From Crypto King to Pardon-Seeking Prisoner: SBF's Final Gamble Fails

比推2026-02-25 tarihinde yayınlandı2026-02-25 tarihinde güncellendi

Özet

Sam Bankman-Fried (SBF), the convicted cryptocurrency fraudster and former major Democratic donor, has recently adopted a pro-Trump and MAGA-aligned rhetoric in a series of social media posts from prison, where he is serving a 25-year sentence. He publicly praised Donald Trump and criticized what he called a politically biased judicial system, aiming to seek a presidential pardon. Despite his efforts to align with conservative causes and even appearing on Tucker Carlson’s show, the Trump administration has explicitly stated it has no intention of pardoning SBF. His shift to the right—including attacks on the “deep state” and endorsements of free speech platforms like Truth Social—is seen as a strategic yet futile attempt to gain freedom, given his history as a top Biden donor and his notorious reputation in the crypto industry. SBF continues to appeal his conviction while maintaining an active, proxy-managed presence on X.

Author: Fortune

Compiled by: Felix, PANews

Original Title: "Startled from a dying illness," SBF desperately flatters Trump for pardon but gets rejected

Convicted cryptocurrency fraudster Sam Bankman-Fried (SBF) was once a major donor to the Democratic Party, but his recent public statements have taken on a distinct "MAGA" (Make America Great Again) flavor. In a recent manifesto posted on the X platform, he wrote: "Judge Lewis Kaplan, appointed by Clinton, showed no hesitation in revealing his political bias when sentencing me. I admire President Donald Trump because he dares to stand against this 'biased, out-of-control radical'!"

This is just one of dozens of tweets SBF has posted in recent weeks, filled with attacks on the "Deep State" and other MAGA villains. Despite being one of the most notorious financial criminals of the century, currently serving a 25-year sentence in federal prison, he remains active.

Although SBF has not explicitly stated it, the purpose of his social media frenzy is obvious: to persuade President Donald Trump to free him from prison. Given that Trump has pardoned several high-profile individuals convicted of financial crimes, including SBF's former rival, Binance founder Changpeng Zhao (CZ), this strategy seems logical.

However, for SBF, his plea for Trump's mercy appears futile. In response to recent social media advocacy, a White House spokesperson reiterated to Fortune magazine that Trump has no intention of pardoning SBF.

In an email, the spokesperson referenced Trump's remarks in January of this year, when the president clearly stated that he does not plan to pardon SBF or several other high-profile prisoners, including former New Jersey Senator Robert Menendez and ousted Venezuelan President Nicolás Maduro. The spokesperson wrote: "The president is the final arbiter of all pardon matters."

SBF's lawyers did not respond to this matter.

Failed Attempt

SBF has long been a supporter of progressive causes. His parents are Stanford law professors with considerable influence among top Democrats. But when SBF's fraudulent crypto empire collapsed in November 2022, the founder began planning a shift to the right. During the trial, a private document revealed that SBF planned to appear on conservative TV host Tucker Carlson's show and "come out as a Republican."

On the surface, this strategy seemed reasonable, especially in the current political climate. Trump is set to take office in January 2025 and has promised to roll back the Biden administration's crackdown on cryptocurrencies. Under Trump's leadership, regulators have withdrawn key lawsuits against blockchain companies, and the Department of Justice has shifted its approach to cryptocurrency enforcement.

However, Washington insiders say that SBF's status as a top donor to Biden, combined with his continued notoriety in the crypto industry, makes his pardon plea a long shot. Even his unauthorized appearance on Tucker Carlson's show last year (which reportedly landed him in solitary confinement) failed to turn the tide.

Despite the slim chances, SBF has not given up. He is also appealing his conviction in federal appellate court. His X account is filled with posts promoting his newly adopted conservative identity, which critics have dubbed a "puppet account." (In his bio, SBF clarifies that he conveys content to agents via Bureau of Prisons-approved phones and emails for posting.)

His recent post reads: "Democrats love to censor 'misinformation' on social media," followed by praise for Trump's campaign platform. "Truth Social and GETTR have always prioritized free speech."

Twitter:https://twitter.com/BitpushNewsCN

Bitpush TG Group:https://t.me/BitPushCommunity

Bitpush TG Subscription: https://t.me/bitpush

Original link:https://www.bitpush.news/articles/7614352

İlgili Sorular

QWhat was the main reason SBF (Sam Bankman-Fried) started publicly supporting Donald Trump and MAGA ideology?

