2026-08-11 Terça

Notícias de cripto - Página 493

Mantenha-se a par do mercado de cripto. Notícias em tempo real, análises, preços, histórias em alta e análise de especialistas — tudo num só lugar.

Bankless Co-founder: Why I Sold All My ETH

Author David Hoffman, founder of Bankless, explains his decision to sell all his ETH, despite being a prominent figure in the Ethereum ecosystem. He clarifies that his move is not a bearish take on Ethereum itself, which he remains highly optimistic about as a network. His core argument is that the "ETH is money" thesis, which he helped popularize, has largely played out. Hoffman argues that ETH has achieved the market valuation it deserves based on Ethereum's current success and competitive position. He details several reasons for this view. First, the path for ETH to become global money required nearly flawless execution and sustained dominance across Ethereum's entire technical and social stack—a coordination challenge he now believes had a narrower window for success than anticipated. Second, market data shows a strong correlation between L1 chain activity/fees and the price of its native asset; Ethereum's fee dominance has been challenged by competitors like Solana. Third, the "strong version" of crypto (decentralized, native crypto economies) that ETH's monetary thesis relied upon has struggled to maintain a positive mainstream narrative and stable adoption beyond a brief period. Finally, Ethereum's architecture as a "giver"—providing secure block space and tokenization capabilities at cost to L2s and applications—means it doesn't capture premium value directly. Its rollup-centric roadmap further directs most profits to L2s and applications ("fat app theory"). In conclusion, Hoffman believes the opportunity for ETH to be revalued significantly upward as money has diminished. He sold not because ETH will fail, but because its monetary thesis has matured, and he seeks to allocate capital to other opportunities he finds more compelling.

链捕手05/27 02:11

Bankless Co-founder: Why I Sold All My ETH

链捕手05/27 02:11

From Issuer to Infrastructure Owner: Circle's Arc Strategy and the Fatal Gap in the GENIUS Act

Circle raised $222 million for its proprietary Layer-1 blockchain, Arc, positioning itself not just as a stablecoin issuer but as the owner of the settlement infrastructure USDC relies on. This move, backed by investors like BlackRock and Apollo, highlights a significant structural conflict unaddressed by the GENIUS Act of 2025. While the act focuses on stablecoin reserves and issuer oversight, it remains silent on the market structure implications of an issuer controlling the underlying network—a scenario akin to a currency issuer also owning the payment rails. Traditionally, financial regulations separate issuers from settlement infrastructure to ensure neutrality. With Arc, Circle gains control over transaction ordering, fees, and network rules, potentially favoring USDC over competitors. The article argues that this creates a permanent structural temptation, even if no abuse occurs. The solution lies in applying established market infrastructure principles: mandating neutral transaction ordering, transparent fee schedules, and governance separated from Circle’s commercial interests. The current pre-mainnet phase offers a critical window for regulators to establish these rules before Arc becomes entrenched. Once operational, enforcing changes would be costly and disruptive. The core question remains: should a regulated stablecoin issuer be allowed to own the settlement network its competitors must use? The GENIUS Act doesn’t answer this, but Circle’s Arc strategy makes it urgent.

marsbit05/27 02:05

From Issuer to Infrastructure Owner: Circle's Arc Strategy and the Fatal Gap in the GENIUS Act

marsbit05/27 02:05

What Are the Key Variables Determining the AI Bull Market?

Title: What Determines the AI Bull Market? Key Variables Revealed Despite rising oil prices above $100/barrel, persistent inflation, and fragile Fed rate cut expectations—a traditionally hostile environment for high-valuation tech stocks—the AI sector continues to drive the market to new highs. According to analysts, the current AI boom is in a phase of "rational fervor": while bubbles exist, they are not yet out of control. The crucial shift is the emergence of Agentic AI, which is evolving from an assisting tool (Copilot) to an autonomous execution tool (Autopilot), creating a clearer commercial path from investment to revenue. This shift accelerates Token consumption and inference computing demand while boosting revenue forecasts for leading firms. The market is now rewarding capital expenditure as it transforms from a burden into a competitive moat, supporting hardware chains like GPUs, optical modules, and storage. However, valuations have already priced in growth expectations for 2027-2028. The forward P/E ratio for the "Magnificent Seven" tech giants is about 35x, compared to 25x for the rest of the S&P 500. This premium implies AI adoption must occur 5 to 8 times faster than past technological revolutions—a scenario with little room for error. The sustainability of the AI bull market hinges on three key variables: 1. **Short-term liquidity shocks**: Risks include sustained high oil prices, resurgent inflation, rising interest rates, and potential unwinding of the yen carry trade. The critical question is whether the upward revision speed of Annual Recurring Revenue (ARR) can outpace the rise in interest rates. 2. **Mid-term industry realization**: Can the actual pace of AI adoption and commercialization match the current lofty valuations? Historically, general-purpose technology revolutions follow a non-linear path with periods of acceleration and deceleration. 3. **Long-term structural constraints**: These include energy and power grid limitations, employment displacement and consumer purchasing power, social acceptance and potential backlash, and potential hardware technology breakthroughs that could disrupt current supply chains. While the long-term prospects for AI remain optimistic with potential for significant productivity gains, the stock market's pricing depends not just on the vision but on the actual speed of realization amid these growing constraints. The direction is clear, but the pace of execution will determine whether the bubble remains controlled or spirals out of control.

marsbit05/27 02:05

What Are the Key Variables Determining the AI Bull Market?

marsbit05/27 02:05

The AI Industrial Revolution: Where Are We Now?

