El registro de MiCA muestra una avalancha de solicitudes de licencias cripto antes del plazo de la UE

ambcryptoPubblicato 2026-07-03Pubblicato ultima volta 2026-07-03

Introduzione

El registro de ESMA muestra una avalancha de autorizaciones de proveedores de servicios de criptoactivos (CASP) justo antes de que finalizara el período transitorio del Reglamento MiCA de la UE. Entre el 23 de junio y el 1 de julio se emitieron 36 licencias, elevando el total a 283 CASP autorizados. Alemania lidera la clasificación con 59 registros, seguida de Francia (31), Países Bajos (28), Malta (22) y Chipre (21). Sin embargo, la mayoría de las autorizaciones se concentran en servicios como custodia y transferencia; solo 17 empresas tienen permiso para operar plataformas de negociación de criptomonedas, lo que subraya que el alto número total no equivale a muchas bolsas autorizadas.

Los reguladores europeos autorizaron a docenas de empresas de criptomonedas en los últimos días antes de que finalizara el período transitorio de MiCA en la UE, según un análisis de los últimos datos del registro de la ESMA.

El registro muestra 36 autorizaciones de proveedores de servicios de criptoactivos fechadas entre el 23 de junio y el 1 de julio, lo que destaca un último impulso para obtener licencias mientras las empresas se esforzaban por cumplir con las nuevas normas unificadas de criptomonedas del bloque.

Las empresas cripto se apresuraron a obtener aprobación antes del plazo de MiCA

El registro de CASP cargado muestra 283 registros de proveedores de servicios de criptoactivos autorizados, con 66 autorizaciones fechadas solo en junio.

El ritmo se aceleró cerca de la fecha límite. El registro enumera 13 autorizaciones el 30 de junio, un día antes de que finalizara el período transitorio, y una más el 1 de julio.

La ESMA había advertido que los proveedores no autorizados que atiendan a clientes de la UE deberían dejar de incorporar nuevos clientes y comenzar a reducir sus actividades reguladas una vez finalizado el período transitorio.

Alemania lidera la carrera de licencias MiCA en Europa

Alemania tiene el mayor número de CASP autorizados en el registro, con 59 registros.

Le sigue Francia con 31, luego los Países Bajos con 28, Malta con 22 y Chipre con 21.

Los datos sugieren que las autorizaciones de MiCA siguen concentradas en un puñado de jurisdicciones, a pesar de que el reglamento crea un marco de pasaporte para que las empresas licenciadas operen en todo el Espacio Económico Europeo.

Las aprobaciones de plataformas de trading siguen siendo limitadas

El registro también muestra que no todas las licencias de MiCA son iguales.

Los permisos de custodia, servicios de transferencia e intercambio parecen ser mucho más comunes que las autorizaciones de plataformas de trading. Solo 17 empresas en el archivo están autorizadas a operar una plataforma de trading de criptomonedas.

Esta distinción es importante porque una cifra elevada de CASP no significa que Europa tenga 283 intercambios completamente autorizados. Muchas empresas poseen permisos más limitados, como custodia, servicios de transferencia, ejecución de órdenes o intercambio de criptomonedas por moneda fiduciaria.

Resumen Final

Los datos del registro de la ESMA muestran que se emitieron 36 autorizaciones de CASP entre el 23 de junio y el 1 de julio, lo que sugiere una oleada tardía de aprobaciones de MiCA antes del plazo de la UE.
Alemania lidera con 59 registros de CASP autorizados, mientras que solo 17 empresas están autorizadas a operar plataformas de trading de criptomonedas.

Crypto di tendenza

CitreaCTR

wrapped stUSDTWSTUSDT

Velodrome FinanceVELODROME

BrevisBREV

ZRX（0X）ZRX

PancakeSwapCAKE

Domande pertinenti

Q¿Qué revela el registro de ESMA sobre las autorizaciones de CASP en los días previos al fin del período transitorio de MiCA?

AEl registro de ESMA revela que se autorizaron 36 proveedores de servicios de criptoactivos (CASP) entre el 23 de junio y el 1 de julio, mostrando una oleada de aprobaciones de última hora antes de que finalizara el plazo de MiCA.

Q¿Cuál es el país europeo con el mayor número de CASP autorizados según el registro MiCA?

AAlemania es el país con el mayor número de CASP autorizados, con 59 registros en el listado.

QSegún el artículo, ¿cuántas empresas están autorizadas específicamente para operar una plataforma de negociación de criptomonedas bajo MiCA?

ASolo 17 empresas en el registro están autorizadas específicamente para operar una plataforma de negociación de criptomonedas.

