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Introducing Meta Perception Encoder: a vision encoder setting new standards in image & video tasks. It excels in zero-shot classification & retrieval, surpassing existing models. Learn more about Meta Perception Encoder, read the research paper, and download the code and dataset

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AI at Meta

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74,689 görüntüleme • 1 yıl önce •via X (Twitter)

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अंग्रेजी साहित्य profil fotoğrafı
अंग्रेजी साहित्य1 yıl önce

Help to excelsheet❓

Rainmaker profil fotoğrafı
Rainmaker1 yıl önce

Decode the labor market! Learn how to track jobless claims using FRED and Python in my latest free Substack post. 📈 A must-read for data enthusiasts & economists. Dive into how data insights can shape your understanding of the economy.

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WhaleX1 yıl önce

"A vision encoder setting new standards in image & video tasks, excelling in zero-shot classification & retrieval."

Guinther Kovalski profil fotoğrafı
Guinther Kovalski1 yıl önce

just impressive how Siglip stills so close with less than 1/6 of the parameters @giffmana

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Zoom1 yıl önce

It’s over bro, rest.

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Thomas | Æ1 yıl önce

Its ability to excel in zero-shot tasks pushes the boundaries of image and video processing. Can’t wait to dive into the research and see how it outperforms current models.

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Reji Modiyil1 yıl önce

@AIatMeta, this could be a game-changer in visual technology. excited to see its impact.

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Jesse Campbell1 yıl önce

Ok...? What is it?

Jack Assery profil fotoğrafı
Jack Assery1 yıl önce

Interesting 👀

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1st Amendment1 yıl önce

42 Homies 😒

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Breck to the Future1 yıl önce

Incredible progress here. Meta Perception Encoder shows what's possible when you unify architecture across image and video tasks. Zero-shot performance is no longer optional... it's the new baseline. Excited to see how this accelerates real-world applications. Always looking to the future!

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Introducing Meta Perception Language Model (PLM): an open & reproducible vision-language model tackling challenging visual tasks. Learn more about how PLM can help the open source community build more capable computer vision systems. Read the research paper, and download the code and dataset:
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Introducing Meta Perception Language Model (PLM): an open & reproducible vision-language model tackling challenging visual tasks. Learn more about how PLM can help the open source community build more capable computer vision systems. Read the research paper, and download the code and dataset:

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🚀 Meta FAIR is releasing several new research artifacts on our road to advanced machine intelligence (AMI). These latest advancements are transforming our understanding of perception. 1️⃣ Meta Perception Encoder: A large-scale vision encoder that excels across several image & video tasks. 2️⃣ Meta Perception Language Model: A fully open & reproducible vision-language model designed to tackle visual recognition tasks. 3️⃣ Meta Locate 3D: An end-to-end model for accurate object localization in 3D environments. 4️⃣ Releasing model weights for our 8B-parameter Dynamic Byte Latent Transformer, an alternative to traditional tokenization methods with the potential to redefine the standards for language model efficiency and reliability. 5️⃣Collaborative Reasoner: A framework for evaluating & improving collaborative reasoning skills in language models. Download the code, datasets, and research papers and learn more about how these artifacts are paving the way for more efficient and accurate AI systems.➡️
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🚀 Meta FAIR is releasing several new research artifacts on our road to advanced machine intelligence (AMI). These latest advancements are transforming our understanding of perception. 1️⃣ Meta Perception Encoder: A large-scale vision encoder that excels across several image & video tasks. 2️⃣ Meta Perception Language Model: A fully open & reproducible vision-language model designed to tackle visual recognition tasks. 3️⃣ Meta Locate 3D: An end-to-end model for accurate object localization in 3D environments. 4️⃣ Releasing model weights for our 8B-parameter Dynamic Byte Latent Transformer, an alternative to traditional tokenization methods with the potential to redefine the standards for language model efficiency and reliability. 5️⃣Collaborative Reasoner: A framework for evaluating & improving collaborative reasoning skills in language models. Download the code, datasets, and research papers and learn more about how these artifacts are paving the way for more efficient and accurate AI systems.➡️

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Introducing Long Zhao, a Senior Research Scientist at Google, who worked to build VideoPrism: A Foundational Visual Encoder for Video Understanding. Read the blog to explore innovations in video understanding tasks and more →

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Today at Meta FAIR we’re announcing three new cutting-edge developments in robotics and touch perception — and releasing a collection of artifacts to empower the community to build on this work. Details on all of this new work ➡️ 1️⃣ Meta Sparsh is the first general-purpose encoder for vision-based tactile sensing that works across many tactile sensors and many tasks. Trained on 460K+ tactile images using self-supervised learning. 2️⃣ Meta Digit 360 is a breakthrough artificial fingertip-based tactile sensor, equipped with 18+ sensing features to deliver detailed touch data with human-level precision and touch-sensing capabilities. 3️⃣ Meta Digit Plexus is a standardized platform for robotic sensor connections and interactions. It provides a hardware-software solution to integrate tactile sensors on a single robot hand and enables seamless data collection, control and analysis over a single cable. The potential impact of expanding capabilities and components like these for the open source community ranges from medical research to supply chain, manufacturing and much more. We’re excited to continue this work with the broader community.

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