Tron TRON Industry Weekly: Bybit's stolen triggers "black swan", full-chain VM protocol attracts capital attention

Reprinted from chaincatcher

02/24/2025·2M

1. Forecast

1. Macro-level summary and future forecast

Last week, the U.S. stock market fluctuated significantly. On February 19, the three major U.S. stock indexes closed slightly higher, and the S&P 500 index continued to hit a record high; but on February 21, the three major U.S. stock indexes collectively fell sharply, with the Nasdaq falling by more than 2%. The market is sensitive to a series of economic data, and investors are cautiously optimistic about the outlook for economic growth and the direction of monetary policy. Over the next period of time, investors need to pay close attention to changes in economic data, policy dynamics and geopolitical factors to make informed investment decisions.

2. Market changes and early warnings in the crypto industry

Last week, Bitcoin price continued to fluctuate narrowly. Some people believe that the Bitcoin price trend has become more complicated and the trading difficulty has been escalated. High-level bulls will no longer catch up, waiting for a fall or a breakthrough. For example, on February 21, the price of Bitcoin was close to the trend line, and the market kept paying attention to whether it could achieve a real market reversal. If there is no positive stimulus this week, the crypto market may face the risk of further correction.

3. Industry and track hot spots

Mango Network, a L1 public chain link to EVM & MoveVM, has obtained US$13.5 million investment from well-known institutions such as AINFRA and KUCOIN; Polychain Capital leads Fluent, a hybrid execution network that links EVM, SVM and WASM chains; Kaito is a cryptocurrency search engine powered by ChatGPT. Aiming to revolutionize crypto research and investment through artificial intelligence, Binance and Coinbase are now online.

2. Market hot tracks and weekly potential projects

1. Potential track performance

1.1. How can Mango Network, a L1 public chain linked to EVM &MoveVM, obtain US$13.5 million in investment from well-known institutions such as AINFRA and KUCOIN

Introduction

Mango Network is a Layer 1 blockchain platform designed to solve challenges in Web3 applications by combining EVM and MoveVM compatibility. It aims to provide developers and users with a secure, modular and high-performance infrastructure.

Mango aims to be the easiest smart contract platform to empower developers to create an excellent user experience in Web3. To welcome the next billion users, Mango provides developers with a variety of tools to take advantage of the power of the Mango blockchain. The Mango Development Kit (SDK) will enable developers to build without boundaries.

Mango satisfies the needs of the application through horizontal scaling. With the improvement of Mango validator processing capabilities, network capacity increases proportionally by adding work nodes, so that gas fees can be kept low even during peak network traffic. This scalability feature is in sharp contrast to the bottleneck design of other blockchains.

Rich on-chain asset support is based on practical new applications and economic models, without relying solely on artificial scarcity. Developers can implement dynamic NFTs, which can upgrade, package and group according to application needs, such as updating avatars and customizable items according to changes in gameplay. This capability enhances the in-game economy because the behavior of NFTs is fully reflected on the chain, making NFTs more valuable and providing a more interactive feedback loop.

Multi-VM Omni-Chain

Mango Network combines OPStack and MoveVM to create a complete on-chain blockchain network that supports cross-chain communication and promotes technological boundaries.

The network adopts a two-layer architecture, Mango Move as the L1 layer to ensure security, and OP-Mango as the L2 layer to increase transaction speed and reduce costs, achieving efficient performance.

Mango Network is flexible in design and supports multi-VM operation, providing developers and users with a wide range of application scenarios and an optimized user experience.

Multi-VM full-chain infrastructure network

Mango Network integrates MoveVM and EVM to create a multi-layer network that supports cross-chain operations, allowing developers to take advantage of the benefits of both virtual machines to provide a wider range of services and application scenarios.

