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A Big Step for AI: 3D-LLM Unleashes Language Models into the 3D World

by Louis BouchardAugust 11th, 2023

Too Long; Didn't Read

3D-LLM is a novel model that bridges the gap between language and the 3D realm we inhabit. It not only perceives the world but also interacts with it. The world it sees may not be conventionally beautiful, but its understanding is deep-rooted in point clouds and language.

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We've witnessed the remarkable capabilities of large language models (LLMs), but there's been a gap—a missing piece in their understanding of the world around us. They've excelled with text, code, and images, yet they've struggled to truly engage with our reality. That is, until now. Here's a groundbreaking leap forward in the AI landscape: 3D-LLM.

3D-LLM is a novel model that bridges the gap between language and the 3D realm we inhabit. While it doesn't cover the entirety of our world, it's a monumental stride in comprehending the crucial dimensions and text that shape our lives. As you'll discover in the video, 3D-LLM not only perceives the world but also interacts with it. You can pose questions about the environment, seek objects or navigate through spaces, and witness its commonsense reasoning—reminiscent of the awe-inspiring feats we've experienced with ChatGPT.

Intriguingly, the world it sees may not be conventionally beautiful, but its understanding is deep-rooted in point clouds and language. Point clouds, the bedrock of 3D data representation, encode spatial coordinates of objects and environments, enabling AI to interact with the real world in a tangible manner. Think of their role in autonomous driving, robotics, and augmented reality—3D-LLM taps into this realm.

Curiously, you might wonder how such a model was trained to fathom 3-dimensional data and language. The process was innovative and intricate, with the authors constructing a unique 3D-text dataset. They harnessed ChatGPT's prowess to gather this data through three distinct methods you'll learn about, creating a comprehensive repository of tasks and examples for each scene.

From this rich dataset, the authors forged an AI model capable of processing both text and 3D point clouds. The model takes the scene, extracts crucial features through various perspectives, and reconstructs it in a form that resonates with the model's understanding.

The result? The birth of the first 3D-LLM, a model that truly sees and comprehends our world—offering an intriguing glimpse into the evolution of AI. The video offers a snapshot of the journey, but I encourage you to explore the paper for a deeper dive into the impressive engineering feats behind this innovation. The link is provided in the references below.

Enjoy the show!