波场TRON近30日日均交易数超686万环比增长2.4%

币界网Pubblicato 2024-07-26Pubblicato ultima volta 2024-07-29

Introduzione

区块链浏览器TRONSCAN数据显示，近30日，波场TRON日均交易数超686万，环比增长2.4%。

币界网报道：
区块链浏览器TRONSCAN数据显示，近30日，波场TRON日均交易数超686万，环比增长2.4%。

依托高吞吐量、可扩展性、高可靠性的底层区块链优势，波场TRON已成为全球增速最快的公链，链上数据也正全面飙升。截至目前，波场TRON账户数突破2.46亿，交易总数突破81亿，总锁仓量（TVL）超219亿美元。此外，波场TRON拥有行业领先的用户活跃度，TVL和链上稳定币总市值均高居全球公链第二，并已承载了价值超13万亿美元的交易。
未来，肩负建设元宇宙金融自由港的全新使命，波场TRON在加快全球化与合规化脚步的同时，将为全球用户创造更多便利，并迎来更多交易量。

Crypto di tendenza

CitreaCTR

wrapped stUSDTWSTUSDT

Velodrome FinanceVELODROME

BrevisBREV

ZRX（0X）ZRX

PancakeSwapCAKE

Letture associate

Dawn Song, The First Lady of Computer Security, Joins Meta

Computer security and AI safety pioneer Dawn Song has joined Meta's Superintelligence Labs as Vice President of AI Research, reporting to MSL head Nat Friedman. Song, a professor at UC Berkeley's EECS department and a MacArthur Fellow, is renowned for her foundational work in dynamic taint analysis and her leadership in adversarial machine learning and AI agent security. Her lab is considered a top training ground in computer security. Song is also a founder of Oasis Labs and Virtue AI, a company focused on enterprise AI safety infrastructure. Virtue AI co-founders Bo Li and Sanmi Koyejo, along with other team members, are also joining Meta, a move seen as strengthening Meta's safety measures for AI agents amid growing industry concerns. Separately, Denny Zhou, founder of Google's Gemini Reasoning Team and a key figure in advancing large language model reasoning techniques like Chain-of-Thought, reportedly joined Meta several months ago. These high-profile hires come as Meta seeks to deploy AI across its products while assuring regulators and the public of its models' robustness against misuse.

marsbit11 min fa

Dawn Song, The First Lady of Computer Security, Joins Meta

marsbit11 min fa

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 News20 min fa

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

Foresight News20 min fa

NVIDIA's New Open-Source MoE: One Line of Import, Fine-Tuning Accelerated by 3.7x

NVIDIA has open-sourced NeMo AutoModel, a tool designed to significantly accelerate the fine-tuning of Mixture-of-Experts (MoE) large language models. By adding just one import line to existing code based on Hugging Face Transformers v5, users can achieve a 3.4x to 3.7x increase in training throughput and reduce GPU memory usage by 29% to 32% without altering their API. The key innovations include Expert Parallelism (EP) to distribute expert weights across GPUs, lowering memory pressure; DeepEP to fuse computation and communication; and TransformerEngine kernels for accelerated core operations. Benchmarks on models like Qwen3-30B-A3B show training throughput per GPU jumping from 3075 to 11340 tokens per second. The solution also enables the fine-tuning of very large models, such as the 550B parameter Nemotron 3 Ultra, which would exceed memory limits with the standard Transformers v5. Code and benchmarks are available on GitHub.

marsbit54 min fa

NVIDIA's New Open-Source MoE: One Line of Import, Fine-Tuning Accelerated by 3.7x

marsbit54 min fa

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.

marsbit56 min fa

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

marsbit56 min fa

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.

marsbit1 h fa

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

marsbit1 h fa

Trading

Spot

Articoli Popolari

Come comprare TRX

Benvenuto in HTX.com! Abbiamo reso l'acquisto di TRON (TRX) semplice e conveniente. Segui la nostra guida passo passo per intraprendere il tuo viaggio nel mondo delle criptovalute.Step 1: Crea il tuo Account HTXUsa la tua email o numero di telefono per registrarti il tuo account gratuito su HTX. Vivi un'esperienza facile e sblocca tutte le funzionalità,Crea il mio accountStep 2: Vai in Acquista crypto e seleziona il tuo metodo di pagamentoCarta di credito/debito: utilizza la tua Visa o Mastercard per acquistare immediatamente TRONTRX.Bilancio: Usa i fondi dal bilancio del tuo account HTX per fare trading senza problemi.Terze parti: abbiamo aggiunto metodi di pagamento molto utilizzati come Google Pay e Apple Pay per maggiore comodità.P2P: Fai trading direttamente con altri utenti HTX.Over-the-Counter (OTC): Offriamo servizi su misura e tassi di cambio competitivi per i trader.Step 3: Conserva TRON (TRX)Dopo aver acquistato TRON (TRX), conserva nel tuo account HTX. In alternativa, puoi inviare tramite trasferimento blockchain o scambiare per altre criptovalute.Step 4: Scambia TRON (TRX)Scambia facilmente TRON (TRX) nel mercato spot di HTX. Accedi al tuo account, seleziona la tua coppia di trading, esegui le tue operazioni e monitora in tempo reale. Offriamo un'esperienza user-friendly sia per chi ha appena iniziato che per i trader più esperti.

1.6k Totale visualizzazioniPubblicato il 2024.12.10Aggiornato il 2026.06.02

Discussioni

Benvenuto nella Community HTX. Qui puoi rimanere informato sugli ultimi sviluppi della piattaforma e accedere ad approfondimenti esperti sul mercato. Le opinioni degli utenti sul prezzo di TRX TRX sono presentate come di seguito.

波场TRON近30日日均交易数超686万 环比增长2.4%