Multi-VM parallelism and cross-chain technology integration Synonymization of parallel execution, cross-chain communication and Layer 2 extension

Multi-VM Parallelism **
**MoveVM optimizes asset management and contract logic, and EVM is combined with OP-Mango to support cross-chain contracts.
Layer 2 Extensions **
**Transactions in Layer 2 are submitted regularly to the main network to ensure security through an assertion mechanism.
Communication between virtual machines **
**Smart contract events are captured and serialized to achieve contract interoperability between EVM and MoveVM.
Cross-chain asset management **
**After the EVM operation, the assets are synchronized to MoveVM through OP-Mango to ensure bidirectional settlement consistency.

MoveVM and EVM cross-chain communication

Mango Network uses OP-Mango Layer 2 network to process transactions synchronously through EVM compatibility and P2P. The sorter sorts transactions and synchronizes the Ethereum state by asserting. Its cross-chain contracts enable interoperability and secure settlement between EVM and MoveVM, optimizing the developer experience.

Comments

Mango modular blockchain can be as sovereign as Layer 1, resistant to hacking and upgradeable. Mango modular blockchain can be applied to new blockchains, simplifying the process of component offloading and reducing deployment time and cost. Mango Public Chain combines zero-knowledge proof technology to allow the disclosure of information knowledge without revealing the information itself. Through the proof of validity, nodes can verify transactions, reduce confirmation time, and improve network throughput. MgoDNS is a distributed domain name solution based on cross-chain protocol, providing domain name and domain name data analysis services. It helps enterprises and individual users manage valuable data on the chain more efficiently, safely and conveniently, and participate in digital asset transactions.

The Mango client uses mechanisms such as resources, distributed locking and sorting to improve system performance and ensure data consistency and parallelism. It enables multifunctional operation based on increased efficiency, security, scalability and quasi-linear capacity.

1.2. Analysis of the Fluent characteristics of link EVM, SVM and WASM chain led by Polychain Capital

Introduction

Fluent is the first hybrid execution network - an Ethereum L2 and framework that combines smart contracts based on Wasm, EVM and (forthcoming) SVM to form a unified execution environment.

Smart contracts for different virtual machine targets can be called directly from each other on Fluent. Fluent is currently in the public development network stage and supports applications composed of Solidity, Vyper and Rust contracts.

Fluent’s unique value proposition lies in its ability to:

Simulate the execution environment (EE) of multiple virtual machines (VMs),
Realize real-time combination of smart contracts related to different virtual machines (such as EVM, SVM, Wasm, etc.),
Support contracts written in various programming languages (such as Solidity, Rust, etc.),
Run in a shared state execution environment.

Fluent supports atomic composition between applications for different virtual machines, as well as "hybrid" applications composed of mixed and matched smart contracts. The interaction between different types of contracts supported by the network occurs in the background, both atomic and real-time.

How does Fluent support hybrid execution?

On Fluent, the functions of EVM, SVM, and Wasm are "fused" together at the execution layer. This is implemented through rWasm - a low-level intermediate representation (IR) that acts as a virtual machine for Fluent. rWasm is actually a state verification function that represents every operation in the Fluent execution layer. Fluent simulates the behavior of EVM, SVM, and Wasm, which are compiled into rWasm for execution. This ensures compatibility and smooth interaction between these different systems and is optimal from the zk proof point of view, since only one state transition is ultimately proven (as in a multi-VM solution that requires multiple state transitions to be proved differently ). Fluent's hybrid design is also scalable - in the future, more virtual machines can be represented through dedicated AOT/JIT compilers.

Hybrid execution vs multiple virtual machines

MultiVM is an alternative virtual machine (altVM) that uses multiple independent virtual machines within the same network. Each virtual machine runs independently and is suitable for different programming languages or execution environments. Maintaining independent virtual machines brings complexity, especially in terms of state synchronization and cross-VM interaction. This can lead to fragmentation of the developer and user experience, as interactions between different environments require additional coordination. Blended Execution provides a more integrated approach than multiVM. Hybrid execution is not about maintaining independent virtual machines for interaction, but rather fuses different virtual machines into a unified execution environment. This allows multiple virtual machines to share the same state and perform seamlessly within the same framework. From the perspective of zk proof, this is also optimal, because only one state transition is proved in the end. In fact, the main difference lies in the degree of integration.

