Release Date: February 28, 2025
Author: BlockBeats Editorial Department

In the past 24 hours, the cryptocurrency market has witnessed a multifaceted dynamic from macroeconomic discussions to the development of specific ecosystems. Mainstream topics focused on the controversy surrounding AI and national security boundaries, the bubble discussions triggered by OpenAI's massive funding, and the potential impact of AI tools on the structure of technology employment. In terms of ecosystem development, the Ethereum roadmap timeline has attracted community attention, progress has been made in the integration of Solana with traditional banking systems, experiments with AI Agent applications in the Base ecosystem are heating up, while discussions on market predictions and structural issues in DeFi have once again become focal points in the industry.

1. Mainstream Topics

1. Anthropic Rejects Pentagon Request, Trump Orders Ban

The controversy surrounding the military use of AI rapidly escalated in the past 24 hours. The Pentagon requested that Anthropic remove security restrictions related to "autonomous lethal weapons" and "mass surveillance" from its model, setting a deadline of 5:01 PM Friday. Anthropic rejected this request, stating that without a written commitment ensuring the model would not be used for such purposes, the company could not continue cooperation. Subsequently, Trump ordered all federal agencies to immediately cease using Anthropic products and terminate approximately $200 million in government contracts.

This decision quickly triggered a chain reaction in the tech industry. OpenAI CEO Sam Altman publicly expressed support for Anthropic's safety stance on social media, stating that they "always put safety first." Some tech practitioners also co-signed an open letter expressing support. Meanwhile, Anthropic released a new product update on the same day, but external discussions once again questioned the potential issues with its model in the chemical weapons risk assessment report.

However, community discussions quickly divided into a debate of "ethics vs. national security." Some argued that Anthropic's decision marked a line drawn for AI ethics, emphasizing that AI should not be used for mass surveillance or autonomous weapons systems, claiming it was "the first time an AI company sacrificed hundreds of millions in contracts for safety principles"; others contended that, in the context of global AI military competition, a refusal by American companies to participate in defense technology development could weaken national security. A policy commentator stated, "If the U.S. does not develop these technologies, China and Russia will." Some comments even questioned whether Anthropic's actions were merely a "moral stance" rather than a genuine principle.

From a broader perspective, this event reflects an increasingly evident trend: as AI technology enters the military and national security domains, the power boundaries between tech companies and governments are rapidly becoming blurred.

2. OpenAI Completes Largest Private Funding Round: $110 Billion

OpenAI recently announced the completion of a new round of private funding totaling $110 billion, making it one of the largest private funding rounds in history. Investors include NVIDIA, Amazon, and SoftBank, with NVIDIA investing approximately $30 billion, and Amazon's investment potentially reaching a maximum of $50 billion. Over the past four months, OpenAI's total funding has exceeded $40 billion, and the company stated that the funds would primarily be used to expand AI infrastructure and computational capacity.

However, this scale of funding quickly sparked controversy in the market. OpenAI's revenue for 2025 is estimated at approximately $13 billion, but expected cumulative losses over the next few years could exceed $115 billion. Some commentators believe this is a typical "overvalued tech race," even labeling it as "the largest loss financing in history." A market commentator with decades of experience on Wall Street wrote on social media: "In my 45-year Wall Street career, it's the first time I've seen three of the smartest investors come together to pour $110 billion into a loss-making company."

Meanwhile, some users expressed dissatisfaction with OpenAI's removal of the GPT-4o model, accusing the company of increasingly prioritizing government and large corporate clients while neglecting the needs of ordinary users. A developer commented, "OpenAI used to say it wanted AI to benefit everyone, but now it is increasingly prioritizing government and corporate contracts."

Around this funding event, the community has formed clear divisions. Supporters argue that the research and development of large models are essentially infrastructure construction, necessitating huge capital investments, and that the current funding level reflects investor bets on the long-term potential of AGI. They view the competition for large models as essentially a long-term war of computing power and capital, where short-term profitability is not the most critical issue; critics, however, contend that the AI industry is gradually forming a capital frenzy similar to the dot-com bubble era, with corporate valuations significantly outpacing commercialization capabilities.

