Gemini DiffusionGoogle DeepMind
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Point-EOpenAI
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About
Gemini Diffusion is our state-of-the-art research model exploring what diffusion means for language and text generation. Large-language models are the foundation of generative AI today. We’re using a technique called diffusion to explore a new kind of language model that gives users greater control, creativity, and speed in text generation. Diffusion models work differently. Instead of predicting text directly, they learn to generate outputs by refining noise, step by step. This means they can iterate on a solution very quickly and error correct during the generation process. This helps them excel at tasks like editing, including in the context of math and code. Generates entire blocks of tokens at once, meaning it responds more coherently to a user’s prompt than autoregressive models. Gemini Diffusion’s external benchmark performance is comparable to much larger models, whilst also being faster.
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About
While recent work on text-conditional 3D object generation has shown promising results, the state-of-the-art methods typically require multiple GPU-hours to produce a single sample. This is in stark contrast to state-of-the-art generative image models, which produce samples in a number of seconds or minutes. In this paper, we explore an alternative method for 3D object generation which produces 3D models in only 1-2 minutes on a single GPU. Our method first generates a single synthetic view using a text-to-image diffusion model and then produces a 3D point cloud using a second diffusion model which conditions the generated image. While our method still falls short of the state-of-the-art in terms of sample quality, it is one to two orders of magnitude faster to sample from, offering a practical trade-off for some use cases. We release our pre-trained point cloud diffusion models, as well as evaluation code and models, at this https URL.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
AI researchers and developers seeking a tool providing editable text generation by leveraging diffusion-based language modeling
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Audience
Anyone searching for a system for generating 3D point clouds from complex prompts
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Support
Phone Support
24/7 Live Support
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Support
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24/7 Live Support
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API
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API
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Free Version
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Pricing
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Free Version
Free Trial
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Reviews/
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Training
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Live Online
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationGoogle DeepMind
Founded: 2010
United Kingdom
deepmind.google/models/gemini-diffusion/
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Company InformationOpenAI
Founded: 2015
United States
openai.com/research/point-e
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Integrations
Gemini
Gemini Enterprise
WeatherNext
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