火币高管面对面|火币 HTX 资产负责人 Jasper 详解优质资产捕捉法则

深潮TechFlowPubblicato 2025-08-10Pubblicato ultima volta 2025-08-11

Introduzione

为了尽可能捕捉潜在优质资产,火币HTX建立了一套健全的研判与评估体系。

近期,火币HTX新上线资产表现亮眼,尤其是$TREE(Treehouse)于7月29日上线后,迅速冲上平台热榜,首日涨幅更是高达6倍,引发市场关注和热议。


8月7日,火币HTX资产部门负责人Jasper受邀出席“火币高管面对面”第三期,围绕火币HTX新资产筛选机制、“长牛潜力股”的关键指标等话题,详细回应了来自X、社群及HTX DAO委员的问题。


新资产筛选机制:严谨评估,捕捉优质潜力股


为了尽可能捕捉潜在优质资产,火币HTX建立了一套健全的研判与评估体系。
据Jasper介绍,对于已上线交易所的项目,火币HTX会重点关注其后续发展情况,评估项目是否在持续推进;对于尚未发币的项目,在评估过程中会综合参考链上多项关键指标,包括持仓分布、链上活跃度、智能合约是否存在漏洞或后门风险,以及项目估值的合理性等,确保筛选出的项目具备良好的潜力和安全性。
“火币HTX会提前长达一年时间跟踪、锁定可能发币的潜力项目,并通过两到三轮的深度评估来判断是否具备上线资格。纬度包括项目团队背景、投资机构、赛道、反洗钱、KYC、合约安全性、实际运营进展、相关流量数据、产品概况、社群热度、社媒口碑、经济模型、筹码分布、链上数据是否真实等,同时借助RootData、Glassnode、CertiK等数据平台来验证链上的数据和合约安全性,确保数据的准确和全面。”


Jasper强调,判断项目“长牛”潜力的关键在于其赛道的刚需属性。例如,AAVE、UNI、LINK、TRX等与DeFi和基础设施相关的项目,真正满足行业核心需求,且具备稳定流水和盈利能力,因而被视为刚需产品,长期表现看好。相反,那些依赖包装概念、虚假数据或伪需求炒作的项目,火币HTX 会通过评估体系及时识别并筛除。


Jasper介绍称,如此严谨的筛选保证了90%以上的重点项目不会被错过。即便如此,对于一些市场热度极高但整体估值和市场反馈不理想的项目,比如“PUMP”类资产,火币HTX 也会果断拒绝上线,因为这本质上是一场赌局,宁可错过,也绝不盲目追高。“今年以来,火币HTX已成功规避了至少三个爆雷项目,充分证明了这一评估体系的可靠性。”


探索资产观察与创新区分层,助力社区参与与透明投资


为增强社区的参与感和信息透明度,火币HTX还在积极探索“资产观察名单”和“试运营区”的创新机制。


Jasper 透露,HTX DAO发起的投票荐币本质就是一个观察区,DAO社区成员可以通过投票推荐和评审潜力项目,成为官方筛选流程的重要补充。同时,火币HTX 在今年第二季度开设了创新区版块,专门用于展示确定性较低、波动较大的早期项目或 Meme 币;主区则保留给更加成熟和优质的资产,帮助用户在不同风险偏好之间进行选择。


直播中,Jasper坦言,没有任何一家交易所能保证每个上线项目都会有出色的表现,哪怕是币安、Upbit 这样的头部平台也不例外。


“交易所只是一个提供资产流通的场所,只在中间收取合理手续费,不会控制币种的涨跌。代币价格波动受项目方实力、做市策略、经济模型、市场情绪、社区热度、大盘走势、估值合理性等多重因素影响。投资者在进入市场前必须做好充分调研,理性判断,为自己的决策负责。”