What is a hybrid application?

This enables developers to write different parts of the application in the language and execution environment that best suits each component, thereby improving performance, flexibility, and usability.

Comments

Judging from the information currently available, Fluent L2 will support two types of applications: shared and dedicated.

Shared Applications: These smart contract applications share state in Fluent's execution environment. All applications shared on Fluent L2 are written in real time, even between different VM targets and programming languages such as Rust and Solidity.
Dedicated Applications: These applications are customizable, standalone state machines that can be aggregated and verified using Fluent. Developers can customize independent application runtimes, modular layers (such as DA, sequencing), and so on.

1.3. Where is Kaito, which is the leading CEX such as Binance and Coinbase, comes from? Can crypto information retrieval tools make a breakthrough?

Introduction

Kaito is a ChatGPT-powered cryptocurrency search engine designed to innovate crypto research and investment through artificial intelligence. Kaito uses in-house artificial intelligence technology to organize and organize unstructured information in terabytes of crypto, making it easy for investors, researchers, developers and the public to access this information.

Three major products

Portal

This is the ultimate AI-powered Web3 information platform designed to transform unstructured information in terabytes of data into actionable perspectives .

Instant Perspective Search

Search for any token, topic or trend in seconds to get instant opinions through thousands of high-quality Web3 sources.

Sentiment Analysis

With Kaito's AI-driven analysis, you can gain insight into the factors that affect large changes in mood and easily interpret complex emotional data for valuable insights.

Real-time intelligent reminder For any Settings of fully composable real-time intelligent reminders such as projects, topics, keywords, events, and mood changes make monitoring unprecedentedly simple.
Customized observation list and dashboard Click all the latest news, governance proposals, discussions, mood changes, upcoming catalysts and events with a customized observation list covering any token, project or topic.
Monitoring and benchmark project awareness Frequently and objectively monitor and benchmark changes in awareness within a market or specific field.
Tracking narrative rotation Systemline Track narrative rotations, understand the momentum of existing narratives, and identify upcoming new narratives in advance.
Catalyst Calendar Real-time tracking exceeds 2000 crypto token events and catalysts. Including product releases, token economics changes, unlocking, TGE, governance voting, etc.
Audio library Access all podcasts and conference minutes, transcribed by Kaito's Web3-optimized speech-to-text model, and provides TLDR summary to easily obtain key information.
The smartest encryption AI assistant The smartest encrypted AI assistant with the most comprehensive real-time information, improving your work efficiency several times.

API

Kaito's API gives you systematic access to our unique internal datasets, helping you make smarter decisions in Web3.

Kaito's API services are aimed at funds, project teams, research institutions, exchanges, and more, providing you with real-time access to the best and most comprehensive knowledge data sets, as well as quantifiable social metrics across our unique databases.

Seamless integration **
**Easily integrate multiple Kaito capabilities for systematic decision-making, monitoring and analysis. Our API ensures that you can get rich information at any time.
Unique metrics and data sources **
**Access unique data sets and keep pace with market dynamics. Our industry-leading methodology, reach and data reliability helps you make informed decisions and stay at the forefront.
Full coverage **
**Covering 2000 tokens and a wide range of Web3 data sources, our API provides unparalleled access, including the latest and historical data, helping you make informed decisions in the evolving Web3 domain.

Yaps

A unique "influencer Internet celebrities" ranking and their related networks. Unlike other platforms that track Internet celebrities' posting consultation, Kaito's Yaps product can add a certain number based on the common functions of this type of platform. The tweet can be a clear path from the initiator to the entire staff process, allowing users to restore the beginning, process and end of an impact tweet.

This function is the first in the industry to accurately capture the views of different Internet celebrities on one thing or market for users in the industry.

Comments

Kaito is a next-generation Web3 information platform that indexes a wide range of Web3 content that is difficult to access through traditional search engines. These include social media, governance forums, research reports, news, podcasts, conference minutes, etc. By leveraging advanced AI technology, Kaito redefines the way users discover and interact with blockchain-related information.