ASBF started publicly supporting Donald Trump and the MAGA ideology in an attempt to seek a presidential pardon from Trump, hoping to be released from his 25-year prison sentence for cryptocurrency fraud.

QAccording to the article, what was the White House's response to SBF's attempts to gain a pardon?

AA White House spokesperson stated that President Trump has no intention of pardoning SBF, reiterating Trump's earlier position from January that he would not pardon SBF or other high-profile prisoners.

QHow did SBF's political affiliations change after the collapse of his crypto empire in November 2022?

AAfter the collapse of his crypto empire, SBF began to shift towards the right wing. He planned to appear on conservative commentator Tucker Carlson's show and present himself as a Republican, despite previously being a major donor to the Democratic Party.

QWhat method does SBF use to post on social media while in federal prison?

ASBF posts on social media by relaying content through an agent using a phone and email approved by the Bureau of Prisons, as clarified in his profile.

QBesides his appeal in federal appellate court, what other action is SBF taking to try to overturn his conviction?

ABesides his legal appeal, SBF is actively posting on social media to promote his newly adopted conservative identity and criticize his perceived political enemies, in a continued effort to seek a pardon.

İlgili Okumalar

XRP Ledger v3.3.0 Release Brings Five Amendments Into Focus

The upcoming XRP Ledger v3.3.0 release, scheduled for early August, focuses on five key amendments: Confidential MPT, Batch, Permission Delegation, Sponsored Fees and Reserves, and Dynamic MPT. This bundle aims to enhance the ledger's infrastructure for advanced use cases like tokenized assets and improve operational flexibility and user experience. Notably, Sponsored Fees could reduce onboarding friction by allowing third parties to cover transaction costs, while Confidential and Dynamic MPT features provide more control for institutional asset tokenization. Batch transactions and Permission Delegation add operational efficiency for applications. However, these features do not activate automatically upon release; they require approval from 80% of network validators. The upgrade represents a significant step in XRPL's roadmap for enterprise and developer utility, with practical impact dependent on subsequent validator consensus and builder adoption.

bitcoinist12 dk önce

XRP Ledger v3.3.0 Release Brings Five Amendments Into Focus

bitcoinist12 dk önce

Wall Street Morning News: V-shaped Rebound at Month-end, but Nasdaq Suffers Worst July in 12 Years; Funds Accelerate Concentration Towards Cloud Giants

Despite a V-shaped rebound at the end of July, the Nasdaq posted its worst July since 2004, while the S&P 500 had its worst July since 2014. Markets were jolted by geopolitical shifts, as President Trump canceled a planned strike on Iran, leading WTI crude to plunge over 8%. This, alongside OPEC+ announcing a supply increase, reversed crude's sharp July gains. Treasury yields surged, with the 10-year yield rising over 30 basis points in July—its largest July increase since 2005. In a rare move, the US and Japan jointly intervened to weaken the USD/JPY, aiming to prevent potential Japanese sales of US Treasuries. While the tech sector faced deleveraging pressure throughout July, cloud giants staged a massive rally on strong earnings. Microsoft, Amazon, and Google collectively added nearly $1.5 trillion in market value last week. Amazon soared over 15% on accelerating AWS growth, Microsoft extended historic gains, Google fully recovered post-earnings losses, and Meta ended an 11-day losing streak. In contrast, Apple tumbled over 7% on supply chain and guidance concerns, ceding its "world's most valuable company" title to Nvidia. The memory and storage sector corrected sharply. Gold edged up 0.91% in July, with analysts viewing the ~30% pullback from January highs as a potential basing period, supported by long-term central bank demand. Key events to watch this week include earnings from Palantir, AMD, SpaceX (its first post-IPO report), and memory giants like Western Digital. The US July non-farm payrolls report on Friday will be critical for gauging the Fed's policy path. SpaceX also faces a significant lock-up expiration, testing market liquidity.

marsbit36 dk önce

Wall Street Morning News: V-shaped Rebound at Month-end, but Nasdaq Suffers Worst July in 12 Years; Funds Accelerate Concentration Towards Cloud Giants

marsbit36 dk önce

Rubin Ultra Makes Major Cuts, Even Nvidia Can't Handle Memory Price Hikes?