The debate ultimately centered on a core question: whether the current capital frenzy in the AI industry is a necessary investment in infrastructure or the start of a new wave of technological bubble. More broadly, this funding event reflects that the AI industry is entering a stage of "capital-driven technological competition," with the mismatch risk between massive financing and actual profitability also rising.

3. Block Layoff Rate Rises to 70%, AI Tools Spark Employment Debate for Engineers

Jack Dorsey's fintech company Block announced a layoff of about 40%, affecting approximately 4,000 employees. Further disclosures revealed that the layoff ratio in the company's engineering team reached as high as 70%. Dorsey stated in the earnings call that since September of last year, the average code output per engineer has increased by about 40%, primarily due to the application of AI tools.

This news quickly sparked discussions about the impact of AI on tech employment. Some commentators believe that this layoff event proves that AI tools are significantly improving development efficiency, consequently reducing the demand for engineers, marking an early sign of AI reshaping the employment structure. A business commentator sarcastically noted, "Those who were saying 'white-collar job loss is alarmist' just three days ago are now suddenly silent after hearing the Block news."

Others argue that Block's layoffs are more of a normal adjustment following overhiring during the pandemic, as the company's staff size had rapidly ballooned from about 3,800 to over 10,000, and the current layoffs are merely a return to a more reasonable organizational scale. An investor commented, "This isn't AI replacing engineers; it's the bubble burst from hiring during the pandemic."

Although the reasons remain contentious, the market reacted relatively positively, with Block's stock price increasing by about 24% after the news broke. From a broader industry perspective, this event reignites discussions about the changes in labor structure in the AI era: as AI tools significantly enhance productivity, software engineering positions may experience obvious differentiation, with high-end system design and AI building capabilities becoming scarcer, while repetitive development work may gradually be replaced by automated tools.

4. Cryptocurrency ETF Race Accelerates: XRP ETF Application Emerges

The competition for cryptocurrency ETFs is further expanding. Bitwise has officially submitted an application for a spot XRP ETF, becoming another mainstream cryptocurrency likely to enter the ETF market following Bitcoin and Ethereum. At the same time, a large institution managing approximately $7 trillion in assets and serving over 18 million clients is advancing the registration of Bitcoin and Ethereum ETFs, described by some analysts as a potential "traditional funds entry point."

The community has shown mixed reactions. Some market participants believe that ETFs will become an important channel for institutional funds to enter the crypto market, especially as the traditional financial advisory system may bring a substantial amount of long-term capital. An ETF analyst pointed out that these institutions have over 16,000 investment advisers, "equivalent to a huge Boomer capital network."

Others exercise caution, arguing that ETFs will not immediately change market structure, as the overall scale of the crypto market is still limited, and institutional participation may exacerbate market centralization. A trader commented, "If this is such a major advantage, why is the market's total market capitalization still at $1.3 trillion?"

In the long term, the push for cryptocurrency ETFs reflects that the integration of digital assets with traditional financial systems is accelerating, but this process also brings new structural contradictions: the tension between decentralization ideals and institutional financial infrastructure persists, and the lagging regulatory framework may amplify market volatility and risks.

5. Paradigm Raises $1.5 Billion New Fund, Bets on AI and Robotics

According to media reports, leading crypto venture capital firm Paradigm is planning to raise up to $1.5 billion for a new fund, expanding its investment scope to AI, robotics, and other cutting-edge technology fields. Paradigm has previously invested in well-known projects such as Coinbase, Uniswap, and dYdX, and its co-founder Matt Huang has publicly stated that the AI field has become "too interesting to ignore."

This news has sparked different interpretations within the community. Some believe this represents a natural trend of merging crypto capital with AI technology, foreseeing that the two may form new overlapping ecosystems in terms of computing power, data, and decentralized infrastructure. They view this as an important signal of Paradigm's "entry into the AI and robotics field."

Others argue that this reflects a search for new growth narratives as some crypto capital seeks to respond to the current slowdown in the crypto market. One commentator quipped, "All crypto companies will eventually become real tech companies." Another market observer more directly stated, "First sell tokens for financing, then go do real business."

However, some believe this is merely a natural expansion of venture capital firms. An industry commentator noted, "This is not abandoning crypto; it's a logical next step."

