‘Disappointing’: U.S. DoJ seeks retrial of Tornado Cash founder

ambcrypto2026-03-10 tarihinde yayınlandı2026-03-10 tarihinde güncellendi

Özet

The U.S. Department of Justice is seeking a retrial of Tornado Cash founder Roman Storm on charges of money laundering and sanctions violations, a move that has drawn strong criticism from the crypto community. Storm was previously found guilty only of operating an unlicensed money-transmitting business. The DeFi community, including the DeFi Education Fund and Solana Policy Institute, expressed disappointment, arguing the case threatens legal protections for software developers. They point to a recent court ruling that exempted developers from liability on non-custodial platforms. Critics also accuse the DoJ of contradicting the U.S. Treasury's stance and undermining crypto innovation. Despite the negative news, Tornado Cash’s native token TORN saw a 4% price increase.

U.S. government agencies are eliciting conflicting views on crypto mixers and DeFi software developers.

The above rift has become evident in the latest push by the Department of Justice (DoJ) to retry the Tornado Cash founder, Roman Storm.

In a letter sent to the Southern District of New York’s (SDNY) Judge Katherine Polk Failla, the DoJ requested the retrial to begin in October 2026.

Community opposes DoJ’s push for retrial

However, the DeFi and crypto community has raised concerns about the planned retrial.

In particular, Amanda Tuminelli, chief legal officer and executive director at lobby group DeFi Education Fund, billed the update as ‘incredibly disappointing news.’

Last year, Tornado Cash founder Roman Storm was charged with three counts: conspiracy to operate an unlicensed money-transmitting business (MTB), money laundering, and violations of sanctions.

But he was only found guilty of running an unlicensed MTB, which attracted a five-year jail sentence. However, the jury was undecided on the two other counts, and each could fetch a 20-year sentence if Storm is found guilty. These are the charges the DoJ is seeking to retry.

Moreover, Roman Storm criticized SDNY prosecutors for overstepping their role, undermining President Donald Trump’s crypto agenda, and disregarding the U.S. Treasury’s latest directive.

Here, Storm was referring to the U.S. Treasury’s latest report on crypto mixers, which characterized the products as ‘unlawful.’

“Lawful users of digital assets may leverage mixers to enable financial privacy when transacting through public blockchains.”

DeFi developers’ protections at risk

Similarly, a recent landmark Uniswap ruling established that scammers were liable for any wrongdoing and losses incurred on non-custodial platforms.

The ruling exempted developers from legal liability and, by extension, was viewed by many policy watchers as a positive sign for DeFi. In fact, the Unsiwap ruling was issued by Judge Failla, who is handling the Storm case.

However, the DoJ’s push for a retrial runs counter to the above ruling and the U.S. Treasury statement, further putting DeFi developers’ protection in limbo.

Reacting to the update, Solana Policy Institute’s CEO Miller Whitehouse-Levine called the retrial push ‘depressing’ but vowed to support Storm.

For his part, David Hoffman of Bankless pleaded with the Trump Administration to drop the charges against Storm.

“If the USA wants to be the Crypto Capital of the world, we need to protect our open-source developers. Please simply pardon Roman Storm from a charge leftover from the Biden admin.”

Interestingly, TORN, Tornado Cash’s native token, surged 4% despite the negative update.


Final Summary

  • The DoJ is pushing for the retrial of Roman Storm for sanctions violations and money laundering.
  • The crypto community expressed disappointment with the update as software developers’ protections hang in the balance.

İlgili Sorular

QWhat are the three charges that Tornado Cash founder Roman Storm was originally facing?

ARoman Storm was originally charged with three counts: conspiracy to operate an unlicensed money-transmitting business (MTB), money laundering, and violations of sanctions.

QWhy is the DeFi and crypto community concerned about the Department of Justice's push for a retrial?

AThe community is concerned because the retrial push runs counter to a recent landmark Uniswap ruling that exempted developers from legal liability, putting the protections for DeFi software developers in jeopardy.

QWhat was the outcome of Roman Storm's initial trial, and which charge was he found guilty of?

AIn the initial trial, the jury found Roman Storm guilty of running an unlicensed money-transmitting business (MTB), which carries a five-year jail term. The jury was undecided on the charges of money laundering and sanctions violations.

QHow did the U.S. Treasury's latest report characterize crypto mixers, and what did it say about their lawful users?

AThe U.S. Treasury's latest report characterized crypto mixers as 'unlawful.' However, it also noted that 'Lawful users of digital assets may leverage mixers to enable financial privacy when transacting through public blockchains.'

QWho is the judge presiding over the Roman Storm case, and why is her previous ruling significant in this context?

AJudge Katherine Polk Failla of the Southern District of New York (SDNY) is presiding over the case. She is significant because she issued the recent Uniswap ruling that established developers are not liable for scams on non-custodial platforms, a decision that contrasts with the DoJ's push for a retrial against Storm.

İlgili Okumalar

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbit1 saat önce

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbit1 saat önce

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbit1 saat önce

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbit1 saat önce

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbit1 saat önce

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbit1 saat önce

İşlemler

Spot
活动图片