We're happy to be providing the resources for this research, which has resulted in the the best and largest open source CLIP model currently available! ↓
MULTIMODAL AI
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Internet of Senses: Future Stadium Experience Immersion
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Absolutely, greater immersion in the experience plus the opportunity to truly feel part of it as well – a dynamic trajectory here for the future stadium I experience I think – internet of senses 🙂 S
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Imagen Outperforms DALL-E2, Stable Diffusion Leads Open Source
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Imagen was released right after DALL-E2, and in their tests with human raters, it outperformed DALL-E2. Stable Diffusion is of course the most useful one as it is open source and people can build on top of it.
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Cerebras Enables Larger Image Semantic Segmentation Training
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Cerebras has made it possible to train and run inference on semantic segmentation models on images larger than can be done on GPUs today. pic.twitter.com/K938yfuFlF
— Cerebras (@cerebras) 3 février 2023Cerebras has made it possible to train and run inference on semantic segmentation models on images larger than can be done on GPUs today.
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PADL: Language-Directed Physics-Based Character Control
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PADL: Language-Directed Physics-Based Character Control Juravsky et al.: https://
arxiv.org/abs/2301.13868 #Artificialintelligence #DeepLearning #ReinforcementLearning -
Stable Diffusion: Text-to-Image Generation with Diffusion Models
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Stable Diffusion is a latent text-to-image diffusion model capable of generating stylized and photo-realistic images within seconds.
— Satya Mallick (@LearnOpenCV) 2 février 2023
To learn more, check out our Introduction to Diffusion Models for Image Generation.https://t.co/wcPfq7tgwQ#stablediffusion #imagegeneration #ai pic.twitter.com/f1dxK35mA5Stable Diffusion is a latent text-to-image diffusion model capable of generating stylized and photo-realistic images within seconds. To learn more, check out our Introduction to Diffusion Models for Image Generation. https://
learnopencv.com/image-generati
on-using-diffusion-models/
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@dfintelligence — 2023-02-02
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Imaginez adapter un visage et les lèvres d’un acteur en fonction des mots qui sont dits.
— Defend Intelligence (Anis Ayari) (@DFintelligence) 2 février 2023
C’est possible avec des méthodes d’#IntelligenceArtificielle qui permettent par exemple d’enlever les insultes ou de changer les lèvres en fonction de la langue parlée. C’est ouf non ? pic.twitter.com/GA8FnTGjpkImaginez adapter un visage et les lèvres d’un acteur en fonction des mots qui sont dits. C’est possible avec des méthodes d’#IntelligenceArtificielle qui permettent par exemple d’enlever les insultes ou de changer les lèvres en fonction de la langue parlée. C’est ouf non ?
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CiT: Data Curation Methods for Vision-Language Model Training
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(5/12) CiT: Curation in Training for Effective Vision-Language Data
Authors: Hu Xu, @sainingxie
, Po-Yao Huang, @Licheng_Yu
, Russell Howes, Gargi Ghosh, Luke Zettlemoyer, @cfeichtenhofer -
AR technology and generative models: software’s victory over physical world
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No tengo dudas de que eventualmente la tecnología de realidad aumentada (AR) potenciada además por todos los avances en visión por computador, modelos generativos, etc, será una victoria del software frente al mundo físico
— Carlos Santana (@DotCSV) 1 février 2023
Y un respiro medioambiental sin tanto producto físico?🤔 https://t.co/QdQv1tTOZqNo tengo dudas de que eventualmente la tecnología de realidad aumentada (AR) potenciada además por todos los avances en visión por computador, modelos generativos, etc, será una victoria del software frente al mundo físico Y un respiro medioambiental sin tanto producto físico?
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Genmo Storytelling: Chain Prompts for Immersive Generative Art
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4. Storytelling Capabilities: Genmo allows you to chain multiple prompts and create a story through your generative art. The result is an interactive and immersive experience for your audience.