The team is committed to revolutionizing the access methods of Web3 information. Thousands of high-quality Web3 sources are indexed to convert unstructured information in terabytes of data into searchable and actionable perspectives to help make smarter decisions.

2. Detailed explanation of the project that week

2.1. Nvidia supports, explains the AI Gaming project GamerBoom, which is followed by Solana and Web3 portal agreement Mask.

Introduction

GamerBoom is an incentive layer and data mining protocol based on mainstream Web2 games and uses an AI-driven data annotation system. It aims to revolutionize the gaming culture and economy by empowering players to control their digital lives.

Gaming Portal (GamerBoom App) is an application covering Web2 games. It serves as a zero-threshold portal for players in the ecosystem, connecting Web2 gamers with the Web3 universe. The goal is to successfully integrate into the Web3 incentive mechanism while maintaining the immersive experience of Web2 games. With innovative gamified design, Gaming App is committed to increasing player engagement and encouraging them to actively participate in various activities in the ecosystem.

Technical analysis

Ecological Overview

The GamerBoom team is committed to creating more than just a gaming platform; the team is building an open gaming ecosystem that allows players to thrive, innovate, and lead the arrival of a new era of digital gaming. Join the team and jointly pave a future path where games and blockchain technology are closely linked to create a world where every player can invest in their own digital life.

GamerBoom's architecture is carefully designed and includes three core levels:

Data mining layer This The basic layer is a gamified incentive layer built on top of Web2 games and aims to mine data. It provides real-time tracking, reactions and ratings of in-game player behavior. The system implements an AI tag system for handling in-game actions, decision modes and engagement.
Future plans include incentivizing users to share social data related to the game, thereby enriching the dimensions of game data.

Game data layer Here In the first layer, the processed data shared by the player is provided to the tuning node for training of the AI agent. All AI agents will automatically generate a unique binding pool based on the binding curve. Sharers pick high-quality AI agents from the sharing market and recommend them by adding liquidity to their binding pools. Some of the revenue generated by the AI agent will be automatically shared with the sharer. Professional sharers can also use player data and AI agents to develop applications and use cases that are more in line with business needs, thereby improving profitability.

Application layer The application layer is The derivative layer of the game data layer is adapted to various usage scenarios, including the upcoming PVP exchange. It uses multi-dimensional real game data to serve various purposes such as suggesting game developers, training game AI, formulating applications based on game behavior or modifying games, and there are other potential application scenarios.

AI-driven data layer

In GamerBoom's technical solution, it is designed to utilize a combination of lightweight local models with cloud-based GPT (generated pretrained transformer) models to facilitate efficient and accurate image recognition tasks in gaming environments. This hybrid approach enables GamerBoom to balance speed, cost, and complexity, ensuring optimal performance while effectively managing resource utilization.

AI system architecture **
**Local Model Architecture Our local model architecture consists of a set of lightweight models that are directly deployed in the client’s gaming applications. These models are designed to perform fast and simple image recognition tasks, providing fast response without significant computational burden.

Hybrid Model Integration Our hybrid model integration strategy combines the advantages of local models with the powerful capabilities of GPT in handling complex image recognition tasks. This approach involves seamless communication between client-native models and cloud-based GPT models, ensuring full coverage and accuracy. The integration process includes the following steps:

Local model call : The local model will continuously analyze the game screen at regular intervals (usually 100 milliseconds) and capture relevant frames.
Simple task solution : Local models quickly process simple image recognition tasks, providing instant response, suitable for direct tasks that do not require a large number of computing resources.
Complex task recognition : For tasks beyond the capabilities of the local model, such as identifying complex game elements or scenarios, the client application forwards relevant frames to the cloud-based GPT model for further analysis.
AI Processing : AI models use advanced deep learning techniques, including image recognition and OCR, to accurately interpret forwarded frames and generate appropriate responses.
Response Integration : After receiving a response from the GPT model, the client application seamlessly integrates the results into the ongoing gaming experience, providing relevant insights or actions based on processed information.

