers, and visualize datasets directly in your browser or in a Jupyter Notebook environment. Web-based demo: Jupyter notebook demo: Video tutorial: #geospatial #opensource #python #jupyter #maplibreshow more

We’re excited to be integrating SERV Reasoning by OpenServ... to bring our no-code robotics solution to market, and had the pleasure of joining their closed beta. Advanced robotics used to require a full team of specialists. Now you can build real behavior in our no-code studio — this Unitree G1 hand grasp function was entirely written by the serv-standard model inside ROBA's no-code studio. This is just a small glimpse of what can be done in our platform. In our benchmarks across real builder tasks, SERV's models matched the quality bar we needed while cutting AI costs by over 80%. SERV Reasoning will now be the default inference engine for the upcoming release of our ROBA no-code studio on June 1st.show more

Sabine Hossenfelder On The Double-Slit Experiment: "You either have... to accept a faster-than-light update of the wave function… or you have to accept that the future is fully determined already." Einstein called it "spooky action at a distance." The wave goes through both slits. Measure at one slit, the other slit updates instantly, even if the particle never hits your detector. The particle somehow “knows” you’re trying to measure it.show more

🚨RFK Jr. warns of the dangers of gain-of-function research:... "Lyme disease almost certainly came from these experiments, which is now devastating our country." "RSV came from a laboratory, which is now the biggest killer of children in our country." "And of course, COVID-19... all of those have been linked credibly to gain-of-function research." "So it's something with enormous cost and no proven benefits." Robert F. Kennedy Jrshow more