Generate text-to-music-video, powered by @riffusionai and @StableDiffusion
. It works surprisingly well and is able to generate up to 10 second long videos. Come check it out at: https://
huggingface.co/spaces/DGSpitz
er/TXT-2-IMG-2-MUSIC-2-VIDEO-w-RIFFUSION
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MULTIMODAL AI
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Text-to-Music-Video Generator Powered by Riffusion
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Marvel IP and Advanced Compute: Future of Creative AI
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Agreed. The delta will close, but the envelope will also push to higher heights. Just imagine — what will Marvel do with their IP + combined with an insane amount of compute and technical artistry!
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Latest AI Breakthroughs Showcased at CES Las Vegas
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Latest Breakthroughs In Artificial Intelligence On Display At CES Trade Show In Las Vegas – Forbes Read more here: https://
ift.tt/HyK8k9D #ArtificialIntelligence #AI #DataScience #100DaysOfCode #Python #MachineLearning #BigData #DeepLearning #NLP #Robots #IoT -
AI Transforms Filmmaking: Creating Years of Work in Minutes
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Foundation #AI goes to the movies
"A.I. could create in minutes what a filmmaker worked on for years" https://
nytimes.com/interactive/20
23/01/13/opinion/jodorowsky-dune-ai-tron.html?searchResultPosition=1
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Scaling Laws for Generative Mixed-Modal Language Models
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Introduces scaling laws for generative mixed-modal language models. 9 of 11
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New Multimodal Deep Learning Book Published on ArXiv
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Multimodal deep learning is a new book published on ArXiv. 4 of 11
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Top Machine Learning Papers of the Week
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Top ML Papers of the Week (Jan 9-15): – DreamerV3
– DeepMatcher
– Multimodal deep learning
– Transformer compiler for RASP
– Potential misuses of LMs and mitigations
– Scaling laws for generative mixed-modal LMs
– Time series forecasting with generative modeling
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Phenaki compresses video to discrete tokens with causal attention
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Phenaki, developed by Google Research, compresses the video to a small representation of discrete tokens. This tokenizer uses causal attention in time, which allows it to work with variable-length videos. pic.twitter.com/3mrxF938sM
— AI Breakfast (@AiBreakfast) 15 janvier 2023Phenaki, developed by Google Research, compresses the video to a small representation of discrete tokens. This tokenizer uses causal attention in time, which allows it to work with variable-length videos.
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Phenaki joint training on image-text and video-text enables generalization beyond video datasets
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Phenaki demonstrates how joint training on a large corpus of image-text pairs as well as a smaller number of video-text examples can result in generalization beyond what is available in the video datasets. pic.twitter.com/q100I6PYqa
— AI Breakfast (@AiBreakfast) 15 janvier 2023Phenaki demonstrates how joint training on a large corpus of image-text pairs as well as a smaller number of video-text examples can result in generalization beyond what is available in the video datasets.