Q¿Qué advertencia había dado ESMA a los proveedores no autorizados que atendían a clientes de la UE?

AESMA había advertido que los proveedores no autorizados que atendían a clientes de la UE debían dejar de incorporar nuevos clientes y comenzar a reducir sus actividades reguladas una vez finalizado el período transitorio.

Q¿Qué tipo de permisos de CASP parecen ser más comunes que las autorizaciones para plataformas de negociación, según los datos del registro?

ALos permisos para servicios de custodia, transferencia e intercambio (de cripto a moneda fiduciaria) parecen ser mucho más comunes que las autorizaciones para operar plataformas de negociación.

Letture associate

Anthropic Creates an AI Jailbreak 'Penal Code': Your Requests, Four Ways to Die

Anthropic has publicly detailed its security measures and a new "Cyber Jailbreak Severity" (CJS) framework following the controversial takedown of its Fable 5 model. The incident, triggered by simple user requests like counting letters or stating a profession, highlighted overzealous safety filters. Anthropic classifies cybersecurity-related prompts into four tiers: malicious activities (blocked), high-risk dual-use (like pentesting, with strict limits), low-risk dual-use (often blocked by "safety margin" errors), and harmless tasks (theoretically allowed but still frequently flagged). The company admits its classifiers are tuned for high sensitivity, leading to many false positives. The newly proposed CJS framework aims to objectively score the severity of AI "jailbreaks" (prompts that bypass safety rules) on a 0-10 scale across four dimensions: Capability Gain (does it grant new attack abilities?), Breadth (does it work across multiple attack types?), Weaponization Ease (how hard is it to turn into a real attack?), and Discoverability (how easy is it to find?). The score determines the response, from no action (CJS-0) to a potential model takedown (CJS-4). The score is context-dependent; for example, discovering a major unknown vulnerability today scores high, while asking about a well-known one scores low. The article raises concerns about Anthropic's dual role: it is both creating powerful models (like the restricted Mythos 5) and defining the rules (CJS) for judging their misuse, potentially giving it disproportionate influence. This is set against the backdrop of U.S. export controls, which for the first time directly restricted API access to a model (Fable 5), creating a "tiered" system where public models are heavily filtered and advanced ones are limited to vetted partners. The CJS framework is portrayed as potentially providing regulators with a metric to justify future API shutdowns. For users, the advice is to carefully phrase prompts, watch for signs of being downgraded to a weaker model, and wait indefinitely for promised filter improvements.

marsbit25 min fa

Anthropic Creates an AI Jailbreak 'Penal Code': Your Requests, Four Ways to Die

marsbit25 min fa

$100M Annual Revenue, Two Berkeley Roommates in Their 20s Build the Most Profitable AI Business

Arena, the AI model ranking platform, has become a $100 million annual revenue business just eight months after launching its commercial service. Originally a UC Berkeley open-source research project called Chatbot Arena, it created a "battle arena" where users blind-test and vote on anonymous AI model responses. This has generated a highly trusted, community-driven leaderboard based on over 10 million user evaluations and 82 million votes. Major AI companies like OpenAI, Google, and Anthropic submit their flagship models to be ranked. The core monetization strategy is its AI Evaluations service, where model developers and large enterprises pay for in-depth performance analysis from Arena's massive user community. This provides real-world feedback on model strengths, weaknesses, and hallucinations—a critical service as models become more complex. The company, spun out from Berkeley in early 2025, quickly raised $100 million in seed funding at a $600 million valuation and later secured a $150 million Series A at a $1.7 billion valuation. The founding team includes CEO Anastasios Angelopoulos, a mathematician focused on rigorous model evaluation; CTO Wei-Lin Chiang, creator of the popular Vicuna chatbot; and co-founder Ion Stoica, a renowned Berkeley professor. Arena is now expanding beyond chat benchmarks into "Agent Mode," evaluating AI agents on complex, multi-step tasks like coding and research. The company's success illustrates the growing value and cost of independent, real-world AI model evaluation as the industry intensifies.