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ChainCatcher Daily Summary - June 1, 2026 In regulatory news, the U.S. OCC granted preliminary conditional approval for Laser Digital to establish a federally regulated trust bank. In Vietnam, a draft law amendment proposes allowing SMEs to use digital and virtual assets as loan collateral. Hong Kong's SFC chairman reported that trading volume on the city's 12 licensed virtual asset platforms grew nearly 300% YoY in Q1 2026. Notable incidents include the Cosmos ecosystem cross-chain bridge Gravity Bridge pausing services after an attack. Aave published a post-mortem on the April 18th Kelp rsETH bridge attack, attributing it to a third-party bridge infrastructure vulnerability via an RPC poisoning attack, not the Aave protocol itself. In market developments, MicroStrategy's Michael Saylor hinted at a potential upcoming Bitcoin purchase announcement. Fed Governor Waller commented that widespread stablecoin adoption could amplify the impact of U.S. monetary policy. Meanwhile, sentiment analysis from Santiment indicates a record-high Bitcoin long/short ratio of 2.23, potentially signaling a short-term price correction, while Ethereum shows signs of FUD among commentators. In legal matters, the SEC sued the founder of Privvy Investments for an alleged $12.3 million crypto AI trading bot scam. In China, a Qingdao man was sentenced to 10 years and 9 months for stealing 107 BTC by obtaining a victim's wallet seed phrase. Top trending meme tokens on ETH, Solana, and Base networks for the past 24 hours are also listed.

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"In late May, two closely timed events in China's AI industry clearly revealed the divergent strategic approaches of two tech giants: Alibaba and ByteDance. Alibaba is aggressively integrating AI into its existing commercial ecosystem, prioritizing immediate monetization. Its Qwen App now fully integrates with Taobao, leveraging the platform's 4-billion-item database for AI-powered shopping features like virtual try-on and price comparison. Internally, Alibaba has reorganized to incentivize AI-driven business growth, notably through the 'Agentic Commerce Trust Protocol' to enable AI-agent transactions. Financially, it emphasizes ROI, with CEO Daniel Wu stating every AI chip purchased is generating revenue. Alibaba's strategy bets that foundational AI model capabilities won't be leapfrogged in the next five years, allowing its 'AI-as-a-utility' approach to succeed. In stark contrast, ByteDance's Seed division focuses on pushing the frontiers of AGI with a long-term, research-oriented mindset. Its video generation model, Seedance 2.0, topped international benchmarks. The division, led by researchers Wu Yonghui and product head Zhu Wenjia, is tasked with 'exploring the upper limits of intelligence,' even considering open-sourcing its models—a rare move among Chinese firms. ByteDance is investing heavily, with reports of its 2026 capital expenditure plan being nearly triple that of 2024, funded by its substantial private profits. This allows it to pursue projects like an 8-month research paper questioning if video models are true 'world models,' devoid of immediate commercial pressure. The core divergence is less about corporate philosophy and more about structural constraints. As a publicly traded company, Alibaba is bound to quarterly financial expectations, forcing a pragmatic, revenue-focused AI integration. As a private entity, ByteDance has the luxury to fund long-term, high-risk foundational research without answering to public markets. The article concludes that the true determinant of a Chinese company's AI path is its IPO status, suggesting that if ByteDance were public, or if Alibaba were private, their strategies might well be reversed."

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Editor's Note: As AI Agents become cheaper and easier to use, a new constraint emerges: the cost isn't in launching more Agents, but in the human attention required to manage, judge, and integrate their outputs. This hidden cost is called the "orchestration tax." The article argues that a developer's cognitive bandwidth is the key bottleneck—a serial, non-parallelizable resource akin to a Global Interpreter Lock (GIL). While many Agents can run concurrently, their results ultimately require human judgment for review, conflict resolution, and final integration. Therefore, more Agents don't automatically mean higher productivity; they can simply create longer queues, lead to cognitive fatigue, and create the illusion of busyness without real output. The core solution is to design workflows around this scarce human attention. Key strategies include: scaling the number of Agents to match review capacity (not UI capacity), categorizing tasks (delegating independent ones, keeping complex judgment-heavy ones serial), batch reviewing results to minimize context-switching costs, automating verifiable checks to reserve human judgment for critical decisions, and protecting focused, uninterrupted thinking time. Ultimately, the critical skill is not launching many Agents, but architecting systems that respect the fundamental limit of human attention. Unpaid "orchestration tax" accumulates as both technical and cognitive debt, undermining system understanding and quality. True productivity comes from thoughtfully managing the single-threaded resource—your focus.

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