Our hybrid technology solutions offer several advantages and things to note:

Advantages :

Speed and efficiency : The use of local models ensures rapid response to simple tasks, reduces latency, and thus improves the overall user experience.
Cost Optimization : By handing over conventional tasks to lightweight local models for processing, we only turn to cloud GPT models when facing complex scenarios, and we optimize computing costs while maintaining high accuracy.
Scalability : The modular architecture is easy to scale, allowing you to easily add new models or enhance existing models to suit the evolving gaming environment.
Accuracy and flexibility : The combination of local models and GPT ensures the accuracy and flexibility of image recognition in a diverse gaming environment, ensuring strong performance in different scenarios.

AI Agents as Assets
AI Agents as Assets (AIaaA) represent a paradigm shift in how artificial intelligence is applied and utilized in various fields. With the integration of advanced data mining technology and game data layer, AI agents are at the forefront of innovation, providing numerous potential applications and providing promising directions for future development. An Initial Agent Issuance (IAO) platform will be launched to accelerate the popularity of AI agents in the market.

Agent Creator Agent Creation The user uses processed game data to train AI agents to serve different applications and purposes, rather than just direct transactions and monetization of game data.

Once the training is completed, these AI agents will directly serve enterprises and individual users. These services include, but are not limited to, API data flow mode or chat conversation mode. Agent creators challenge and compete with each other to improve the performance and service of AI agents.

Potential applications of AI agents
Personalized gaming experience : AI agents can analyze large amounts of game data collected from players and create highly personalized gaming experiences. From dynamically adjusting the difficulty level to providing customized in-game content recommendations, AI agents have improved player engagement and satisfaction.

Predictive analysis in the game : By leveraging machine learning algorithms, AI agents can predict player behaviors and preferences, promoting targeted marketing strategies and content development. This predictive capability allows game developers to predict trends and adjust products in real time to maximize revenue potential.

Virtual Partners for Gamers : AI agents can act as virtual assistants for gamers, providing real-time guidance, tips and strategies tailored to suit individual play styles and skill levels. Whether it’s assisting puzzle solving or providing tactical advice in multiplayer battles, AI assistants can enhance the gaming experience.

Anti-cheating mechanism : AI agents play a vital role in detecting and preventing game cheating. By analyzing game modes and identifying exceptions, these agents help maintain fair competition and maintain integrity in the online gaming environment.

Content Supervision and Security : AI agents with natural language processing capabilities can monitor in-game communications and detect improper or harmful content. By enforcing community guidelines and filtering for toxic behavior, these agents help create a safer and more inclusive gaming environment.

Future development potential **
**Cross-industry integration : In addition to gaming, AI agents have the potential to innovate multiple industries, including education, healthcare and finance. By adjusting their capabilities to suit different areas, these agents can promote personalized learning experiences, assist in medical diagnosis, and optimize financial decision-making processes.

Enhanced human-machine collaboration : With the continuous advancement of AI technology, AI agents will become more adept at collaborating with human users. Through natural language interfaces and intuitive interactions, these agents will be seamlessly integrated into daily tasks, enhancing human capabilities and productivity.

Ethical and Responsible AI : As AI agents grow autonomy and influence, they must follow ethical principles and guidelines to ensure responsible behavior. Future developments will focus on achieving transparent and accountable AI systems, prioritizing user privacy, equity and social well-being.

Continuous innovation in AI algorithms : The evolution of AI agents depends on the continuous advancement of machine learning algorithms, including deep learning, reinforcement learning and evolutionary computing. By pushing the boundaries of AI research, developers can unlock new capabilities and expand potential applications of AI agents.

In short, AI Agent as a Service (AIaaS) represents a breakthrough approach, leveraging the power of artificial intelligence to expand beyond the gaming space, but also to other industries. With its diverse applications and unlimited innovation potential, AIaaS heralds a future where smart agents will play a central role in shaping our digital experiences and transforming all walks of life.

