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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

74,392 次观看 • 1 年前 •via X (Twitter)

11 条评论

अंग्रेजी साहित्य 的头像
अंग्रेजी साहित्य1 年前

Help to excelsheet❓

Rainmaker 的头像
Rainmaker1 年前

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.

WhaleX 的头像
WhaleX1 年前

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

Guinther Kovalski 的头像
Guinther Kovalski1 年前

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

Zoom 的头像
Zoom1 年前

It’s over bro, rest.

Thomas | Æ 的头像
Thomas | Æ1 年前

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.

Reji Modiyil 的头像
Reji Modiyil1 年前

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

Jesse Campbell 的头像
Jesse Campbell1 年前

Ok...? What is it?

Jack Assery 的头像
Jack Assery1 年前

Interesting 👀

1st Amendment 的头像
1st Amendment1 年前

42 Homies 😒

Breck to the Future 的头像
Breck to the Future1 年前

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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Open science is how we continue to push technology forward and today at Meta FAIR we’re sharing eight new AI research artifacts including new models, datasets and code to inspire innovation in the community. More in the video from Joelle Pineau. This work is another important step towards our goal of achieving Advanced Machine Intelligence (AMI). What we’re releasing: • Meta Spirit LM: An open source language model for seamless speech and text integration. • Meta Segment Anything Model 2.1: An updated checkpoint with improved results on visually similar objects, small objects and occlusion handling. Plus a new developer suite to make it easier for developers to build with SAM 2. • Layer Skip: Inference code and fine-tuned checkpoints demonstrating a new method for enhancing LLM performance. • SALSA: New code to enable researchers to benchmark AI-based attacks in support of validating security for post-quantum cryptography. • Meta Lingua: A lightweight and self-contained codebase designed to train language models at scale. • Meta Open Materials: New open source models and the largest dataset of its kind to accelerate AI-driven discovery of new inorganic materials. • MEXMA: A new research paper and code for our novel pre-trained cross-lingual sentence encoder with coverage across 80 languages. • Self-Taught Evaluator: a new method for generating synthetic preference data to train reward models without relying on human annotations. Access to state-of-the-art AI creates opportunities for everyone. We’re excited to share this work and look forward to seeing the community innovation that results from it. Details and access to everything released by FAIR today ➡️

AI at Meta

150,222 次观看 • 1 年前