#3779 Google Gemini 2.5 Pro with Meta Quest 3s; ++ 3D SVG (Actually STL); ++Stacked SVG's
#3779 Google Gemini 2.5 Pro with Meta Quest 3s; ++ 3D SVG (Actually STL); ++Stacked SVG's
#3779 Think hard. Think innovatively. How can I use the creative ability of Google Gemini 2.5 Pro within Meta Quest 3s?
Using the creative abilities of Google Gemini 2.5 Pro within the Meta Quest 3 presents a fascinating opportunity to merge advanced reasoning and multimodal understanding with the immersive, spatial computing environment of mixed reality. While there isn't a direct, out-of-the-box integration between the two platforms, the synergy lies in leveraging their respective strengths through clever development and application design.
Here’s a breakdown of how you could use Gemini 2.5 Pro's capabilities within the Meta Quest 3, from current possibilities to innovative, forward-thinking concepts.
Key Gemini 2.5 Pro Capabilities to Leverage
Deep Think Mode: This is a core feature that allows the model to "think" through problems, evaluate multiple possibilities, and arrive at more accurate and nuanced responses.
In a VR/MR context, this is crucial for tasks requiring complex problem-solving. Multimodal Capabilities: Gemini 2.5 Pro can understand and generate content across text, code, images, audio, and video.
This is the bridge between the digital and physical worlds in a mixed reality environment. Computer Use Model: This specialized model can interpret screenshots of a user interface and generate actions (like clicks, drags, and typing) to complete tasks.
This is a game-changer for agentic applications. Long Context Window: The 1-million token context window allows the model to process and reason over massive amounts of information in a single session, such as entire books or complex technical manuals.
Code Generation and Debugging: The model excels at generating and debugging code, which is invaluable for creative applications.
Innovative Applications and Use Cases
1. The Interactive Creative Co-Pilot
Concept: A mixed reality application where Gemini 2.5 Pro acts as a creative partner. Instead of just a chatbot, it's an intelligent entity within your virtual space.
How it works:
You, as the user, might be a 3D artist. You describe the object you want to create with a simple prompt: "Create a steampunk airship that's half-bird, half-machine, and can be disassembled."
Using its Deep Think Mode and code generation capabilities, Gemini 2.5 Pro could analyze the request, generate 3D models and textures, and even write the code for the interactive elements (e.g., how the parts disassemble and reassemble).
The model then visualizes these elements directly in your mixed reality space, allowing you to manipulate them with your hands.
You could use a passthrough view to place the virtual airship on your real-world coffee table. As you interact with it, you can ask Gemini 2.5 Pro questions like, "What's the best way to animate the wings so they look more organic?" and it could provide a detailed, step-by-step response and even a code snippet for the animation, visualized as a series of instructions floating in the air.
2. The Dynamic Architectural Designer
Concept: A powerful tool for architects and interior designers that uses Gemini 2.5 Pro's reasoning and multimodal capabilities to iterate on designs in real-time within a physical space.
How it works:
Using the Quest 3's passthrough camera, you scan your physical room. The Quest 3's spatial mapping tools create a digital mesh of the environment.
You ask Gemini 2.5 Pro, "Generate three different layout options for a modern minimalist living room in this space. Take into account the window and the natural light source."
Leveraging its Deep Think Mode and multimodal understanding, the AI analyzes the room's dimensions and light sources, and then generates three distinct layouts. It places virtual furniture, lighting, and art in the room, seamlessly blended with the physical environment.
You can then walk through each design, give verbal feedback ("Make the couch bigger," or "Move the bookshelf to the other wall"), and Gemini 2.5 Pro adjusts the virtual scene instantly. This is a form of agentic behavior where the AI is not just creating, but also responding to and executing your commands in a complex, three-dimensional space.
3. Agentic Task Automation in Mixed Reality
Concept: The Gemini 2.5 Computer Use model could be adapted to operate within a mixed reality interface, effectively creating a super-powered virtual assistant.
How it works:
You're wearing your Quest 3 and have a virtual browser window open in your mixed reality space.
You say, "Gemini, find me the best-rated Italian restaurant in this neighborhood and make a reservation for two tonight at 7 PM."