From a larger investment cycle perspective, this event reflects a clear trend: as AI becomes the new technological center, capital is flowing from certain crypto tracks to broader cutting-edge technology fields.

2. Ecosystem Development

[Ethereum Ecosystem]

1. Vitalik Provides Roadmap Timeline, Community Rarely Excited

In a recent core developer discussion, Vitalik Buterin rarely provided specific timelines for the Ethereum expansion roadmap: in 2026, ZK-EVM clients will start participating in network validation (initially accounting for about 5% of network dependency), and in 2027, the participation ratio of ZK-EVM will gradually increase to support higher gas limits, with a long-term goal to transition to a 3-of-5 proof system. Meanwhile, the roadmap also includes a multi-dimensional gas pricing mechanism, PeerDAS blobs (target 8MB/sec), and a long-term verification security model.

As Vitalik seldom gives clear timelines, this statement quickly attracted community attention. An Ethereum commentator noted, "I rarely see Vitalik giving dates; when he does, it usually indicates that the plan is very certain." Overall, community sentiment is notably optimistic, viewing this as a signal that the Ethereum expansion roadmap is entering a more specific phase. However, some discussions also focus on technical risks. Some developers worry that if there's excessive reliance on ZK-EVM clients in the future, a systemic issue could affect block validation stability; others suggest that as the validation threshold rises, the network may gradually concentrate around large nodes.

In the long term, this event reflects that the Ethereum expansion path increasingly relies on the ZK technology system, and the balance between its security and decentralization will remain one of the most critical technical variables in the coming years.

2. Why is Morpho Performing Better than AAVE in the Bear Market?

In the current market environment, the DeFi lending protocol Morpho's performance has significantly surpassed AAVE. Data shows that Morpho has only dropped about 39% from its cycle peak, with a year-to-date increase of approximately 155%, outperforming most DeFi assets.

A DeFi researcher believes this is related to Morpho's governance structure. He pointed out, "Morpho has no governance infighting between Labs, DAOs, and core teams; the structure is very simple." In contrast, AAVE has frequently experienced governance controversies in recent years, raising concerns among investors about long-term decision-making efficiency. However, the community is not entirely in agreement on this conclusion. Some believe Morpho's advantages stem more from its low circulating supply and ecological distribution channel advantages, rather than purely from its governance structure. Others point out that even though AAVE has a complex governance structure, its long-term history and ecosystem scale still hold advantages.

This discussion touches on the core issue of DeFi: how should the protocol find a new balance between decentralized governance and decision-making efficiency.

3. AI Agent Era: API-first Service Providers May Become the Biggest Winners

As AI Agents increasingly become the core form at the application layer, some developers are beginning to rethink the infrastructure landscape. An industry observer likened it to the "transition from the desktop era to the cloud computing era," believing that when AI Agents begin to call developer infrastructure at scale, service providers that support API-first registration, identity management, and payment systems will become the biggest winners.

This viewpoint suggests that the agent economy is essentially a "machine calling machine" system, so many future development tools need to be redesigned around APIs, automated registration, and payment mechanisms rather than traditional human user interfaces.

The community generally agrees with this, but some maintain caution. Some developers point out that current AI Agents are still in the experimental phase, and their capabilities are still significantly distant from a fully automated economic system.

Nonetheless, more discussions have begun to revolve around one question: how will the next generation of developer infrastructure evolve when Agents become significant participants in the internet.

[Solana Ecosystem]

1. SoFi Integrates with Solana, 13.7 Million Users Can Directly Hold SOL

The American licensed bank SoFi has officially supported the storage and retrieval of Solana network assets. Its approximately 13.7 million users can now directly hold and transfer SOL in the banking app, without needing to go through cryptocurrency exchanges like Coinbase or Kraken.

This news is viewed by some market participants as an important signal of deep integration between traditional financial systems and public chain infrastructure. A user reported, "It took only three minutes to open an account, and now I can directly hold SOL in my bank account." However, some discussions have focused on privacy and centralization issues. Some pointed out that purchasing crypto assets through a bank entry means that all transactions must undergo KYC systems, which may undermine the anonymity that crypto originally emphasizes.

In the long term, the direct connection between banking systems and public chain networks may become an important path for pushing crypto assets into the mainstream financial system.

