Лишь 1,43% токенов на Pump.fun достигли успеха за месяц

cryptonews.ruPubblicato 2020-06-20Pubblicato ultima volta 2024-11-20

Исследователи компании СryptoRank поделились статистикой о мем-криптовалютах. Они отметили, что на платформе Pump.fun на базе сети Solana за последние 30 дней было запущено 974 тыс. токенов, но только 1,43% из них достигли минимального уровня капитализации $69 тыс. необходимого для листинга на Raydium. Из почти 1 млн запущенных проектов лишь 13,8 тыс. смогли пройти этот порог.

По мнению экспертов, подобные данные говорят о высокой конкуренции на рынке криптовалют и значительных сложностях для новых токенов. Несмотря на огромное количество запусков, большинство из них остается незамеченными или не успевает достичь минимальных требований для выхода на крупные платформы.

Ежедневный выпуск новых токенов варьировался от 30 тыс. до 45 тыс., с некоторыми пиками, которые видны на графике, опубликованном экспертами. В последние дни количество новых мем-криптовалют только растет. Однако общий процент успешных проектов остается низким. Это подчёркивает, что даже при большом энтузиазме разработчиков и инвесторов, успех требует серьезных усилий, маркетинга и стратегии.

Для инвесторов эти данные также служат предупреждением. Большая часть новых токенов может оказаться нерентабельной, поэтому анализ и изучение проектов перед вложениями крайне важны. Высокая волатильность и быстрые изменения на рынке делают вложения в мем-токены рискованными.

Pump.fun показывает, насколько крипторынок стал доступным для новичков, но также подчеркивает необходимость качественных проектов с долгосрочным потенциалом. Без сильной идеи и поддержки шансы выжить среди тысяч конкурентов минимальны. В целом, текущая ситуация демонстрирует, что рынок токенов перенасыщен. Инвесторам и разработчикам предстоит адаптироваться к таким условиям, чтобы достигать успеха и выделяться на фоне других.

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NVIDIA CPU Advances, China's RISC-V Responds: Semiconductor Deep Dive - Part Four

NVIDIA is set to launch its new Vera AI data center CPU in China as early as August, with high pricing. While this move offers a new option, it highlights China's continued dependence on foreign-controlled Arm architecture. In response, the Chinese semiconductor industry is increasingly turning to RISC-V as a strategic alternative for achieving high-performance computing autonomy. The article explores the concept of the "impossible triangle" in CPU development—balancing prosperity, control, and autonomy—and posits that RISC-V's open-source, modular nature offers a unique path to achieving all three. While RISC-V is already dominant in embedded systems, the focus is now shifting to data centers and AI workloads. China has become a global hotspot for RISC-V development, driven by AI-driven compute demand, supply chain concerns from export controls, cost benefits of open-source, and strong policy support. Multiple Chinese companies have reportedly crossed the key performance threshold of 15 SPECint per GHz, a benchmark for entering the high-performance CPU club. Progress extends beyond single-core benchmarks. Companies are developing complete computing subsystems, including commercial-grade coherent network-on-chip (NoC) technology and server processors with up to 40 cores that strictly adhere to the RVA23 standard to ensure software compatibility. Real-world applications are emerging in areas like video transcoding and edge AI. However, significant challenges remain. The RISC-V ecosystem faces fragmentation, immature toolchains and verification processes, and gaps in single-core performance and energy efficiency compared to mature x86 and Arm architectures. The formidable software moat, epitomized by NVIDIA's CUDA, is a long-term hurdle. In conclusion, while RISC-V cannot immediately replace offerings like NVIDIA's Vera, it represents a viable long-term path for China to develop a self-sufficient, high-performance CPU ecosystem. The journey is acknowledged to be long and arduous, requiring sustained effort to overcome technical and ecosystem challenges.

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My Coding Betting Dashboard is Profiting, but Polymarket is Truly Not a Good Place for 'Arbitrage'

The author built a custom monitoring dashboard for Polymarket, a prediction market platform, and tested it with $1,600, achieving over 30% returns. However, the core argument is that Polymarket is not a good venue for traditional arbitrage. The dashboard has two main sections: a "Portfolio Dashboard" for tracking active positions with key metrics like total capital, P&L, and a risk-control module using a tier system (T1, T2, T3), and an "Opportunity Watchlist" for monitoring markets. The article details a critical structural trap in binary markets: a bet with a high perceived probability of success still carries a 100% loss risk if wrong. The author's T1/T2/T3 system is designed to manage this by limiting position sizes based on conviction and time horizon, emphasizing that high confidence should not equal high concentration. A key insight is the danger of "pseudo-diversification"—betting on different markets driven by the same underlying variable. The author concludes that Polymarket offers few true low-risk, arbitrage opportunities. It is instead a high-risk environment where wins can create a false sense of mastery, leading to large losses. The platform is better viewed as a training ground for honing judgment through disciplined, framework-driven betting rather than a reliable income source. The tools help transform intuition into structured, rule-based decisions to mitigate the risk of catastrophic errors.

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**"WeChat AI Card" Practical Test Guide: Has the Era of AI Shopping Arrived?** WeChat has officially launched the "AI Exclusive Card," a feature integrated into its Workbuddy AI assistant. This card is designed to handle payments for AI-initiated purchases. Our hands-on test reveals it's not yet a tool for fully autonomous AI shopping, but rather a controlled payment layer for AI agents. The AI Card functions as an isolated sub-wallet within WeChat Pay. Users must bind the card and transfer funds into it from their main wallet. Crucially, every transaction requires explicit user confirmation via smartphone scan; AI cannot spend autonomously. Currently accessible through the Workbuddy agent, the card targets specific digital consumption scenarios: purchasing paid content (reports, data), calling paid APIs/tools, and subscribing to services. Its design prioritizes security and control by separating funds and mandating approval for each payment. We tested a real-world scenario: ordering bubble tea via Workbuddy using a "Meituan Life Assistant" skill. The process encountered multiple hurdles: high "skill" usage costs (exceeding daily free credits), and most importantly, while a payment was successfully initiated, the AI purchased an incorrect product (a mismatched group-buy coupon instead of the desired drink). This highlights the current limitation: the **AI Card only solves the payment step**. The broader challenge lies in the **AI agent's execution chain**—accurately understanding intent, navigating third-party platforms, selecting the right product, and ensuring proper fulfillment. The payment succeeded, but the purchase failed to meet the user's need. In conclusion, the WeChat AI Exclusive Card is a cautious, early-step experiment in AI commerce. It provides a secure, user-controlled payment method for agent interactions but is not yet capable of reliable, end-to-end complex purchases. For now, it's best used for low-value, low-risk digital services with careful user verification at each step. The vision of AI handling complete shopping tasks remains a work in progress.

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323 Totale visualizzazioniPubblicato il 2024.12.12Aggiornato il 2026.06.02

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