Vitalik Buterin endorses TiTok compression method for blockchain applications

Author: Josh O'Sullivan, CoinTelegraph; Compiled by: Whitewater, Golden Finance

Ethereum co-founder Vitalik Buterin has endorsed the new Token for Image Tokenizer (TiTok) compression method for its potential blockchain applications.

Not to be confused with social media platform TikTok, the new TiTok compression method significantly reduces image size, making it more suitable for storage on the blockchain.

Buterin highlighted TiTok’s blockchain potential on the decentralized social media platform Farcaster, saying “320 A bit is basically a hash value small enough for each user to chain. ;">This development could have significant implications for the storage of digital images in Personal Profile Pictures (PFPs) and Non-Fungible Tokens (NFTs).

TiTok image compression

TiTok was jointly developed by ByteDance and researchers from the Technical University of Munich, Images can be compressed into 32 small blocks (bits) without losing quality.

Advanced artificial intelligence (AI) image compression allows TiTok to compress a 256x256 pixel image into "32 discrete markers," according to a TiTok research paper.

TiTok is a one-dimensional (1D) image tokenization framework that "breaks the boundaries of 2D tokenization methods existing grid constraints", resulting in a more flexible and compact image.

"As a result, it can significantly speed up the sampling process (for example, 410 times faster than DiT-XL/2) while achieving competitive generation quality."< / p>

TikTok research paper shows comparison of image compression sizes. Source: TikTok

Machine Learning Image

TikTok uses machine learning and advanced artificial intelligence Smart,convert images into tokenized representations using,transformer-based models.

This method uses area redundancy, which means it identifies and uses redundant information in different areas of the image to reduce the overall data size of the final product.

“Recent advances in generative models highlight the important role of image labeling in efficient synthesis of high-resolution images.”

According to the research paper, TiTok’s “compact latent representation” can generate "More efficient and effective representation than traditional techniques".

Illustration of image reconstruction (a) and generation (b) using TiTok framework (c). Source: TiTok

TikTok, not TikTok

Despite the similar name, the social media platform TikTok is not endorsed by Buterin.

Ethereum co-founder highlights TiTok’s blockchain potential for this new AI-powered The image compression method adds credibility.

" Unlike existing 2D VQ models that treat the image latent space as a 2D grid, we provide a more compact formulation to label images as 1D latent sequence."

The proposed new method can "represent images with 8 to 64 times fewer markers than "2D marker", and the team hopes this research will lead to "more efficient image representation." Provide inspiration.