Загрузка видео...

Не удалось загрузить видео

На главную

> Natural data is "generated" from a constrained hierarchical / compositional function. > Deep networks learns that hidden structure from polynomially few examples and creatively generate exponentially many valid new ones. > The depth of the network is what's important to overcome the curse of dimensionality, and potentially invalidate...

12,887 просмотров • 20 дней назад •via X (Twitter)

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

In collaboration with Intel, our Depth Fusion showcases the power of our LDM3D diffusion model in generating 360° views from text prompts provided by the user. The LDM3D diffusion model generates a 2D RGB image and its corresponding relative depth map providing a complete RGBD representation corresponding to the text prompt. The LDM 3D model is a specialized version of the stable diffusion V 1.4 model that has been modified to fit both image and depth map data.The model was then fine tuned on a subset of the Laion400M data set - large scale image caption data set. The depth maps used to fine tune our model were generated by the DPTBeiT large 512 depth estimation model that provides highly accurate relative depth estimates for each pixel. We take the generated 2D RGB image and depth map and use them to compute a 360° projection using touchdesigner. Touchdesigner is a versatile platform that allows for the creation of immersive and interactive multimedia experiences. Our application harnesses the power of touchdesigner to bring the generated 360° views to life, providing users with a unique and engaging way to experience their text prompts, whether it’s a description of a tranquil forest, a noisy cityscape or a futuristic sci fi world. Our depth fusion can bring these concepts to life in a vivid and immersive detail. - Scottie Fox, VP Engineering Blockade Labs ScottieFox #AI #VR #3D #gamedev #stablediffusion

Blockade Labs

11,439 просмотров • 3 лет назад

🧠 A Beautiful loop: An active inference theory of consciousness. Many psychological, philosophical and scientific approaches have posited that loops, recursion, and reflective broadcasting are somehow central to the emergence of consciousness in hierarchical complex apparatus such as the nervous system. The geometrodynamics of the experiential reality model itself continuously looping and conforming its own existence. The capacity to reiterate the cognitive process in a variety of states like attention, metacognition, sleep, lucidity, meditation and psychedelic is the cornerstone for the emergence of consciousness. In this scientific study are proposed three conditions necessary to the functionality of self awareness. 1st) Generative World Model Epistemic Field. This model represents the brain's internal representation of the world, which is continuously updated throughout sensory inputs and prior knowledge. 2nd) Inferential Competition Determining Conscious Content. The inferential competition is necessary for determining what becomes conscious and why it’s coherent. This competition arises from the brain's attempt to resolve uncertainty and ambiguity in its internal models. 3d) Epistemic Depth Recursive and Widespread Sharing. The epistemic depth refers to the recursive and widespread sharing of the epistemic field throughout the hierarchical structure, and it’s a fundamental component for consciousness. 🔗

Maurizio Iβλἄ

18,220 просмотров • 1 год назад