Open sharing network
GamerBoom also provides a decentralized curation network for user-generated AI agents within the ecosystem, which consists of a local curation market, an application launch platform and governance modules. A liquidity-based curatorial network is an important part of the GamerBoom ecosystem, providing a reliable and efficient value exchange mechanism and laying a solid foundation for future development.

For each AI agent, a binding curve-based binding pool will be created for liquidity-driven curation and promotion. Curators can add liquidity ($BOOM) to better promotions and earn profit share by holding share tokens.
Throughout the network, all AI agents will be prioritized and recommended based on their liquidity rankings.

Liquidity participants in the bound pool (BLP token holders) also act as liquidity-based retail curators, substantially amplifying the influence of their associated assets. Professional curators also monetize using use cases and applications based on AI agents and player data.

This additional layer of liquidity enables intangible assets (data sets) to create unique binding pools that earn transaction fee sharing and network incentives by monetizing and tokenizing their influence and intrinsic value.

Our innovative dynamic binding curve provides an open, transparent and efficient on-chain data curation mechanism that automatically distributes revenue to data miners, tuning nodes, data curators and data consumers. This approach makes the market more efficient and transparent, and the price of tokens is determined by the collective behavior of network participants.

Initial binding curve

In the GamerBoom ecosystem, we set the initial value of the reserve ratio K to 1/3, and the value of m is determined when creating a binding pool for a specific asset. Through these settings, we can deduce the price function of the BLP token (sharing token for binding pools) minted or destroyed in the asset binding pool, as shown below:

Price formula: **
**
Reserve formula:

Dynamic binding curve

GamerBoom uses dynamic binding curves to coordinate the interests of data miners, data curators and data consumers. If the dataset generates revenue throughout the ecosystem, some of the revenue will be automatically added to the reserves of the binding pool.

Assuming that the reserve ratio K will increase from K0 to K0+ΔK from R0, then:

If the user sells BLP tokens with a total amount of N, causing the total supply to be reduced from S0 to S0−N, the total amount of parent currency A paid is:

Based on the above formula, we get:

When the reserve is added somewhere in the binding curve, the reserve ratio K will increase (always not exceed 1). For users who already hold N NLP tokens, this means they will sell more reserve tokens than before they are added.

Summarize

The advantages of GamerBoom include that by using UI/UX designs with common launchers like Steam, Epic Games, and Wegame, we allow users to keep their habits without having to adapt to new workflows. Augmenting popular Web2 games with interesting and beneficial overlays through an artificial intelligence-driven data tagging system, smoothly aggregating game data. Introduce a binding curve to build a sustainable, decentralized AI-agent-driven gaming economy for billions of players around the world.

Challenges include the need to balance on-premises computing resources with cloud processing requirements. The need for careful resource management to avoid performance degradation or excessive costs. Optimizing integration between local models and GPT, minimizing latency and ensuring accurate results are critical to maintaining real-time gaming experience. When processing sensitive game data (such as screen capture), strong privacy and security measures are required to protect user information and prevent unauthorized access or abuse. Regular maintenance and updates of on-premises and cloud models are necessary to ensure that they are consistent with evolving gaming environments and technological advancements.

3. Industry data analysis

1. Overall market performance

1.1 Spot BTC &ETH ETF

1.2. Spot BTC vs ETH Price Trend

BTC

Analysis

Last week, BTC rebounded at the bottom of the $100,000 resistance range as expected. This week's price trend is likely to continue to test the first-line resistance around $98,000, but if there is no obvious amplification of trading volume, the possibility of $95,000 downward is tested. Unlimited rise, falling below $94,000 may directly pay attention to the bottom support mark of $90,000. If it stabilizes within the $94,000 area, it may continue to consolidate around the $94,000 range, remind users to move less and watch more, continue to hold spot goods, and reduce opening and contracts. trading model.

ETH

Analysis

ETH continued to fluctuate along the Fibonacci pullback line last week, so the trend is easier to judge. If the rebound reaches a stagflation pattern near US$2900, it means that the small-scale rebound ends, the downward trend continues, and the support can continue. Pay attention to the near $2,600. It is highly likely to be determined that if the fundamentals do not fluctuate too much, the probability of continuing to fluctuate in the above range this week is relatively high. Before falling below $2,520, it is not advisable to be bearish for a long time.

