CoinDeskPolicyPubblicato 2024-04-09Pubblicato ultima volta 2024-04-10

Introduzione

Steven Nerayoff has retained well-known civil liberties lawyer Alan Dershowitz to serve as a consultant on constitutional issues in the case.

  • Steven Nerayoff, a former adviser to the Ethereum network, is seeking $9.6 billion in damages from the U.S. government stemming from a 2019 case against him that was later dropped.
  • Lawyers for Nerayoff allege their client was framed by the FBI and federal prosecutors in order to get him to turn over evidence on high-profile people in the crypto industry.
13.6K
Kraken Co-Founder Jesse Powell Faces Probe on Claims of Hacking, Cyberstalking Non-Profit

Steven Nerayoff, an early adviser to the Ethereum network, has filed a notice of his intent to sue the U.S. government for $9.6 billion in damages connected to his 2019 arrest on criminal extortion charges, which his lawyers called “fabricated” and “baseless.”

Nerayoff’s Federal Tort Claims Act (FTCA) form, which was provided to CoinDesk by his lawyers, is the first step towards filing a lawsuit against the Department of Justice (DOJ). In FTCA cases, the agencies involved must be notified of the claimant’s intention to sue at least six months before a lawsuit is formally filed.

Well-known civil liberties lawyer Alan Dershowitz confirmed Wednesday that he will serve as a consultant on constitutional issues for Nerayoff’s case.

Advertisement
Advertisement

The government’s charges against Nerayoff were dropped in May 2023. Two months earlier, prosecutors moved to end the case, admitting that they had obtained material exculpatory evidence and were unable to prove the charges in the indictment beyond a reasonable doubt. Nerayoff’s lawyers had, before that, filed a motion to dismiss that was chock-full of explosive claims against the federal investigators and prosecutors involved in the case.

Nerayoff and his lawyers say that he was the victim of an elaborate, years-long setup by the Federal Bureau of Investigation (FBI) with the ultimate intention of getting him to turn over evidence on important figures in the crypto industry.

The FBI did not respond to CoinDesk’s request for comment by the time of publication.

On the morning of Sept. 17, 2019, Nerayoff claims he was arrested by a dozen gun-wielding FBI agents and interrogated for “hours” in an unmarked van parked outside his home. According to Nerayoff, the agents told him he would “not see his young minor children grow old” unless he cooperated by giving them information.

The government denied the majority of Nerayoff’s claims in a filing of its own, including the assertion that Nerayoff’s colleague and former co-defendant on the extortion charges, Michael Hlady, was a government informant. Nerayoff’s lawyers maintain that Hlady, who was convicted of swindling Catholic nuns out of nearly $400,000 in 2010, was “insinuated … into [his] orbit” by the FBI, in order to help them build a case against Nerayoff.

Advertisement
Advertisement

In 2021, Hlady pleaded guilty to the extortion charges Nerayoff was also tied up in. But last month, the government moved to drop the charges against him and allow him to withdraw his guilty plea, instead having him plead guilty to one count of wire fraud in an unrelated fraud scheme he committed while out on bond.

Edited by Nikhilesh De and Nick Baker.

Letture associate

A Company Once on the Brink of Bankruptcy Just Surpassed Bitcoin in Market Cap

On June 22nd, driven by rising stock prices, SK Hynix’s market capitalization reached $1.35 trillion, surpassing Bitcoin's total market cap of approximately $1.29 trillion. This temporarily made it South Korea's highest-valued company. The core driver of this surge is HBM (High Bandwidth Memory), for which SK Hynix is the primary supplier to NVIDIA, holding over 60% market share. AI's demand for high memory bandwidth has translated into immense profitability, with SK Hynix reporting a 72% operating profit margin in Q1. The company's success follows a 13-year bet on HBM technology, beginning in 2009. It nearly failed after the 2001 dot-com bubble, was acquired by SK Group in 2012, and was subsequently recapitalized to continue its long-term HBM development. The article contrasts this with the Crypto AI narrative. Capital currently favors AI infrastructure players like SK Hynix due to "real orders, physical barriers, and quantifiable profit margins." In comparison, Crypto AI projects, promising decentralized compute and data markets, remain largely conceptual with limited tangible progress. Examples include Bittensor, whose core mechanisms are still under development, and Bitcoin miners transitioning to AI, who face significant funding gaps and execution challenges. The piece cites analysis suggesting the AI sector has absorbed nearly all new market liquidity since 2022, leaving little for crypto. It concludes that the current AI infrastructure红利 is captured by entities with proven technical barriers and supply capabilities, while crypto networks still need to define their concrete role in the value chain.

