LBank主办“人工智能与Web3创新论坛”,拓宽加密货币与人工智能融合的未来边界

深潮Published on 2025-06-20Last updated on 2025-06-20

这一重要活动汇聚行业先锋,探讨人工智能和Web3如何革新去中心化金融并推动加密货币的未来。

全球领先的加密货币交易所LBank将于2025年6月26日在香港千禧新世界酒店举办人工智能与Web3创新论坛。

这一重要活动汇聚行业先锋,探讨人工智能和Web3如何革新去中心化金融并推动加密货币的未来。

人工智能与Web3创新论坛将汇集加密货币领域的领导者、开发者和创新者,共同探讨人工智能与Web3融合的变革潜力。

主要讨论主题包括:

• 人工智能时代的突破:数据智能重构与增长路径

• LBank生态系统项目深度剖析:探索重塑去中心化金融的突破性项目

• 云计算+人工智能引擎:解锁去中心化生态系统的新范式

• LBank特别专场:来自浪潮背后的独家见解

论坛将聚焦于领先项目、基础设施提供商和重要的生态系统合作伙伴,包括TUBE协议、HyperX、IPX、HF RealX、Taiko、Indonesia blockchain center、Aetherium Digital、Project J、olaxbt、Floxypay、ArtDollar和Quantoz。此外,本次活动得到多家知名媒体的广泛关注,包括CoinGape、Crypto.news、ODaily、MetaEra、TechFlame、Foresight News、PANews、Dethings、Marsbit、TechFlow、币界网和B.NEWS,它们将为论坛提供深入报道和行业洞察。

“LBank社区天使官兼风控顾问Eric He表示:“人工智能不仅仅是一个短暂的流行词——它是一个正在迅速重新定义互联网架构和价值创造本身的转折点。这是一个重新定义加密世界信任、效率和可访问性的范式转变。LBank通过此次论坛,致力于催化对话和创新,探索可能性边界。”

2025年2月,LBank Labs成功举办了“AI in the Skyline”峰会,呈现了人工智能驱动的区块链解决方案并推动了行业合作。通过此次论坛,LBank旨在通过创造可扩展解决方案和推动区块链大规模采用,为开发者、投资者和爱好者赋能。

立即注册,加入论坛,引领下一趋势!

关于LBank

成立于2015年,LBank是全球领先的加密货币交易平台,拥有1,500万+注册用户,覆盖210+国家和地区。LBank已稳健运营 9 年,始终保持零安全事故。LBank日交易量超过40亿美元,支持800多种加密货币,致力于为用户提供多元化、便捷的交易体验。通过创新的交易解决方案,LBank帮助用户在新资产上市时实现130%以上的平均收益。

作为 Meme 资产市场的先锋,LBank 已累计上线超过 300 个主流 Meme 资产及 50+金狗meme资产,Meme资产百倍币比例行业第一。凭借上币速度最快、Meme深度第一和交易包赔等优势,LBank 已成为全球 Meme 投资者的首选平台。

关注LBank获取最新资讯

• 官网:https://www.lbank.com/

• 推特:https://twitter.com/LBank_Exchange

• 电报:https://t.me/LBank_en

• Instagram:https://www.instagram.com/lbank_exchange

• LinkedIn:https://www.linkedin.com/company/lbank

Related Reads

South Korean Institutions' Crypto Race: Dual Explosion of Stablecoins and RWA

**Summary: South Korea's Institutional Crypto Race: Stablecoins and RWA Take Off** South Korea is undergoing a structural shift in its crypto ecosystem, moving beyond its historical role as a major retail trading hub. Major financial institutions and internet platforms are now building institutional-grade blockchain infrastructure, with stablecoins and Real-World Asset (RWA) tokenization as the primary drivers. The push for a regulated Korean won stablecoin market is a major policy and corporate focus. This is driven partly by an estimated $115 billion outflow into dollar stablecoins like USDC, threatening the domestic financial system. Banks (e.g., KB Financial, Hana), payment giants (e.g., Shinhan Card, BC Card), and internet super-apps (KakaoPay, NAVER Pay) are all conducting pilots. The goal is to anchor future digital finance to the Korean won and local regulations. In RWA, South Korea is advancing rapidly within regulatory sandboxes, focusing on unique domestic assets beyond typical global templates like US Treasuries. Projects involve tokenizing ships (with Hyundai Heavy Industries), defense supply chain assets, and K-pop intellectual property, alongside more conventional assets. A legal framework is set for 2027, and platforms like NXT are preparing for regulated trading. Key opportunities for crypto-native projects lie in providing the underlying technology these traditional institutions lack: global distribution channels for tokenized assets, cross-chain liquidity solutions, and enabling infrastructure tools (e.g., for asset packaging and management). Partnerships, such as Solana with Shinhan Card or LayerZero with the Korea Gold Exchange, exemplify this proactive approach. Crucially, user access is being shaped by consumer platforms. NAVER's planned acquisition of Upbit's operator Dunamu and Kakao's development of a unified wallet aim to seamlessly integrate crypto with everyday payments for tens of millions of users. The race is now about which protocols and projects will become the foundational standards as regulation solidifies and institutional adoption accelerates.