1.3. Panic & Greed Index

The cryptocurrency fear and greed index fell from 47 to 38 between February 17 and February 23, 2025, indicating that market sentiment has changed from neutral to fear. This shows that investors have become more cautious during this period. Factors that may cause this change include:

Market volatility : Increased price volatility may lead to an increase in investor uncertainty, thus turning market sentiment into fear.
Market Adjustment : The decline in cryptocurrency prices may cause investors to worry about the future direction of the market, which in turn will trigger fear.
Negative news : security breaches, hacking of exchanges (Bybit currency theft incident) or other adverse events may weaken investor confidence.

2. Public chain data

2.1. BTC Layer 2 Summary

Analysis

Between February 17 and February 23, 2025, there have been several important advances in the field of Bitcoin Layer 2, highlighting the increasing focus on improving Bitcoin’s scalability and efficiency.

Main progress:

Nic Carter discusses Bitcoin Rollups with David Seroy: On February 17, 2025, Nic Carter held a discussion with David Seroy of Strata/Alpen about Bitcoin Rollups and the upcoming "Bitcoin Level 2 Season". This conversation highlights the growing concern of the second layer solution aimed at improving the efficiency and scalability of Bitcoin network transactions.
Market reaction: Bitcoin price rose slightly after announcing progress in Bitcoin’s second-tier solution. At 12:00 UTC on February 17, 2025, the price of Bitcoin rose from $65,100 at 9:00 UTC to $65,420. In addition, trading volume increased by 10% within three hours of the announcement to 23.5 million BTC, showing the high attention of traders.
Stacks launches Nakamoto upgrade: Stacks, a leading Bitcoin tier 2 platform, announced the launch of Nakamoto upgrade aimed at improving transaction speed and security. This upgrade is expected to enhance the Bitcoin economy by supporting faster and safer applications and smart contracts.

These advances reflect the growing concern for improving Bitcoin’s scalability and efficiency through second-tier solutions, during which relevant discussions and technological advancements have attracted much attention.

2.2. EVM &non-EVM Layer 1 Summary

Analysis

During the period from February 17 to February 23, 2025, several important advances have occurred in the EVM compatible and non-EVM Layer 1 blockchain:

EVM is compatible with Layer 1 blockchain:

Monad Test Network Launch: Monad, a high-performance EVM compatible with the Layer 1 blockchain, launched the Test Network on February 19. The network aims to achieve speeds of over 10,000 transactions per second through parallel execution, striving to compete with Ethereum and Solana in terms of speed and scalability. Developers can now participate in the testnet using their new browser and wallet and get testnet tokens from the Monad faucet.
Orderly and Monad integration: On February 19, Orderly, a licenseless liquidity layer, integrates its cross-chain liquidity infrastructure with Monad. This move provides the Monad ecosystem, including decentralized exchanges, with deep liquidity across multiple blockchains and enhances users' trading experience.
Sonic Labs Performance Milestones: Sonic Labs, an EVM Layer 1 blockchain, reportedly has processed more than 25 million transactions, attracted 758,000 standalone addresses, and deployed 58,000 smart contracts. The network operates at a rate of 10,000 transactions per second, at low cost and the ecosystem is growing rapidly.

Non-EVM Layer 1 Blockchain:

Aptos and Aave integration proposal: The Aptos Foundation proposes integrating Aave protocol v3 into its mainnet, which is the first time that the Aave liquidity protocol has been deployed on a non-EVM blockchain. The proposal seeks community feedback to expand Aave's reach beyond EVM-compatible networks.
Entangle 's Solana Integration: Entangle extends its cross-chain support by integrating Solana into its Photon messaging protocol. This integration enables trustless cross-chain messaging between EVM and non-EVM Layer 1 networks such as Solana, facilitating secure interactions between different blockchain ecosystems.

