AVAX 的 TVL 上涨 40%, 会推动下一轮上涨吗?

ambcryptoОпубліковано о 2025-07-29Востаннє оновлено о 2025-07-29

Анотація

疲软的网络活动和平淡的社交吸引力可能会限制其上涨空间。成功突破阻力位,加上用户数量的恢复增长,或许能够验证这轮上涨的有效性,并为更高的目标打开大门。

关键要点

DeFi 锁仓总值 (TVL) 和未平仓合约量飙升,但社交和网络指标表现不一。AVAX在双底之后测试阻力位,由于地址增长放缓,市场情绪略有好转。

Avalanche [AVAX] 的DeFi 生态系统在最近的 Octane 升级后得到了显着提升,总锁定价值 (TVL) 环比飙升近 40%,达到 15 亿美元。

这一增长凸显了市场对提高交易速度、降低费用和简化用户体验的反应。

随着资本不断流入生态系统,人们开始质疑当前的势头是否会导致持续的反弹或暂时的兴趣飙升。

衍生品交易员是否发出看涨信号?

过去一周,未平仓合约飙升逾15%,目前达到8.3544亿美元。这一增长反映了对AVAX衍生品的资本配置增加,这通常预示着投机兴趣的上升。

虽然上涨可能会增强持续的涨势,但也会带来波动风险,尤其是在杠杆头寸平仓的情况下。

尽管如此,未平仓合约的持续增长表明交易员的信心,如果有现货需求的支持,可能会扩大上行势头。

然而,如果情绪迅速转变,这种杠杆可能会变成阻力。

AVAX 会突破过去的阻力吗?

AVAX 近期完成了典型的双底形态,并突破了下行趋势线。目前股价在 26-28 美元的阻力位附近徘徊,这一阻力位在历史上一直充当着强大的阻力位。

这种技术设置通常预示着趋势逆转,但确认需要坚决收于阻力位上方。

从该水平的拒绝可能会引发回调以重新测试较低的支撑位。

然而,持续的购买压力(尤其是来自 DeFi 资金流入和交易员的压力)可能为未来几个交易日的彻底突破铺平道路。

为什么情绪在好转,而社会关注度却在减弱?

尽管价格上涨,AVAX 的社会主导地位已下降至 0.419%,反映出围绕该资产的讨论和炒作正在消退。

相比之下,加权情绪略有改善,达到+0.115,表明市场情绪略微转向乐观。这种分化表明,尽管交易员信心正在增强,但更广泛的散户兴趣尚未跟上。

社交媒体影响力的低迷可能会限制这波上涨的影响力,尤其是在媒体关注度跟不上股价表现的情况下。因此,社交媒体热度的飙升可能是推动股价进一步上涨的关键。

尽管网络活动减少,AVAX 还能保持增长势头吗?

网络数据描绘出一幅不太乐观的景象,过去七天新地址下降了 33.93%,活跃地址下降了 10% 以上。

这些数字与价格和 TVL 的上涨形成了鲜明的对比,这意味着上涨可能更多地受到资本轮换而非有机用户增长的推动。

为了长期可持续发展,Avalanche 需要重新引导用户并进行互动。否则,一旦生态系统中最初升级带来的兴奋感消退,当前的势头可能会失去动力。

总而言之,AVAX 显示出技术和基本面实力,TVL 不断上升,价格模式看涨,交易者信心不断增强。

然而,疲软的网络活动和平淡的社交吸引力可能会限制其上涨空间。成功突破阻力位,加上用户数量的恢复增长,或许能够验证这轮上涨的有效性,并为更高的目标打开大门。

Пов'язані матеріали

U.S. Government Bans Foreign Nationals from Using Fable 5, Anthropic Issues Rebuttal

U.S. Government Bans Foreign Access to Fable 5, Anthropic Issues Rebuttal On June 12th, the U.S. government ordered AI company Anthropic to immediately suspend all foreign access—including foreign nationals within the U.S. and Anthropic's own foreign employees—to its newly released Fable 5 and Mythos 5 AI models, citing national security concerns. This forced Anthropic to temporarily disable access to both models for all users globally, as it cannot technically differentiate user nationality at scale. The models, released just three days prior, represent Anthropic's highest public capability tier. Fable 5 is the first publicly available model from the advanced "Mythos" family, while Mythos 5 is a less-restricted version for approved cybersecurity and critical infrastructure partners. The government's directive was reportedly triggered by claims from another company that it could "jailbreak" Mythos 5, raising alarm within the Trump administration. Anthropic, in a detailed public statement, strongly challenged this rationale. The company argues the demonstrated "jailbreak" is a narrow, non-generalized technique that merely involves identifying minor, known software vulnerabilities—a capability common to other publicly available models like OpenAI's GPT-5.5 and routinely used by cybersecurity defenders. Anthropic stated it has complied with the order but disagrees with the government's standard, warning that applying it industry-wide would halt all new frontier model deployments. The company criticized the lack of a transparent, fact-based legal process and expressed confidence the situation stems from a misunderstanding. It is working to restore access and will release more technical details within 24 hours. Other Anthropic models remain unaffected.