marsbit29 min fa

$100M Annual Revenue, Two Berkeley Roommates in Their 20s Build the Most Profitable AI Business

marsbit29 min fa

Racking Up 24,000 Stars: With One Command, AI Can Now Find Its Own Skills

Vercel, known for its developer tools like Next.js, has launched 'skills', a package manager for AI coding agents, garnering 24,000 GitHub stars. It allows developers to add specialized capabilities, such as React best practices, to AI assistants like Claude Code or Cursor with a single command: `npx skills add <package>`. Skills are shareable, reusable modules that define an AI agent's behavior for specific tasks, moving beyond one-off prompt engineering towards standardized 'capability engineering'. A key innovation is the 'find-skills' skill, which acts as an internal search engine, allowing an agent to autonomously find and install the right skill for a user's request. This lowers the barrier for non-developers to leverage advanced AI coding assistance. However, this 'npm moment' for AI brings significant security risks. Security audits of thousands of skills on platforms like skills.sh and ClawHub found over 30% contained security flaws, with about 13% classified as severe. Threats include malicious scripts that can access local files and credentials, and prompt injection hidden within skill documentation. Unlike traditional code packages, skills blend instructions, code, and system access, posing a direct risk to user machines and data. Experts advise treating skills like code—reviewing them carefully before installation, especially their scripts, and being wary of excessive permissions. Ultimately, Vercel's initiative represents a major shift towards modular, reusable AI capabilities, but its rapid adoption requires developers to bring the same caution used in managing traditional software dependencies.

marsbit30 min fa

Racking Up 24,000 Stars: With One Command, AI Can Now Find Its Own Skills

marsbit30 min fa

Token Devours One-Third of Payroll, Silicon Valley's AI Bill is Spinning Out of Control

The article discusses the dual reality of AI token costs in Silicon Valley. While research firm SemiAnalysis reports spending 30% of its employee salary budget on internal LLM tokens—translating to massive productivity gains like converting complex Excel models in minutes—other giants are struggling with ballooning, uncontrolled AI bills. Uber exhausted its annual AI budget in months after rapid engineer adoption, and Microsoft is cutting third-party AI tools due to high costs. NVIDIA's CEO argues tokens are becoming "means of production" and plans substantial AI budgets per engineer. Despite current cost concerns, the analysis emphasizes that cost collapse is just beginning. Through software optimizations (like 14x throughput boosts) and next-gen hardware (e.g., GB300 NVL72 with 17-32x H100 performance), real token costs can fall far below list prices. Anthropic's gross margins reportedly soared as token prices dropped. Gartner predicts a >90% inference cost drop by 2030. The piece highlights a split: massive AI capex ($740B announced) contrasts with tech layoffs and minimal measured economic impact so far. The transition mirrors past infrastructure shifts—investment precedes widespread productivity. For early adopters like SemiAnalysis, tokens already deliver high leverage; for others, the choice is to adopt now or risk falling behind.

marsbit34 min fa

Token Devours One-Third of Payroll, Silicon Valley's AI Bill is Spinning Out of Control

marsbit34 min fa

Claude Engineer Finally Unveils Fable 5's Ultimate Strategy, Teaching You How to Bridge the Information Gap with AI Models

This article, titled "Claude Engineer Finally Releases Fable 5 'Skill-Burning' Guide, Teaching How to Bridge the Information Gap with Models," details a blog post by Claude Code engineer Thariq Shihipar. The core concept is the "information gap" or "unknowns"—the disconnect between a user's instructions (the "map") and the actual task requirements (the "territory"). The article argues that with powerful models like Claude Fable 5, work quality depends on the user's ability to identify and clarify these unknowns. Shihipar categorizes unknowns into four types: Known Knowns (explicit instructions), Known Unknowns (awareness of gaps), Unknown Knowns (implicit, unstated knowledge), and Unknown Unknowns (unforeseen issues). The blog provides a framework for addressing these gaps throughout the workflow: * **Before Implementation:** Techniques include "Blindspot Scanning" to uncover Unknown Unknowns, brainstorming/prototyping for visual or complex tasks, having Claude ask clarifying questions, using reference code/examples, and creating implementation plans. * **During Implementation:** Maintaining an "implementation notes" file for Claude to document deviations and decisions made due to encountered edge cases. * **After Implementation:** Creating summary documents for review and having Claude generate quizzes to ensure the user fully understands the completed changes. The article concludes that as models become more capable, the key to success is systematically discovering and defining these unknowns through low-cost methods like prototyping and planning, allowing for more effective collaboration.

marsbit35 min fa

Claude Engineer Finally Unveils Fable 5's Ultimate Strategy, Teaching You How to Bridge the Information Gap with AI Models

marsbit35 min fa

Trading

Spot

Articoli Popolari

Come comprare T

Benvenuto in HTX.com! Abbiamo reso l'acquisto di Threshold Network Token (T) 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 Threshold Network TokenT.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 Threshold Network Token (T)Dopo aver acquistato Threshold Network Token (T), conserva nel tuo account HTX. In alternativa, puoi inviare tramite trasferimento blockchain o scambiare per altre criptovalute.Step 4: Scambia Threshold Network Token (T)Scambia facilmente Threshold Network Token (T) 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.

438 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 T T sono presentate come di seguito.