2.3. EVM Layer 2 Summary

Analysis

Between February 17 and February 23, 2025, several important advances have taken place in the second layer of the Ethereum Virtual Machine (EVM) ecosystem:

Berachain main network is online in Bitget wallet, providing airdrop rewards

On February 7, 2025, the Berachain main network was launched on Bitget Wallet, and users can receive additional rewards through BERA airdrops.

Ramp Network launches direct withdrawal function of Ethereum Layer 2 through MetaMask

2025年1月22日，Ramp Network宣布，用户现在可以通过MetaMask直接从以太坊Layer-2网络出售加密货币。

SOON通过NFT销售为SVM驱动的以太坊Layer 2筹集2,200万美元

2025年1月，Solana Optimistic Network（SOON）通过NFT销售，为其基于Solana虚拟机（SVM）的以太坊Layer-2网络筹集了2,200万美元。

四.宏观数据回顾与下周关键数据发布节点

密歇根大学公布的消费者信心指数从1月的71.7大幅下降至2月的64.7，创下2024年8月以来的最低水平。消费者对未来经济状况的信心明显减弱。

上周发布的美联储最新会议纪要显示，官员们认为通胀率仍略高于目标，经济前景存在不确定性，但就业和通胀目标的风险大致平衡。市场普遍关注本周即将公布的核心PCE数据，以进一步判断美联储的货币政策方向。

本周（2月24日-2月28日）重要宏观数据节点包括：

2月26日：美国至2月21日当周EIA原油库存

2月27日：美国至2月22日当周初请失业金人数

2月28日：美国1月核心PCE物价指数年率

五. 监管政策

周内加密行业大事件不断，包括阿根廷总统米莱试图澄清与LIBRA的关系、Bybit被黑客盗走约15亿美元加密货币等等，都显示出了加密行业与监管部门探索适当监管方式的迫切性与必要性。在美国放松监管高压后，香港适时推出了监管路线图，意图十分明显，即建立一个友好的加密中心，但后续如何推进还尚待观察。

USA

美国证券交易委员会（SEC）宣布成立网络和新兴技术部门CETU，以保护散户投资者。Laura D'Allaird 被任命为新部门的负责人，CETU 取代加密资产和网络部门，由来自多个SEC 办公室的大约30 名欺诈专家和律师组成。这个新部门将补充由Hester Peirce 专员领导的加密工作组的工作。重要的是，新部门还将允许SEC 明智地部署执法资源。CETU 将负责打击涉及区块链技术和加密资产的欺诈，与网络安全相关的公共发行人欺诈性披露等不当行为。

Nigeria

据路透社报道，法庭文件显示，尼日利亚已提起诉讼，要求强制币安支付795 亿美元，以弥补其在该国的业务所造成的经济损失，并补缴20 亿美元税款。此前，币安曾表示其正在与尼日利亚联邦内陆税收局合作，以解决潜在的历史税负问题。

India

据CoinDesk 报道，印度执法局（ED）透露，印度在BitConnect 欺诈案件调查中查封了约1.9 亿美元的加密货币、现金和一辆雷克萨斯汽车。BitConnect 创始人Satish Kumbhani 自2023 年起在印度和美国均被通缉。

Hong Kong, China

2 月19 日，香港证监会（SFC）发布了新的虚拟资产监管路线图，即「ASPI-Re」路线图，旨在加强香港虚拟资产市场的安全性、创新和增长。该路线图有五大支柱，分别为：准入（Access）、保障（Safeguards）、产品（Products）、基础设施（Infrastructure）和关系（Relationships）。

Tron TRON Industry Weekly: Bybit&#39;s stolen triggers &quot;black swan&quot;, full-chain VM protocol attracts capital attention

1. Forecast

2. Market hot tracks and weekly potential projects

3. Industry data analysis

四.宏观数据回顾与下周关键数据发布节点

五. 监管政策

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Tron TRON Industry Weekly: Bybit's stolen triggers "black swan", full-chain VM protocol attracts capital attention