链捕手10 хв тому

U.S. Government Bans Foreign Nationals from Using Fable 5, Anthropic Issues Rebuttal

链捕手10 хв тому

The Revelation from the Raydium Theft Incident: New DeFi Vulnerabilities Lurking in Forgotten Old Contracts

**Raydium Exploit Reveals DeFi's Hidden Risk: Forgotten "Zombie" Contracts** A recent attack on Raydium's deprecated V3 AMM pools resulted in a loss of approximately $1.34 million. The hacker exploited pools that were no longer supported by Raydium's current UI or SDK but remained fully functional and accessible on-chain. This incident highlights a critical, often overlooked category of risk in DeFi: inactive or legacy smart contracts that projects fail to properly decommission. Since March 2025, there have been at least 8 publicly reported attacks targeting such abandoned contracts, with total losses around $10.8 million. Including older pools and deprecated features, the count rises to 10 incidents with roughly $22.5 million in losses. These "zombie contracts" represent a lifecycle management failure rather than a code vulnerability, yet they are typically misclassified under general "code bug" categories in security reports, masking the true scale of the problem. The root cause is that projects often merely document a contract as "deprecated" without taking essential technical steps to secure it: withdrawing remaining assets, disabling external call functions, and implementing ongoing monitoring. These forgotten, under-monitored components become prime targets for attackers. To address this, the industry needs to recognize "zombie contracts" as a distinct risk category and establish standardized decommissioning protocols. Essential steps should include: 1) a formal retirement announcement, 2) removal of all front-end integrations, 3) withdrawal of locked assets, 4) disabling key contract functions, 5) ongoing security monitoring, 6) clear user communication, and 7) a post-mortem analysis. The value of a DeFi project lies not only in its current TVL but also in the security of its historical codebase, which has now become a new attack surface.

Foresight News1 год тому

The Revelation from the Raydium Theft Incident: New DeFi Vulnerabilities Lurking in Forgotten Old Contracts

Foresight News1 год тому

Robots Begin to 'Consume Data': The Hidden Production Chain from Indian Data Factories to Billion-Dollar Humanoid Robots

Robots have started to 'consume data,' driving the formation of a new industrial supply chain focused on producing training data for embodied AI. Unlike large language models, which are trained on vast internet text corpora, embodied AI models face a 'data desert' in the physical world. This has created a massive demand for first-person perspective video data (Ego Data), captured by workers wearing cameras in places like Indian garment factories. Companies like Neocambrian AI are establishing 'data factories' where workers perform standardized tasks (e.g., sorting clothes, kitchen organization) to generate thousands of hours of video. Research, such as NVIDIA's EgoScale, demonstrates that scaling this human demonstration data predictably improves robot performance, particularly for dexterous manipulation. This has validated a training path combining large-scale human data for pre-training with smaller amounts of robot-specific data for fine-tuning. The value of different data types varies significantly, forming a 'data pyramid.' The base consists of low-cost, large-scale internet and Ego Data. Higher layers include more expensive motion-capture data (e.g., from data gloves), simulation/synthetic data, and the most costly and scarce layer: real robot teleoperation data. This demand has spawned a layered ecosystem of data suppliers: low-cost data factories, motion capture and alignment specialists, robot-native teleoperation service providers, simulation data companies, and platforms aiming for data standardization. Robot companies themselves are adopting a 'layered procurement' strategy: outsourcing generic Ego Data while building in-house capabilities for robot-specific adaptation data and the critical deployment/failure data generated in real-world applications. The industry is shifting focus from hardware and basic mobility to the data pipelines required for general-purpose capability. While parallels exist to data labeling companies like Scale AI in the LLM boom, the physical complexity of robot data—involving action success ambiguity and sim-to-real gaps—requires more integrated solutions for data collection, annotation, and a continuous feedback loop. The race is on to build the data engines that will teach robots to operate reliably in the unstructured real world.

marsbit4 год тому

Robots Begin to 'Consume Data': The Hidden Production Chain from Indian Data Factories to Billion-Dollar Humanoid Robots

marsbit4 год тому

Торгівля

Спот
Ф'ючерси

Популярні статті

Як купити AVAX

Ласкаво просимо до HTX.com! Ми зробили покупку Avalanche (AVAX) простою та зручною. Дотримуйтесь нашої покрокової інструкції, щоб розпочати свою криптовалютну подорож.Крок 1: Створіть обліковий запис на HTXВикористовуйте свою електронну пошту або номер телефону, щоб зареєструвати обліковий запис на HTX безплатно. Пройдіть безпроблемну реєстрацію й отримайте доступ до всіх функцій.ЗареєструватисьКрок 2: Перейдіть до розділу Купити крипту і виберіть спосіб оплатиКредитна/дебетова картка: використовуйте вашу картку Visa або Mastercard, щоб миттєво купити Avalanche (AVAX).Баланс: використовуйте кошти з балансу вашого рахунку HTX для безперешкодної торгівлі.Треті особи: ми додали популярні способи оплати, такі як Google Pay та Apple Pay, щоб підвищити зручність.P2P: Торгуйте безпосередньо з іншими користувачами на HTX.Позабіржова торгівля (OTC): ми пропонуємо індивідуальні послуги та конкурентні обмінні курси для трейдерів.Крок 3: Зберігайте свої Avalanche (AVAX)Після придбання Avalanche (AVAX) збережіть його у своєму обліковому записі на HTX. Крім того, ви можете відправити його в інше місце за допомогою блокчейн-переказу або використовувати його для торгівлі іншими криптовалютами.Крок 4: Торгівля Avalanche (AVAX)Легко торгуйте Avalanche (AVAX) на спотовому ринку HTX. Просто увійдіть до свого облікового запису, виберіть торгову пару, укладайте угоди та спостерігайте за ними в режимі реального часу. Ми пропонуємо зручний досвід як для початківців, так і для досвідчених трейдерів.

596 переглядів усьогоОпубліковано 2024.12.12Оновлено 2026.06.02

Як купити AVAX

Обговорення

Ласкаво просимо до спільноти HTX. Тут ви можете бути в курсі останніх подій розвитку платформи та отримати доступ до професійної ринкової інформації. Нижче представлені думки користувачів щодо ціни AVAX (AVAX).

活动图片