一项调查报告内容显示 2024 年美国私人投资者的加密投资将会激增

币界网Publicado a 2024-08-07Actualizado a 2024-08-07

币界网报道:

正文:

https://cointelegraph.com/news/us-private-investors-predict-surge-crypto-investments-2024-report

Barnes & Thornburg 律师事务所近期发布了一项调查报告,该调查报告采访了美国各行业的私募股权、风险投资、对冲基金和投资银行公司的 138 名有限合伙人、普通合伙人和服务提供商。有 84% 的受访者认为可能会在未来 12 个月内增加投资加密货币的预算。其中 59% 的人表示他们更倾向于投资加密货币基金产品(加密 ETF )。

该报告的调查结果表明,与去年相比,大多数受访者的态度有了明显转变,当时大多数人认为加密货币市场对其行业或企业产生了严重的负面影响。转向投资加密货币后,投资者对该领域的信心有所改善,这主要是因为机构开始大量投资合规的交易所基金(ETF)和衍生品等加密投资产品。此外,今年一月份,比特币现货 ETF 的首次亮相以及随后的市场复苏,带来了加密货币监管的明确性,并大大增强了投资者的信心。

但也有 26% 的投资者表示他们在未来 12 个月内投资加密货币基金的可能性较小,主要原因是加密货币市场的波动较大。Barnes & Thornburg 私募基金和资产合伙人兼联席主席 Scott Baels 表示:“FTX 交易所崩溃一年半后,我们看到了比特币和其他加密货币的显著复苏。SEC 对比特币现货 ETF 的批准是该行业的重大里程碑,这可能会增加投资私募加密基金和其他非监管产品的投资意愿。”

调查报告显示,投资者也在寻求有着更多流动性和更好收益的产品,受访的有限合伙人最关注的问题是“投资回报”,有 54% 的受访者将其列为首要问题。有 50% 受访者的另一个主要担忧是“融资条款”,这表明筹集资金的条件会更加严格。在普通合伙人中,“融资条款”被认为是最紧迫的问题,有 40% 的人提到这一点,高于去年的 23%。

免责声明:本节提供的信息仅供参考,不代表任何投资建议或FameEX官方观点。

Lecturas Relacionadas

GPT-5.6 Countdown: Abandon the Illusion of a Single API, Computational Iteration Can't Outpace a Single Page of Compliance

In mid-June, three seemingly independent industry events—the compliance-driven throttling of Fable 5, the open-sourcing of GLM-5.2, and the leaked release timeline for GPT-5.6—are pushing the global AI industry toward a watershed moment. These shifts signal a fundamental restructuring of the industry's underlying logic. First, **"usability" has substantially overtaken "advanced capabilities"** as the primary weight, pushing the global large language model (LLM) supply chain into a "dual-track" phase of controlled closed-source and local open-source coexistence. Second, **the competitive moats of closed-source giants are shifting**. Their technical focus is moving from "language intelligence" toward "spatial intelligence (world models)"—a domain heavily reliant on computing power. Third, faced with常态化 transnational compliance risks, **a "model-agnostic" decoupled design has become a survival necessity for application-layer developers to maintain business continuity.** The article details how Anthropic's Fable 5, despite its advanced engineering feats, was restricted for non-U.S. citizens within 72 hours of launch, highlighting how geopolitical compliance can instantly limit even the most advanced models. In response, the open-source camp, exemplified by Zhipu AI's MIT-licensed GLM-5.2, is gaining market share by offering stable performance improvements and significant cost advantages (up to 70% savings for enterprises), while achieving full adaptation with domestic semiconductor platforms. Meanwhile, closed-source leaders like OpenAI are pivoting. The anticipated GPT-5.6 reportedly shifts focus from language to spatial intelligence and world models, aiming to rebuild a generational gap in areas like 3D understanding, simulation, and industrial design that demand immense compute. The core conclusion is that the LLM supply chain's logic has changed. Enterprises must now evaluate infrastructure based on a composite of technical performance and policy compliance. For developers, complete reliance on a single closed-source API poses unacceptable risk. Implementing a truly model-agnostic architecture—enabling swift switches to compliant, locally deployable open-source alternatives—is no longer just good practice but a fundamental baseline for business continuity.

marsbitHace 6 min(s)

GPT-5.6 Countdown: Abandon the Illusion of a Single API, Computational Iteration Can't Outpace a Single Page of Compliance

marsbitHace 6 min(s)

Is the 'Token Subsidy War' Among AI Giants Almost Over?

