Do Kwon Can Be Extradited to South Korea, Montenegrin Court Rules: Reports

CoinDeskPolicyPublished on 2024-03-06Last updated on 2024-03-07

Abstract

Kwon had successfully appealed a previous decision by the same court to send him to the U.S.

  • Terra founder Do Kwon can be extradited to South Korea to face criminal charges over the collapse of his crypto enterprise, a Montenegrin court ruled.
  • Kwon was arrested last year while attempting to travel with falsified documents
  • The U.S. and South Korea both requested his extradition, and Montenegrin authorities make the decision on where he goes.

Do Kwon, a co-founder of Terraform Labs, can be extradited to South Korea to face criminal charges concerning the May 2022 collapse of his multibillion-dollar crypto enterprise, a Montenegrin high court has ruled, according to local news reports from Thursday.

The South Korean national successfully appealed an earlier ruling by the same court, which approved his extradition to the U.S. It's likely he will also challenge this latest decision.

Following Terra's collapse, Kwon managed to evade South Korean authorities for some time until he was arrested last year in Montenegro while attempting to travel with faked documents. Kwon was arrested alongside former Terra executive Han Chang-joon, who was extradited to South Korea in February.

Advertisement
Advertisement

Kwon has remained in Montenegro, first serving a four-month sentence for possession of falsified documents and then later until a decision on his extradition is made.

The U.S. and South Korea both requested Kwon's extradition. In the U.S., Kwon faces a securities fraud trial.

Edited by Sheldon Reback.


Related Reads

NVIDIA CPU Advances, China's RISC-V Responds: Semiconductor Deep Dive - Part Four

NVIDIA is set to launch its new Vera AI data center CPU in China as early as August, with high pricing. While this move offers a new option, it highlights China's continued dependence on foreign-controlled Arm architecture. In response, the Chinese semiconductor industry is increasingly turning to RISC-V as a strategic alternative for achieving high-performance computing autonomy. The article explores the concept of the "impossible triangle" in CPU development—balancing prosperity, control, and autonomy—and posits that RISC-V's open-source, modular nature offers a unique path to achieving all three. While RISC-V is already dominant in embedded systems, the focus is now shifting to data centers and AI workloads. China has become a global hotspot for RISC-V development, driven by AI-driven compute demand, supply chain concerns from export controls, cost benefits of open-source, and strong policy support. Multiple Chinese companies have reportedly crossed the key performance threshold of 15 SPECint per GHz, a benchmark for entering the high-performance CPU club. Progress extends beyond single-core benchmarks. Companies are developing complete computing subsystems, including commercial-grade coherent network-on-chip (NoC) technology and server processors with up to 40 cores that strictly adhere to the RVA23 standard to ensure software compatibility. Real-world applications are emerging in areas like video transcoding and edge AI. However, significant challenges remain. The RISC-V ecosystem faces fragmentation, immature toolchains and verification processes, and gaps in single-core performance and energy efficiency compared to mature x86 and Arm architectures. The formidable software moat, epitomized by NVIDIA's CUDA, is a long-term hurdle. In conclusion, while RISC-V cannot immediately replace offerings like NVIDIA's Vera, it represents a viable long-term path for China to develop a self-sufficient, high-performance CPU ecosystem. The journey is acknowledged to be long and arduous, requiring sustained effort to overcome technical and ecosystem challenges.

marsbit2h ago

NVIDIA CPU Advances, China's RISC-V Responds: Semiconductor Deep Dive - Part Four

marsbit2h ago

My Coding Betting Dashboard is Profiting, but Polymarket is Truly Not a Good Place for 'Arbitrage'

The author built a custom monitoring dashboard for Polymarket, a prediction market platform, and tested it with $1,600, achieving over 30% returns. However, the core argument is that Polymarket is not a good venue for traditional arbitrage. The dashboard has two main sections: a "Portfolio Dashboard" for tracking active positions with key metrics like total capital, P&L, and a risk-control module using a tier system (T1, T2, T3), and an "Opportunity Watchlist" for monitoring markets. The article details a critical structural trap in binary markets: a bet with a high perceived probability of success still carries a 100% loss risk if wrong. The author's T1/T2/T3 system is designed to manage this by limiting position sizes based on conviction and time horizon, emphasizing that high confidence should not equal high concentration. A key insight is the danger of "pseudo-diversification"—betting on different markets driven by the same underlying variable. The author concludes that Polymarket offers few true low-risk, arbitrage opportunities. It is instead a high-risk environment where wins can create a false sense of mastery, leading to large losses. The platform is better viewed as a training ground for honing judgment through disciplined, framework-driven betting rather than a reliable income source. The tools help transform intuition into structured, rule-based decisions to mitigate the risk of catastrophic errors.

marsbit5h ago

My Coding Betting Dashboard is Profiting, but Polymarket is Truly Not a Good Place for 'Arbitrage'

marsbit5h ago

WeChat AI Card Hands-On Guide: Has the AI Shopping Era Arrived?

**"WeChat AI Card" Practical Test Guide: Has the Era of AI Shopping Arrived?** WeChat has officially launched the "AI Exclusive Card," a feature integrated into its Workbuddy AI assistant. This card is designed to handle payments for AI-initiated purchases. Our hands-on test reveals it's not yet a tool for fully autonomous AI shopping, but rather a controlled payment layer for AI agents. The AI Card functions as an isolated sub-wallet within WeChat Pay. Users must bind the card and transfer funds into it from their main wallet. Crucially, every transaction requires explicit user confirmation via smartphone scan; AI cannot spend autonomously. Currently accessible through the Workbuddy agent, the card targets specific digital consumption scenarios: purchasing paid content (reports, data), calling paid APIs/tools, and subscribing to services. Its design prioritizes security and control by separating funds and mandating approval for each payment. We tested a real-world scenario: ordering bubble tea via Workbuddy using a "Meituan Life Assistant" skill. The process encountered multiple hurdles: high "skill" usage costs (exceeding daily free credits), and most importantly, while a payment was successfully initiated, the AI purchased an incorrect product (a mismatched group-buy coupon instead of the desired drink). This highlights the current limitation: the **AI Card only solves the payment step**. The broader challenge lies in the **AI agent's execution chain**—accurately understanding intent, navigating third-party platforms, selecting the right product, and ensuring proper fulfillment. The payment succeeded, but the purchase failed to meet the user's need. In conclusion, the WeChat AI Exclusive Card is a cautious, early-step experiment in AI commerce. It provides a secure, user-controlled payment method for agent interactions but is not yet capable of reliable, end-to-end complex purchases. For now, it's best used for low-value, low-risk digital services with careful user verification at each step. The vision of AI handling complete shopping tasks remains a work in progress.

marsbit8h ago

WeChat AI Card Hands-On Guide: Has the AI Shopping Era Arrived?

marsbit8h ago

Trading

Spot
Futures
活动图片