HierVL is a novel hierarchical video-language embedding that simultaneously accounts for both long-term and short-term associations. Paper https://
bit.ly/3qSmEk6 7/7
RESEARCH
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HierVL: Hierarchical Video-Language Embedding for Temporal Associations
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Galactic: Fast RL Framework for Robotic Mobile Manipulation
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🚀 Galactic is a large-scale simulation and RL framework for robotic mobile manipulation in indoor environments that achieves an incredible 54x speed increase over Habitat 2.0 on an 8-GPU node.
— AI at Meta (@AIatMeta) 20 juin 2023
Paper ➡️ https://t.co/2z7JrmdyHK
5/7 pic.twitter.com/hIXjWa9l3kGalactic is a large-scale simulation and RL framework for robotic mobile manipulation in indoor environments that achieves an incredible 54x speed increase over Habitat 2.0 on an 8-GPU node. Paper https://
bit.ly/42UkNbI 5/7 -
Learning Video Representations from Large Language Models
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📺 Learning Video Representations from Large Language Models
— AI at Meta (@AIatMeta) 20 juin 2023
This work repurposed pre-trained LLMs to be conditioned on visual input, and finetune them to create automatic video narrators.
Paper ➡️ https://t.co/OsZt3AnAEM
3/7 pic.twitter.com/DLunz5bcgPLearning Representations from Large Language Models This work repurposed pre-trained LLMs to be conditioned on visual input, and finetune them to create automatic video narrators. Paper https://
bit.ly/3NDCWpR 3/7 -
Meta AI Interesting Papers CVPR 2023 Conference
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#CVPR2023 — Here are Interesting new papers you should know about from Meta AI — and how you can access them if you’re not at the conference.
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EgoTask Translation: Multi-Task Model Output Integration
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EgoTask Translation (EgoT2) takes a collection of models optimized on separate tasks and learns to translate their outputs for improved performance on any or all of them at once. Paper https://
bit.ly/3PmIJBr 2/7 -
Attention Economy: The Most Wasted Resource in Digital Age
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In the age of attention economy, attention is the most wasted resource.
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Google Showcases AI Research Projects at CVPR2023 Conference
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Attending #CVPR2023 this year? Stop by the Google booth where you can chat with researchers, attend a demo or Q&A session, and learn about some of the many projects our researchers are presenting throughout the conference. https://
goo.gle/3CCxbSU -
ANITI publishes a position paper on generative AI systems
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@ANITI_Toulouse publishes a position paper on generative AI systems https://actuia.com/actualite/aniti-publie-un-position-paper-sur-les-systemes-dia-generative/
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Team Adds Encodec Model in Record Time
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Massive kudos to @mhollemans
, @art_zucker and patrickvonplaten for sprinting and adding this model in record time Special thanks to @honualx for all his help and support! ref: https://
github.com/facebookresear
ch/encodec
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EnCodec Model Now Available in Transformers Library
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Want to train your own Bark/MusicGen-like TTS/TTA models? 👀
— Vaibhav (VB) Srivastav (@reach_vb) 20 juin 2023
The SoTA Encodec model by @MetaAI has now landed in 🤗Transformers!
It supports compression up to 1.5KHz and produces discrete audio representations. ⚡️
Model: https://t.co/Hq8rDHBfjw
Colab: https://t.co/MaWVEAMCXs pic.twitter.com/tDpPAdlYHUWant to train your own Bark/MusicGen-like TTS/TTA models? The SoTA Encodec model by @MetaAI has now landed in Transformers! It supports compression up to 1.5KHz and produces discrete audio representations. Model: https://
huggingface.co/docs/transform
ers/main/en/model_doc/encodec#overview
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Colab: https://
github.com/Vaibhavs10/not
ebooks/blob/main/use_encodec_w_transformers.ipynb
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