The article discusses the ongoing "token subsidy war" among AI giants like OpenAI and Anthropic, questioning whether it's nearing its end. It reveals that current AI subscription prices are heavily subsidized, with some plans offering tokens at up to 70 times the actual cost to attract and retain heavy users, especially developers and enterprises. This strategy mirrors past internet-era subsidy battles, but with a key difference: AI tokens lack "lock-in" effects. Unlike ride-hailing or food delivery apps, users can easily switch between AI providers as APIs become standardized, making it difficult for companies to raise prices post-subsidy. The piece highlights a structural asymmetry in the competition. Giants like Google, with massive advertising revenue, can afford to subsidize tokens indefinitely, akin to using "tokens as a weapon." In contrast, venture-backed companies like OpenAI and Anthropic face pressure to become profitable, especially as they approach IPO. The article cites Google Ventures founder Bill Maris, who suggests Google could slash token prices by 80%, putting immense pressure on competitors. Two potential endgames are presented: the "internet service" model (subsidize, monopolize, then raise prices) and the "utility" model (tokens become a standardized, low-margin commodity like electricity). Given the low switching costs, the latter seems more likely. The competition may not have a single winner but could instead accelerate AI's evolution into a foundational, infrastructure-level technology, akin to a public utility. For now, users continue to benefit from heavily subsidized token costs.

marsbitHace 23 min(s)

Is the 'Token Subsidy War' Among AI Giants Almost Over?

marsbitHace 23 min(s)

Beyond the Stadium: The Profitable Games Surrounding the World Cup

"Beyond the Pitch: The Profit Game Around the World Cup" The FIFA World Cup transcends being a sporting spectacle, evolving into a massive global arena for speculation and profit-seeking. The 2026 tournament has amplified this dynamic, creating a multi-layered ecosystem of financial opportunism alongside the football. **Prediction markets** have surged into the mainstream. Platforms like Polymarket and Kalshi saw trading volumes for World Cup contracts soar, attracting new users with their financial trading model and high-profile, chain-based wealth stories that overshadow traditional sports betting in terms of growth and narrative. However, **traditional sportsbooks** remain the dominant force, leveraging established user habits, legal markets, and comprehensive product offerings to handle the vast majority of speculative wagers, with projections suggesting record-breaking betting volumes. Capital markets also react. **"Concept stocks"** in countries like South Korea and Japan experience volatile price swings based on team performance and anticipated fan spending on items like chicken, beer, and viewing parties, effectively becoming a stock market reflecting fan sentiment. The **ticket resale market** has become a sophisticated arena for arbitrage. Prices fluctuate wildly based on team draws and star power, with sellers sometimes listing tickets they don't yet own in a practice akin to short-selling, while FIFA's own "Right to Buy" tokens add another layer of speculative trading. **Collectibles and merchandise** offer another avenue. Panini sticker albums, with their inherent scarcity and nostalgic value, can become high-value collectibles. Limited-edition or locally themed jerseys command significant premiums on secondary markets, and even counterfeit vendors profit from fans' desire for affordable match-day identity. The **cryptocurrency** space has seen a frenzy of speculative, unauthorized World Cup-themed meme coins on chains like Solana. These tokens, often exploiting team names and player imagery, experience extreme pump-and-dump cycles, creating stories of massive gains for a few early entrants and steep losses for many others. Finally, an entire industry thrives on **providing information and tools** to other speculators. Developers create platforms like SeatSidekick to track ticket inventory and prices, while paid Telegram groups and subscriptions sell betting tips and predictions, monetizing the widespread desire for an informational edge. In essence, the World Cup has become a compressed, global laboratory for speculation. While the games determine champions on the field, a parallel, complex network of financial transactions—spanning prediction contracts, bets, stocks, tickets, collectibles, crypto, and information services—settles its own scores in the global market.

marsbitHace 1 hora(s)

Beyond the Stadium: The Profitable Games Surrounding the World Cup

marsbitHace 1 hora(s)

How Does Codex Use a Computer? Three Entry Points and Permission Boundaries

This article explains the three primary methods for Codex to interact with a computer, each with distinct use cases, permission boundaries, and trust levels. **1. Computer Use:** This offers the broadest access, allowing Codex to visually control and interact with the graphical user interface of authorized macOS/Windows apps, system settings, and even iOS simulators. It's ideal for tasks lacking APIs or structured tools, such as operating legacy software or multi-app workflows. However, it's the slowest method and has the widest permission scope, requiring careful supervision for sensitive actions. **2. Chrome Extension:** This grants Codex access to the user's logged-in Chrome browser state, including cookies, profiles, and open tabs. It's best for tasks requiring user identity across websites like Gmail, LinkedIn, Salesforce, or internal dashboards. Its key advantage is multi-tab control for complex workflows. While more powerful for browser-based tasks than Computer Use, it carries higher sensitivity as actions are performed under the user's identity. **3. In-App Browser:** This is a browser isolated within the Codex thread, separate from the user's personal browsing data. It excels in web development and debugging scenarios—previewing local servers, testing responsive layouts, or annotating designs directly on the page. Its isolation is a strength for development but a limitation for tasks requiring login sessions. The core principle is to choose the narrowest, safest, and most structured interface for the task. Use plugins or MCPs first, resort to visual control (Computer Use) only for GUI-dependent tasks, employ the Chrome extension for identity-reliant browser work, and prefer the In-App Browser for isolated development. **Appshots** are clarified as a fourth, complementary tool for *inputting* context—capturing a screenshot of a window to point Codex to something—rather than a method for Codex to *act*. Together, this layered approach highlights a key to AI agent productization: not granting unlimited permissions, but constraining them within clear boundaries for specific tasks while preserving user oversight.

marsbitHace 2 hora(s)

How Does Codex Use a Computer? Three Entry Points and Permission Boundaries

marsbitHace 2 hora(s)

Trading

Spot
Futuros
活动图片