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Vitalik proposed the "extremely simplified chain" solution, where validators submit STARK proofs daily, and the state storage is compressed to 6 bytes

Ethereum co-founder Vitalik Buterin published the proposal "The Extremely Lean Chain," demonstrating how to radically compress the state requirements of the Ethereum consensus chain in the context of the "Lean" upgrade. This plan shifts responsibility to validators, who manage and periodically prove their state through ZK proofs, thereby eliminating the processing burden for each epoch and potentially supporting millions of validators.The core mechanisms include: removing the validator public keys from the on-chain state, storing only the deposit tree index; canceling real-time reward and penalty processing, with validators generating daily STARK proofs of their participation and updating balances; completely re-randomizing validator identities daily, achieving strong anonymity through ZK-STARK, with withdrawal addresses exposed only at the time of withdrawal and not publicly linked to deposits or on-chain activities. Vitalik stated that based on upgrades such as single-slot finality and quantum-resistant signature aggregation, the state requirement per validator could be compressed from approximately 180 bytes to 6 bytes. The daily proof cost for a single validator requires processing about 5400 Merkle branches, which can be completed within 1 hour on ordinary hardware, and the on-chain burden can be reduced through aggregated proofs. Additionally, this design can achieve a "virtually free" single secret leader election function, with 1 day as the conservative cycle length and 1 hour as the lower limit.

ByteDance releases Doubao 2.1 Pro large model, accelerating AI strategy towards the enterprise sector

According to the "Science and Technology Innovation Board Daily," at the 2026 Volcano Engine Force Conference, ByteDance officially released the latest flagship version 2.1Pro of the Doubao large model. Tan Dai, President of Volcano Engine, stated that the model has made breakthroughs in four dimensions: code delivery, long-range Agent tasks, multimodal understanding, and enterprise-level stable operation, possessing stronger engineering delivery capabilities and being capable of handling complex R&D tasks for enterprises. At the conference, ByteDance CEO Liang Rubo also emphasized that the company will focus on enhancing large model capabilities and firmly invest in MaaS (Model as a Service) business.The report pointed out that ByteDance's AI strategic focus is clearly shifting towards enterprise-level services. Currently, the daily token call volume of the Doubao large model has reached 180 trillion, an increase of over 1500 times since its release, and has grown more than 10 times in the past year. However, due to the bottleneck in monetization on the consumer side and high expenses (with daily computing costs reaching tens of millions and daily revenue below one million), ByteDance has accordingly adjusted its resource allocation. Meanwhile, the video generation model Seedance, primarily aimed at the B-end, has validated its commercialization potential, with current annual recurring revenue (ARR) reaching 2 billion dollars, effectively offsetting Doubao's computing costs. In addition, the new version of Seedance will also be the first in the industry to launch a 3D white membrane preview feature.

ByteDance's AI strategic focus may shift from mass consumer to enterprise services

According to LatePost, ByteDance is adjusting its AI resource allocation strategy, shifting its focus from consumer-facing products like "Doubao" to products that serve enterprise clients. This change is partly influenced by the high operational costs of AI and challenges to existing business models.It is reported that "Doubao" has over 200 million daily active users, but due to the enormous computational costs associated with inference and multimodal capabilities, it incurs daily expenses of tens of millions, while its monetization channels, such as e-commerce, generate less than one million daily. In contrast, ByteDance's video generation model Seedance demonstrates strong profitability. Thanks to its efficient MoE architecture (200 billion parameters) and relatively low reliance on inference computing power, Seedance 2.0 currently has a gross margin of 70%, with the vast majority of its revenue coming from enterprise clients, and its current annual recurring revenue (ARR) has reached 2 billion dollars.Insiders reveal that ByteDance's large model data review team has expanded to over 3,000 people this year, primarily to clean training data for programming models. Meanwhile, the MaaS business of Volcano Engine has also been placed in a more important position, with ByteDance's top management setting a goal to increase revenue tenfold and accelerate international expansion. Additionally, ByteDance executives recently visited Anthropic, which has achieved significant growth in both revenue and valuation through enterprise-level AI programming services, providing a reference for ByteDance's strategic adjustments.
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