The Gemini Computer Use model would take a "screenshot" of the virtual browser, navigate to a review site, find the best-rated restaurant, then go to its website, and fill out the reservation form—all while you watch the process unfold in a holographic window.
The model would use its reasoning to understand the request, its UI action capabilities to execute the steps, and its ability to handle long-form context to recall details like the number of people and time of the reservation.
Technical Integration and Challenges
Cloud-based Processing: Given the complexity of Gemini 2.5 Pro, the processing would need to be done in the cloud. The Quest 3 would act as the client, sending audio, video, and other sensor data to Google's servers via the Gemini API. The AI would then send back commands, text, and data to be rendered in the Quest 3 environment. This is supported by the fact that Meta has a cloud computing partnership with Google Cloud for AI infrastructure.
API and SDK Bridge: Developers would need to create a bridge between Meta's development platforms (like the Meta Spatial SDK, Unity, or Unreal Engine) and Google's Gemini API. This would involve taking input from the Quest's microphones and cameras, formatting it for the API, and then translating the AI's output into rendered visuals and actions within the mixed reality scene.
Performance and Latency: The success of these applications would depend heavily on low latency. The Quest 3 has a powerful processor, but network latency could be a challenge for real-time, high-fidelity interactions. Google's focus on low latency for its Computer Use model and its collaboration with Meta on cloud infrastructure suggests this is a solvable problem.
In summary, integrating Google Gemini 2.5 Pro with Meta Quest 3 isn't just about running an AI model on a headset. It's about combining the AI's "brain" (deep reasoning, multimodal understanding) with the Quest's "body" (spatial awareness, mixed reality passthrough, and hand tracking) to create a new class of applications that can understand and interact with the physical and digital worlds in profoundly new and creative ways.
Is there such a thing as 3D SVG?
While SVG (Scalable Vector Graphics) is a powerful 2D vector format, there is no official, standardized "3D SVG" file format from the W3C (World Wide Web Consortium), the organization that governs web standards. SVG is designed to be a "presentation format" for 2D graphics, not a "data-interchange format" for complex 3D models.
How SVG is Used in a 3D Context 🎨
Even though a native 3D SVG format doesn't exist, this doesn't mean SVG can't be used in 3D workflows.
Extrusion: One of the most common methods is to extrude a 2D SVG shape into a 3D object.
This is like taking a cookie cutter and pushing it through a slab of dough to create a 3D shape with a uniform thickness. Many 3D modeling programs and online converters can take a clean SVG file and extrude it into a 3D model in formats like .STL or .OBJ. This is particularly useful for creating logos, text, or simple, uniform shapes for 3D printing or use in a game engine. 3D Papercraft: Some crafters and hobbyists use the term "3D SVG" to refer to a series of 2D SVG files that are designed to be cut out and folded into a 3D object, such as a paper sculpture. These are not true 3D models in the digital sense but are a clever use of the SVG format for a three-dimensional physical craft.
Web-based 3D: With libraries like Three.js and frameworks like X3D, developers can render 2D SVG files within a 3D web environment. This allows for placing a flat SVG graphic on a 3D plane or using it as a texture. While not a 3D SVG format, it creates a 3D experience using SVG assets.
So, while there is no official 3D version of SVG, its vector-based nature makes it an excellent starting point for creating 3D content through various conversion and rendering processes.
This video demonstrates how to take a 2D SVG file and convert it into a 3D object using Blender.
3D SVG is not a standard format; it's a term used to describe a process where a 2D SVG file is converted into a 3D model, typically for purposes like 3D printing. SVG and STL files are fundamentally different in their purpose and structure, yet they can be used in the same workflows.
Differences 🗂️
Dimensionality: This is the key difference. An SVG (Scalable Vector Graphics) file is a 2D vector format that uses mathematical paths and points to define shapes.
An STL (STereoLithography) file is a 3D mesh format that represents the surface of a three-dimensional object as a collection of interconnected triangles. Data Stored: An SVG file is compact and stores data about lines, curves, and colors, making it ideal for web graphics, logos, and simple designs. An STL file stores only geometric data about the object's surface; it doesn't support color, texture, or material properties, which is a major limitation for modern 3D printing.
Use Case: SVG is perfect for applications that require scalable 2D graphics, like laser cutting and CNC machining.