NVIDIA's Rubin Ultra, the top-tier variant of the newly announced Rubin AI accelerators, has reportedly seen significant specification downgrades, according to an industry report from SemiAnalysis. Initially designed with four compute dies (4-die), the Rubin Ultra is now said to be reduced to a 2-die design. Key changes highlighted in the report include: * **No increase in peak theoretical compute performance**, remaining at 35 PFLOPs like the standard Rubin. * **Severe reduction in memory capacity** to 192GB using 8-Hi HBM stacks, which is less than the standard Rubin's 288GB using 12-Hi stacks. * **Negligible memory bandwidth improvement** of only 1 TB/s. * **Slightly higher chip-level power consumption**. * The **primary upgrade is a massive increase in scale-up interconnect capacity**, supporting connections for up to 576 GPUs via NVLink, compared to 72 for the standard Rubin. The report suggests the redesign is primarily a cost-optimization move driven by the sharp rise in HBM (High-Bandwidth Memory) prices. By reducing the expensive HBM content and shifting investment towards enhanced system-scale networking, NVIDIA aims to maintain the platform's value for large-scale AI training clusters while managing soaring material costs. The news reportedly triggered a sell-off in South Korean memory stocks, with SK Hynix and Samsung shares falling around 8%, as markets grew concerned that NVIDIA—a major HBM buyer—might be reducing its reliance on high-capacity memory, potentially capping future pricing power for memory makers.

Odaily星球日报57 dk önce

Rubin Ultra Makes Major Cuts, Even Nvidia Can't Handle Memory Price Hikes?

Odaily星球日报57 dk önce

Upbit Rebalances 864B SHIB In Internal Wallet Move

South Korean cryptocurrency exchange Upbit moved a total of 864 billion SHIB (worth approximately $4 million) between its internal wallet addresses. The activity, involving transfers of 384 billion SHIB outbound and 480 billion SHIB inbound, occurred following a 36% SHIB price rally. On-chain data indicates this was a routine internal wallet rebalancing operation by the exchange, not a sell-off or liquidation event. The article cautions that while large on-chain transfers are highly visible, they require proper context and wallet labeling to interpret correctly. In this case, the movement between known Upbit addresses does not inherently signal a change in market supply or selling pressure for SHIB.

bitcoinist1 saat önce

Upbit Rebalances 864B SHIB In Internal Wallet Move

bitcoinist1 saat önce

Can Generative Models Finally Be Trained End-to-End? The Core Is a For Loop

This article introduces a novel training paradigm for generative models called Explorative Modeling (XM), which enables true end-to-end training. Traditionally, powerful generative models like autoregressive and diffusion models are not trained end-to-end. They are trained to predict a single small step but require iterative multi-step sampling for inference. This "exposure bias" leads to error accumulation and limits performance. The core challenge XM addresses is "mode blurring." In generative tasks, a single input (e.g., "generate a dog") corresponds to many valid outputs (multiple modes). Standard training objectives like reconstruction loss force the model to average these modes, producing unrealistic, blurry outputs. To avoid this, existing models break generation into many small, almost deterministic steps, sacrificing end-to-end training. XM tackles this by restructuring the training loop itself. Its key insight is to amplify "generative expressivity." For each training input, instead of generating one sample, the model generates K candidate outputs. Only the candidate closest to the real data is used for computing the loss and updating the model via backpropagation. This simple "best-of-K" mechanism is implemented as a short for-loop. By exploring multiple possibilities, the model learns to distribute its guesses across different modes rather than collapsing to their uninformative average. The paper demonstrates that "exploration" acts as a new, powerful scaling axis. Gains from XM increase with model size, data scale, and compute. Experiments show improvements in FID scores for image generation and significant efficiency gains, sometimes outperforming larger models without exploration. When pushed to the limit, XM enables fully single-step, end-to-end generative models. In robotics tasks, an "Explorative Policy" matched the performance of a 100-step Diffusion Policy with a single forward pass, drastically improving inference speed. While the best-of-K concept is not entirely new, the authors' contribution lies in formally understanding it as a direct method to boost generative expressivity without fragmenting the generation process. This work suggests that as models scale, enhancing exploration during training may become crucial for overcoming fundamental performance bottlenecks.

marsbit1 saat önce

Can Generative Models Finally Be Trained End-to-End? The Core Is a For Loop

marsbit1 saat önce

İşlemler

Spot