This article explores the current stage of the AI industrial revolution, arguing we are still merely attaching new tools to old workflows rather than fundamentally redesigning production. The author compares this to the early Industrial Revolution, where factories simply replaced waterwheels with steam engines without changing their core structure. Similarly, today we embed AI chat windows into existing software but leave organizational processes unchanged. While massive investment floods into AI infrastructure (data centers, chips), akin to railway manias of the past, the real transformation lies in "dismantling the old workshop"—reorganizing companies around AI. Examples include Notion's use of hundreds of AI Agents and Y Combinator's experiments with self-improving AI systems that operate autonomously. The author notes a critical gap: while China has vast AI user growth, few companies have rebuilt core workflows. AI is beginning to impact entry-level jobs, and early adopters are gaining a compounding advantage. The conclusion is that the pivotal moment will not be the invention of better models, but when organizations decide to tear down old structures and rebuild around AI, shifting the bottleneck from human coordination to computing power. The future workplace and job titles are yet to be defined, but the imperative is to move away from legacy processes and position oneself where the new "railway" is being built.

marsbit05/27 01:32

The AI Industrial Revolution: Where Are We Now?

marsbit05/27 01:32

Morning Post | Hyperliquid Launches Off-chain Event Prediction Market Contract; Strategy Completes $1.5 Billion Debt Buyback; Kelp DAO Announces rsETH Fully Restored

Crypto Market Digest (May 27, 2026) Ondo Finance's founder Nathan Allman has passed away, with President Ian De Bode taking over as CEO. In regulatory news, Hong Kong authorities concluded a consultation on virtual asset service provider licensing, aiming to align rules with traditional finance. Kelp DAO announced its rsETH token has fully recovered five weeks after a $293 million hack by Lazarus Group, though the incident caused significant damage to DeFi lending protocols like Aave. Key industry developments include Hyperliquid launching off-chain event prediction market contracts, and the CME introducing futures for Avalanche and Sui. A report highlights the rise of AI Agent payments, with over $73 million settled on-chain in a year, predominantly using USDC. Meanwhile, blockchain detective ZachXBT exposed market manipulation involving several BSC tokens. In investment news, a firm referred to as "Strategy" completed a $1.5 billion debt buyback. Political contributions from the crypto sector for the 2026 U.S. elections have surpassed $500 million, heavily favoring Republican candidates. BitMEX founder Arthur Hayes revealed Zcash is his second-largest holding, citing the growing necessity for monetary privacy. The digest concludes with trending memecoins on Ethereum, Solana, and Base networks, and highlights in-depth articles covering the impending SpaceX IPO, Polymarket's regulatory challenges, and an analysis of the on-chain treasury landscape.

链捕手05/27 01:32

Morning Post | Hyperliquid Launches Off-chain Event Prediction Market Contract; Strategy Completes $1.5 Billion Debt Buyback; Kelp DAO Announces rsETH Fully Restored

链捕手05/27 01:32

Just Now, Chinese AI Enters Top 2 in Global Programming, Only Claude Remains Ahead

**China's AI Ranks Second Globally in Programming, Trailing Only Claude** Today, Alibaba's Qwen3.7-Max achieved a score of 1541 on the Code Arena benchmark, securing fourth place globally and surpassing top models like GPT-5.5 and Gemini 3.5 Flash. Among the top positions, it is now the only non-Claude model, placing second overall after Anthropic's Opus models. Before this official ranking, Qwen3.7-Max had already gained recognition overseas. In practical tests, it outperformed rivals on tasks like creating a self-training Tetris AI and generating complex 3D models, often at a significantly lower cost. Developers praised its ability, especially when integrated with tools like Hermes Agent and OpenCode, to effectively replace models such as GPT-5.5. In a hands-on challenge to create a 3D racing game from a detailed prompt, Qwen3.7-Max delivered a fully playable HTML file in the first attempt, requiring only minor bug fixes. It uniquely included a start menu and sound effects—details missed by other models. While competitors like Gemini 3.5 Flash and Claude Opus 4.6 produced less polished or functional versions, and GPT-5.5 had its own quirks, Qwen3.7-Max stood out for its initial completeness and playability. This performance stems from its design as an "Agent Base Model," built for long-duration, autonomous task execution. Internal tests show it can run continuously for 35 hours, making over 1158 tool calls without context degradation or instruction drift. Key technical advancements include "environment expansion" training, which improves adaptability across different frameworks, and "long-horizon autonomous execution" training, enabling sustained strategic decision-making. By entering the top tier of the programming arena, Qwen3.7-Max demonstrates that Chinese AI models are not just catching up but are becoming defining competitors, challenging the long-standing dominance of Silicon Valley in this field.

marsbit05/27 00:17

Just Now, Chinese AI Enters Top 2 in Global Programming, Only Claude Remains Ahead

marsbit05/27 00:17

活动图片