链捕手38 min fa

A Company Once on the Brink of Bankruptcy Just Surpassed Bitcoin in Market Cap

链捕手38 min fa

Bittensor Moves Towards Ultimate Decentralization: The Critical 18 Months for the TAO Ecosystem is Here?

Bittensor, a decentralized AI protocol, is accelerating its transition to full decentralization over the next 18 months, as outlined in a recent post by co-founder Const. The project currently operates in a "semi-decentralized" state: ownership and network participation are open and permissionless, with TAO distribution based on competitive contribution. However, protocol upgrades and governance have remained under core team control to enable rapid iteration in the fast-evolving AI sector. This strategic shift comes as the ecosystem matures, boasting 128 subnets and a large community. Const argues that continued centralization now poses risks, including single points of failure and regulatory scrutiny. The upcoming decentralization roadmap includes optimizing validator competition, opening liquidity pools, introducing governance rights for Alpha holders, and refining economic models. The move could fundamentally reshape TAO's value proposition, adding governance premiums to its existing valuation based on AI narrative and scarcity. It also signals a potential maturation of the AI crypto sector, where competition may shift from hype to sustainable protocol design and real economic activity. Bittensor positions itself not just as another AI token, but as foundational infrastructure aiming to decentralize intelligence production—analogous to Bitcoin's role in decentralizing money—with the goal of creating a resilient "Millennium Intelligence Federation."

marsbit50 min fa

Bittensor Moves Towards Ultimate Decentralization: The Critical 18 Months for the TAO Ecosystem is Here?

marsbit50 min fa

Japan's AI Dark Horse Emerges: How a 7B Small Model Challenges Fable and Mythos?

In June 2026, Sakana AI's new model Fugu caused a stir in the AI community. Its Fugu Ultra variant achieved scores of 73.7 on SWE-Bench Pro and 82.1 on TerminalBench 2.1, surpassing GPT-5.5 and Claude Opus 4.8, and was claimed to be comparable to export-restricted models like Fable 5 and Mythos Preview. Remarkably, the core of this high-performance system is not a massive model, but a small 7B-parameter RL Conductor model. Fugu operates as a multi-agent orchestrator: the 7B model acts as a "foreman," dynamically analyzing user tasks and delegating subtasks to a pool of top-tier global models (e.g., GPT-5, Gemini 3.1 Pro). It then synthesizes and verifies their outputs. This architecture represents a paradigm shift from monolithic models to an expert-team approach. It enhances performance in complex, multi-step engineering tasks like code review and security testing by enabling cross-validation from specialized models, improving long-session stability and token efficiency. However, Fugu's strengths come with trade-offs: it faces inherent latency due to multiple API calls, relies heavily on underlying US model APIs (creating dependency risks), and its benchmark comparisons with Fable/Mythos are based on reported scores, not head-to-head testing. For Japan's AI ecosystem, which lacks the massive compute and data resources of the US or China, Fugu exemplifies an "asymmetric breakthrough" strategy. Instead of competing directly in parameter scale, it focuses on intelligent orchestration of existing global models, offering a degree of AI sovereignty and resilience. While a significant system-level innovation, its ultimate capability is still bounded by the underlying models it coordinates.

marsbit50 min fa

Japan's AI Dark Horse Emerges: How a 7B Small Model Challenges Fable and Mythos?

marsbit50 min fa

Trading

Spot
Futures
活动图片