STL is the universal standard for 3D printing because it describes the geometry of a solid object.
Similarities 🤝
Vector-based Foundation: While an STL is a mesh, it's often created from a vector-based starting point. Many 3D modeling programs begin with a 2D sketch or shape and then "extrude" it to give it depth, a process that is often started with an SVG file.
Both formats are based on mathematical descriptions of shapes rather than pixels. Conversion and Workflow: You can't directly use an SVG for 3D printing, and you can't use an STL for 2D laser cutting, but they are often part of the same production workflow. It's a common practice to convert a 2D SVG file into a 3D STL file by extruding the shape. This makes the two formats complementary rather than competing.
This video on how to make an STL from an SVG demonstrates how they can be used together in a 3D printing workflow.
Explain how SVG works
SVG, or Scalable Vector Graphics, is an XML-based language for describing two-dimensional vector graphics. Unlike raster images (like JPEGs or PNGs) that are composed of a fixed grid of pixels, SVG files are made up of mathematical formulas and instructions that tell a browser or program how to draw the image.
How it Works ⚙️
Instead of storing data for each individual pixel, an SVG file is a text file containing commands that define shapes, lines, colors, and text. For example, a simple SVG file for a red circle might look something like this:
<svg width="100" height="100">
<circle cx="50" cy="50" r="40" stroke="black" stroke-width="3" fill="red" />
</svg>
When a browser or SVG viewer encounters this code, it reads the instructions:
<svg>: Creates an SVG canvas with a width and height of 100.<circle>: Draws a circle.cx="50" cy="50": Positions the center of the circle at coordinates (50, 50).r="40": Gives the circle a radius of 40.fill="red": Fills the circle with the color red.
This mathematical approach is what makes SVG files infinitely scalable without any loss of quality. No matter how much you enlarge the image, the browser simply recalculates the positions and dimensions of the shapes to render a sharp, clean image.
Key Concepts 🔑
Vector vs. Raster: The core difference is the data format. A raster image (e.g., a photo) is a static map of colored pixels. A vector image (SVG) is a set of dynamic instructions that can be scaled to any size. This makes SVGs perfect for logos, icons, and illustrations.
XML Structure: An SVG file is a form of XML, a markup language similar to HTML. This means its content is readable by both humans and machines, and it can be easily styled with CSS or manipulated with JavaScript through the Document Object Model (DOM).
Coordinate System: SVG uses a 2D Cartesian coordinate system with the origin (0,0) at the top-left corner of the canvas. The x-axis extends to the right and the y-axis extends downward.
"Painters Model": The rendering process of an SVG document follows a "painters model," where elements are drawn in the order they appear in the code. Later elements are painted "on top of" earlier ones.
Interactivity: Because SVGs are XML and have a DOM, you can add interactivity and animation using scripting languages like JavaScript. This allows for dynamic, interactive charts, graphs, and UI elements.
It seems like an easy step to create an SVG-3D format
Despite what seems like a logical next step, creating a standard "3D SVG" format is far from simple and faces significant challenges. The fundamental issue is that SVG is a 2D presentation format, not a 3D data-interchange format.
Why a "3D SVG" Standard is Difficult 🚧
From 2D to 3D: SVG's core strength is its ability to describe 2D shapes with a clear, mathematical structure. Introducing a third dimension would require a complete re-imagining of its coordinate system, the rules for describing shapes, and how those shapes are rendered in space.
The Painter's Model: SVG uses a "painter's model," where objects are layered on top of each other. This concept doesn't translate well to a 3D environment, where objects can be behind or in front of each other, and a single view of the object can change drastically with rotation.
A New Set of Data: 3D models require a different set of data to be described accurately. While a 2D circle can be described by a center point and a radius, a 3D sphere needs additional information like a radius on the z-axis to be fully defined. This means a new, more complex set of commands would have to be created.
The Problem of Primitives: While a "3D SVG" could theoretically use geometric primitives like spheres and cubes, it would still fail to describe the vast majority of 3D models, which are often complex, free-form meshes. 3D formats like STL or OBJ are built to describe these complex shapes using vertices and triangles, a function that is completely outside the scope of SVG.
