2026-07-28 Terça

Notícias de cripto - Página 19

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.

Weekly Data Recap: S&P Pantera Index Launches, Robinhood Chain Volume Climbs to Top 4

Weekly Data Recap: S&P Pantera Index Launches, Robinhood Chain Volume Ranks Fourth This week saw a mixed performance for risk assets amidst internal reshuffling. Bitcoin closed slightly down at $64,444, while Ethereum gained 0.6%. A key development was the launch of the S&P Pantera Digital Assets Index (SPPDA), co-created by S&P Dow Jones Indices and Pantera Capital. This 18-token benchmark index, powered by Artemis's revenue and supply data, filters for protocols with actual revenue and weights constituents by market cap. Notably, Bitcoin and XRP were excluded due to the revenue requirement. Meanwhile, Robinhood Chain, an Arbitrum Orbit L2 launched on July 1st, surged to become the fourth-largest chain by DEX volume with $4.7B weekly trading. However, analysis reveals a gap between its intended purpose and current reality. While marketed for tokenizing real-world assets (RWAs) like stocks, the chain is currently dominated by memecoin trading, accounting for ~75% of DEX volume. Robinhood's own stock tokens represent only 4.2% of the chain's $595M TVL, with 70% locked in third-party protocols like Morpho and Ethena. Uniswap commands a near-monopoly (98%) on the DEX layer. The launchpad pons.family captured most activity, generating fees roughly five times the chain's total gas fees. Robinhood currently earns basic transaction fees, while third-party applications capture significant economic value, illustrating a "fat app, skinny chain" dynamic. Other notable developments include Hyperliquid's open interest hitting a record $11.4B, consistent weekly inflows into Ethereum ETFs (~$104M), and the end of a six-week outflow streak for Bitcoin ETFs. Regulatory news included the LSE announcing a 24/5 trading venue and the SEC scheduling a roundtable on 24-hour stock trading, while the GENIUS Act's implementation was delayed to 2027.

marsbitOntem 11:46

Weekly Data Recap: S&P Pantera Index Launches, Robinhood Chain Volume Climbs to Top 4

marsbitOntem 11:46

Institutions and On-Chain Capital Are Bullish on CXMT's Continued Surge, Except for South Koreans

Changxin Technology, China's leading memory chip manufacturer, made its debut on the STAR Market, closing up 465.8% with a market cap of 3.28 trillion yuan. Its record-breaking first day included over 140 billion yuan in turnover. Market opinions on its future trajectory diverge. Nomura issued a "buy" rating with a 116 yuan target (implying ~1239.5% upside), citing rapid growth projections, expansion into HBM, and the "crown jewel" status of its DRAM business. Northeast Securities offered a more conservative 10-15x PE valuation range, implying significant but lower upside. While the stock's surge reflects optimism, analysis suggests Changxin's current capacity remains below giants like Samsung and SK Hynix. U.S. equipment export restrictions may limit near-term expansion, and the company is not yet competitive in the high-margin HBM segment crucial for AI. On-chain data from Hyperliquid showed pre-listing positioning was net long by wallets tagged to the U.S., Hong Kong, and mainland China, while Korean-tagged wallets were heavily net short. Other bullish factors noted include a low initial float (6.63%), the ongoing memory "super cycle," and the stock's unique status as a domestic industry leader. Founder Zhu Yiming's plan to distribute 40% of his increased wealth to employees may also slow share sales. Multiple ETF issuers warned that fund net asset values might deviate from displayed reference values on the first day due to the large gap between Changxin's IPO price and its market price.

Odaily星球日报Ontem 11:42

Institutions and On-Chain Capital Are Bullish on CXMT's Continued Surge, Except for South Koreans

Odaily星球日报Ontem 11:42

Claude Code Slashes 80% of Prompt Tokens, But Opus 5 Just Adds Them Right Back In

Claude Code, the AI coding assistant from Anthropic, recently announced a massive reduction of over 80% in its system prompt content for models like Opus 5 and Fable 5. The goal was to remove verbose, often conflicting, rules (like strict commenting and documentation requirements) and replace them with a simpler directive: write code that matches the style of the surrounding project. This "pruning" aims to make the model more efficient by reducing internal conflict from overlapping instructions, with no measurable performance drop reported. However, a developer's (@chenchengpro) investigation revealed a twist. While the prompt was drastically cut from 15,225 characters in Opus 4.7 to 4,467 in Opus 4.8, it *increased* by approximately 72% to 7,694 characters in Opus 5. This isn't a contradiction. The "over 80% cut" refers to the overall shift from the old, detailed rulebook-style prompts to a new, streamlined system. The 72% increase for Opus 5 represents new, targeted instructions added to manage the model's enhanced capabilities. Opus 5 is more proactive—it likes to report progress, generate longer outputs, use sub-agents, and expand task scope. The added prompt content (roughly 3,755 characters) primarily provides guidelines for "Delivering work" (controlling task scope, progress reporting) and "Corrections" (limiting excessive self-correction). These new rules are necessary to curb potential over-engineering on simple tasks, ensuring efficiency even as the model becomes more independent. In short, the old, restrictive manual was deleted, but new guidelines were written to harness the model's newfound initiative.

marsbitOntem 11:37

Claude Code Slashes 80% of Prompt Tokens, But Opus 5 Just Adds Them Right Back In

marsbitOntem 11:37

One-Third of arXiv 'Contaminated', 65% of CS Papers Smell of AI, Only 0.7% in Math

Approximately one-third of recently posted arXiv papers show signs of significant AI-generated text, according to a new study. An analysis of 12,750 papers from January 2023 to July 2026 across ten disciplines found a sharp increase in AI text markers following ChatGPT's release, with the overall detection rate reaching 32% in the latest quarter and peaking near 39% in early 2026. The rate varies drastically by field. Computer Science papers lead at 65%, followed by Quantitative Biology (56.3%) and Electrical Engineering (51.3%). Mathematics, however, has the lowest detection rate at just 0.7%. The study's authors note this could be due to mathematicians using AI less or because the detector struggles with the high volume of formulas and symbolic notation in math papers, leaving the true cause unclear. The research highlights that the detector identifies a statistical "AI style" in the text rather than proving full AI authorship. It cannot distinguish between light AI-assisted editing and fully AI-generated content. Furthermore, the detector can produce false positives, as some pre-ChatGPT academic writing also exhibits patterns now flagged as "AI-like." The growing use of AI, particularly in highly competitive fields, is creating a cycle where researchers may feel pressured to adopt AI tools to keep pace. The findings raise questions about the changing nature of academic writing and the emergence of a new "AI style" that is increasingly difficult to distinguish from human prose, potentially undermining trust in written text regardless of its true origin.

marsbitOntem 11:35

One-Third of arXiv 'Contaminated', 65% of CS Papers Smell of AI, Only 0.7% in Math

marsbitOntem 11:35

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