[Base Ecosystem]

1. Base Ecosystem AI Agent Experiments Heat Up

Recently, multiple AI Agent-related experiments have emerged in the Base ecosystem. DX Terminal Pro launched a large-scale Agent trading experiment, with trading volume reaching approximately $4.5 million in the first hour; meanwhile, the new version of Towns App allows AI Agents to directly place bets or open positions in group chats and supports Apple Pay and USDC payments.

This series of product updates is viewed by some developers as an early exploration of "Agent native applications." Some believe that such experiments may provide new scenarios for future automated trading and Agent collaboration. However, others argue that most current Agent applications are still experimental, and actual user needs and sustainable business models still need further verification.

Overall, the Base ecosystem is becoming one of the important experimental fields for the integration of AI Agents and crypto applications.

2. Brian Armstrong: Good Products Will Emerge Only in a Poor Market

In a period of market sentiment downturn, Coinbase CEO Brian Armstrong encouraged developers to continue innovating on social media. He stated, "Don't pay too much attention to prices; historically, the best products and memes are born during the worst market times."

This viewpoint has quickly sparked discussion. Some believe that bear markets indeed provide the best period for tech teams to refine products; others think this statement is more about the experience summary of industry veterans and does not mean all projects can survive a downturn. However, the history of the crypto industry does show that many key products and cultural symbols often emerge during the coldest market times.

[Others]

1. OpenAI Fires Employee for Insider Trading in Prediction Markets

According to media reports, OpenAI recently fired an employee who was accused of using internal company information to trade on prediction market platforms Polymarket and Kalshi. Investigations showed that this employee may have utilized non-public information regarding product release times for betting. The platforms subsequently reported the related situation to regulatory authorities.

This incident sparked discussions about the information asymmetry issues in prediction markets. Some observers believe that when internal information from tech companies can affect prediction market outcomes, the risks of insider trading become more complex. As prediction markets scale, related regulatory issues are also garnering more attention.

2. Hyperliquid Becomes the Only Profitable DAT Project

Data shows that among current Digital Asset Treasury (DAT) projects, only Hyperliquid's related DAT project is profitable, with unrealized earnings of about $356 million. The project holds approximately 17 million HYPE tokens and continuously adjusts asset structures through OTC trading and repurchase mechanisms, while providing a real-time NAV dashboard to enhance transparency.

Some market participants believe this transparent asset structure may serve as a reference model for future DAT projects. However, others point out that the DAT model as a whole is still in its early stages, and its long-term stability still needs to be validated through market cycles.

3. Kalshi CEO Clashes with Senator over War Prediction Markets

Recently, a U.S. Senator referenced a link to an overseas war prediction market on social media, implying that similar markets might appear in compliant platforms within the U.S. Kalshi's CEO publicly responded, stating that regulated prediction markets in the U.S. do not allow the establishment of war-related markets, and that the link comes from an overseas unregulated platform.

This response once again sparked discussions about the regulatory boundaries concerning prediction markets. Some commentators believe the differences between the U.S. regulatory system and overseas markets may cause confusion among users. As prediction markets' influence in financial and political fields expands, related regulatory issues may become more complex.

4. Dragonfly Founder Responds to Company Origin Controversy for the First Time

Dragonfly's founder Feng Bo recently provided a detailed response regarding the company's founding background on social media for the first time. He stated that he originally entered the industry through a fund-of-funds model and decided to transition into a direct investment firm after encountering many crypto projects, ultimately co-founding Dragonfly with Haseeb and others.

This response has also sparked discussions about the roles of VC founders and the distribution of contributions. Some industry insiders believe that such public clarifications help understand the developmental paths of crypto venture capital firms. From an industry perspective, crypto venture capital firms have gradually established a mature investment system from early exploration stages, reflecting the evolution of the entire crypto investment ecosystem.

免责声明：本文章仅代表作者个人观点，不代表本平台的立场和观点。本文章仅供信息分享，不构成对任何人的任何投资建议。用户与作者之间的任何争议，与本平台无关。如网页中刊载的文章或图片涉及侵权，请提供相关的权利证明和身份证明发送邮件到support@aicoin.com，本平台相关工作人员将会进行核查。