Existing Solutions and the Problem with Them 🤔
The web development community has experimented with creating 3D experiences using SVG, but these are often limited in scope.
X3D: This is a standard from the Web3D Consortium that uses XML to describe 3D scenes. It's often referred to as a "3D equivalent" to SVG. However, it's not a direct extension of SVG, and it never gained the widespread adoption that SVG did.
CSS and Libraries: Developers can create some simple 3D effects on 2D SVG shapes using CSS transforms and JavaScript libraries like Three.js. However, these methods are primarily for visual effects, not for creating or storing a true, editable 3D object.
In short, a direct extension of SVG into a 3D format would require a complete overhaul of its fundamental design. While it's not impossible, the industry has largely converged on other file formats like glTF and USDZ for 3D data-interchange, leaving little need for a new standard built from a 2D foundation.
Describe how STL works
An STL file represents the surface geometry of a 3D model as a collection of tiny, connected triangles, a process called tessellation 📐.
The STL File Structure
An STL file is a very simple and efficient format that only stores two key pieces of information for each triangle:
The vertices (corners): The
(x, y, z)coordinates for each of the triangle's three points.The normal vector: A set of
(x, y, z)coordinates that defines a vector perpendicular to the triangle, pointing outwards from the object's surface.This tells the 3D printer which side of the triangle is the "outside."
The data for all the triangles is stored in a long list.
Two Types of STL Files
There are two main types of STL files, both of which contain the same information but in different formats:
ASCII (text): This is a human-readable text file where the data is written out with keywords like
solid,facet normal, andvertex.These files are much larger than binary files, which can make them slow to process. Binary (compressed): This is a more compact, non-readable format that stores the data as binary code.
Because of their smaller file size, binary STL files are the most common format used in 3D printing.
From STL to 3D Print
The STL file is the intermediate step between a CAD (Computer-Aided Design) model and the final print.
A designer creates a 3D model using CAD software.
The software exports the model as an STL file, triangulating its surface based on resolution settings (e.g., chordal tolerance).
The STL file is loaded into slicer software, which "slices" the 3D model into hundreds or thousands of 2D layers.
The slicer software then generates G-code, a set of instructions that tells the 3D printer exactly how to move and extrude material layer by layer to build the final object.
Describe how gen-ai could use a stack of svg's to create a 3D model
Generative AI could use a stack of SVGs to create a 3D model through a process known as 2D-to-3D reconstruction. This method is particularly powerful with vector graphics because the AI can leverage the SVG's precise mathematical data rather than the pixel information of a raster image.
The Process: A Step-by-Step Breakdown
Data Ingestion and Analysis: The AI would first ingest a series of SVGs. For this to work, the SVGs must be "slices" of a single object, arranged in a specific order (e.g., from top to bottom, or front to back). The AI's generative model, likely a 3D-aware GAN (Generative Adversarial Network) or a Diffusion Model, would analyze the vector data, including the paths, shapes, and their spatial relationship across the stack.
Feature Extraction: Instead of just seeing flat shapes, the AI would be trained to understand the implicit 3D information. It would look for correlations between the SVGs, such as:
Morphological Changes: How a shape gradually changes from one slice to the next. For instance, how a circle becomes an oval, then a square, in a stack of SVGs.
Structural Consistency: Identifying consistent elements across slices that define the overall structure of the object. The AI can use the vector data to extrapolate details and fill in gaps between slices.
Voxel or Mesh Generation: The AI would then translate the extracted features into a 3D representation. There are two main approaches:
Voxel Grid: The AI could generate a grid of 3D pixels (voxels), where each voxel is either filled or empty. This is like building a 3D model out of tiny digital Lego bricks.
Mesh Generation: A more complex approach is to generate a 3D mesh—a surface made of interconnected triangles—that connects the shapes from each SVG slice. The AI would essentially "bridge" the gaps between the 2D outlines to form a smooth, continuous 3D surface.
Refinement and Texturing: Once a base 3D model is created, the AI could refine it. The mathematical precision of the SVGs would allow the model to retain sharp edges and curves. The AI could also use the color and fill information from the SVGs to create a texture map and apply it to the 3D surface, giving it a final, polished look.
