[Ethereum Part]
Increase validator balance limit
Translation: Previously, 32 ETH = 1 validator (a validator is equivalent to a mining machine), now increased to 2048 ETH. In the past, it required queuing to recharge or withdraw ETH from validators.
Benefits: This raises the upper limit, greatly accelerating the queue speed. Moreover, as the nodes become larger, there will be opportunities in the future to push consensus algorithms that allow only large nodes to participate in block creation, thus speeding things up.
Dynamically adjust Blob capacity
Translation: L2 needs to store data on the ETH mainnet for security (similar to reporting to a leader). To avoid occupying space on the ETH mainnet, a separate space was allocated for them, called Blob.
Dynamic adjustment of Blob capacity means enlarging this space during peak times for L2 and reducing it during valleys.
The benefit is: making L2 cheaper and faster.
Blob expansion
Translation: Directly increasing the space for storing data in L2.
Benefit: making L2 cheaper and faster.
[Other Chains Part]
Chain abstraction
Translation: It means abstracting each module, aiming for one-click chain deployment. It's like customizing a sandwich at Subway, where you can freely choose the consensus mechanism (bread), the virtual machine (filling), and the settlement method (sauce).
Benefit: High degree of freedom in one-click chain deployment.
Delta neutral
Translation: This means no profit or loss; for example, you hold 1 BTC in spot and open a 1x BTC short position. The fluctuations of Bitcoin don’t affect you; you are neutral, without direction.
Benefit: Bitcoin short positions can earn fees, equivalent to stablecoin investments.
DeSci
Translation: Decentralized + Science, an acronym for decentralized scientific research, a concept from the meme era.
Benefit: Making scientific fundraising easier, which may help science.
AI agent
Translation: AI refers to systems like ChatGPT, DeepSeek, Grok, etc., which only ask and answer questions; an AI agent enables AI to take action based on these Q&A, also a concept from the meme era.
If an engineering project is named 'AI Agent', it means its problem-solving logic must follow these steps:
1. Perception → 2. Thinking → 3. Action
For example, the most common AI Agent project [automatically investing in cryptocurrencies with AI] works like this:
1. Perception: Read the latest cryptocurrency news
2. Thinking: Determine if the news is favorable or unfavorable for a certain coin
3. Action: Buy if favorable, sell if unfavorable
Benefit: AI actually does real work, rather than just talking.
I hope this helps everyone understand at once.