Foresight News43m ago

South Korean Institutions' Crypto Race: Dual Explosion of Stablecoins and RWA

Foresight News43m ago

How to Detect AI-Generated Videos? A Review of Dynamic, Traceable, and Explainable Detection Systems

**How to Detect AI-Generated Videos: A Survey on Dynamic, Traceable, and Explainable Detection Systems** With rapid advances in AI video generation (e.g., Sora, Veo), creating highly realistic, multi-minute videos is now possible, widening the gap with detection research. Current AI video detection, often limited to unreliable binary classifications, is insufficient. This survey, accepted at ACL 2026, reframes the goal as **"factual fidelity verification"**—checking if a video's content (who, when, where, what) aligns with the real world perceptually and cognitively. It categorizes AI-generated videos into three paradigms: **Local Manipulation Videos (LMV**, e.g., face swaps), **Audio-Visual Editing (AVE**, e.g., lip-syncing), and **Generative Video Synthesis (GVS**, fully synthetic videos like Sora's). Detection challenges evolve from visual artifacts in LMV to multi-modal inconsistencies in AVE and higher-level world knowledge violations in GVS. The core proposal is a **Vision-Language Dual-View framework** with four hierarchical layers: 1. **Layer 1 (Intrinsic Visual Cues):** Analyzes low-level signal statistics, noise patterns, and physiological signals. 2. **Layer 2 (Spatiotemporal Consistency):** Checks for temporal coherence in object motion and scene dynamics. 3. **Layer 3 (Cross-Modal Consistency):** Verifies alignment between video, audio, and text within the video. 4. **Layer 4 (Language-Guided World-Level Reasoning):** Uses external knowledge, facts, and physical laws to judge semantic plausibility and factual correctness. The survey traces a shift in detection focus from lower layers (1 & 2) toward higher, language-involved layers (3 & 4). It also reviews evolving evaluation metrics and datasets tailored for each video paradigm. The conclusion advocates for a **dynamic, evidence-first detection system** that moves beyond simple classification. Future trustworthy detection requires combining visual evidence (from CV) with semantic reasoning and explanation (from NLP & multimodal AI), ultimately creating traceable and explainable judgments about a video's adherence to real-world constraints.

marsbit1h ago

How to Detect AI-Generated Videos? A Review of Dynamic, Traceable, and Explainable Detection Systems

marsbit1h ago

It Turns Out the First Real-World Application of AI x Crypto is in Security Auditing

The article explores the surprising trend where AI's first major impact on crypto has been in security auditing, not in areas like trading or analytics. It details how AI-powered tools are dramatically lowering the barrier to finding smart contract vulnerabilities, enabling attackers to scan thousands of contracts and execute exploits within minutes. This has rendered traditional, manually-produced audit reports with their month-long validity periods increasingly obsolete, creating a critical "structural crack" in the old security model. Cases like Drift Protocol and KelpDAO show that even extensively audited protocols can be hacked through social engineering, operational flaws, or infrastructure misconfigurations beyond pure code review. Attackers are also using AI to find and exploit vulnerabilities in years-old, deployed contracts. Notably, OpenZeppelin's co-founder has expressed a grim view that "all DeFi is insecure" due to AI's asymmetric advantage. In response, the audit industry is undergoing a fundamental shift. While there's a short-term spike in defensive re-audits, the long-term business model is changing. Firms are developing AI-assisted systems and moving from one-time report deliveries towards embedded, continuous services like real-time monitoring and formal verification. Examples include AI tools uncovering critical, previously missed vulnerabilities in heavily audited protocols like Curve Finance and Zcash. The conclusion is that security must become a continuous investment, not a one-time checkbox, and audit firms must rapidly evolve their tools and service models to survive.

marsbit1h ago

It Turns Out the First Real-World Application of AI x Crypto is in Security Auditing

marsbit1h ago

Trading

Spot
活动图片