This process is similar to how AI is used in medical imaging to create a 3D model of an organ from a series of 2D MRI or CT scans. The SVG's vector data provides a cleaner, more precise input than a pixelated image, making the reconstruction more accurate and efficient.
This video on how to create a 3D model from a single 2D image demonstrates the AI-powered tools that are already available to do so.
Would Mathematica supported by Wolfram LLM Took Kit be useful in building 3D models from SVG's?
Yes, Mathematica supported by the Wolfram LLM Toolkit would be useful for building 3D models from SVGs, especially for creating mathematically precise and editable shapes. While current generative AI models can convert a single 2D image into a 3D model, the Wolfram Language's unique approach and its new LLM capabilities could enable more sophisticated, rule-based 3D modeling from vector graphics.
The Power of the Wolfram Language and LLMs 🧠
The Wolfram Language, which powers Mathematica, is built on a foundation of symbolic representation.
How it Would Work: A Step-by-Step Scenario
Natural Language Prompt: You start with a conversational prompt, such as, "Take this stack of SVGs representing a turbine blade and extrude them into a 3D model. Then, smooth the surface and export it as an STL file for 3D printing."
LLM Translation: The Wolfram LLM Toolkit would interpret this prompt and generate the necessary Wolfram Language code.
It would know to use functions like Importto load the SVG files,Graphics3Dto work with 3D graphics, and specific commands for geometric operations.Extrusion and Lathing: The system can execute extrusion, which is the process of giving a 2D shape depth, or revolution plotting, which spins a 2D curve around an axis to create a 3D object. The LLM would generate code to apply these operations to your SVGs based on the prompt's instructions.
Mathematical Precision: Because the Wolfram Language works with symbolic representations, the resulting 3D model would be mathematically precise, not an approximation.
This is ideal for engineering, scientific visualization, or creating models that need to be a specific size. Refinement and Export: After creating the initial model, the LLM could generate additional code to refine it, such as by smoothing the surface, applying colors, or adding other features. Finally, the model can be exported to standard 3D formats like STL, OBJ, or GLTF. The Wolfram Language supports importing and exporting a variety of 3D geometry formats.
This video showcases how the Wolfram Notebook Assistant, a tool that uses an LLM, can turn conversational input into precise computational code within Mathematica.
In place of revolution plotting, could a radial graph plot be used for each layer?
Yes, a stacked radial graph plot could be used as a method to create a 3D model. While revolution plotting creates a 3D object by rotating a single 2D profile, stacking radial graphs is a method of 2D-to-3D reconstruction. It works by using a series of 2D cross-sections to define the geometry of a 3D object along an axis.
How it's different from revolution plotting 🔄
Revolution plotting is limited to creating objects with an axis of symmetry, like a vase, a bowl, or a tire. The entire 3D object is generated from a single 2D profile that is revolved around a central axis. This is a very efficient way to create simple 3D shapes.
Stacking radial graphs is a more versatile approach. Each radial graph represents a unique "slice" of the object at a specific point along an axis (e.g., the z-axis). You can think of it like an MRI scan, where each image is a cross-section of the body. By stacking these slices and connecting the corresponding points, you can build a complex 3D shape that doesn't have to be symmetrical.
The workflow using SVGs and Gen-AI 🤖
Input: The process would start with a stack of SVGs, where each SVG is a radial plot representing a 2D cross-section of the object. For example, if you wanted to model a lopsided vase, each SVG would be a different oval or non-circular shape that gradually changes.
Analysis: A generative AI would take these SVGs, analyze the path data and vertices of each one, and identify how the shapes morph from one layer to the next. The AI would essentially find the corresponding points on each SVG slice.
Interpolation: The AI would then use a mathematical function to interpolate the space between each SVG slice, creating new points and faces to form a smooth surface. This is a crucial step that distinguishes this method from a simple stack of 2D shapes. The result would be a 3D mesh made of interconnected triangles or polygons.
Output: The final 3D mesh would be exported as a standard file format like STL or OBJ, which can then be used for 3D printing or further editing.
This method is particularly powerful because it allows for the creation of complex, non-symmetrical 3D forms that cannot be created with revolution plotting. It's a key technique used in scientific visualization and medical imaging, which generative AI can now automate.
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From <https://gemini.google.com/app/> Google Gemini 2.5 Pro
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