From a Trillion-Dollar Empire to Prison Appeals: A 35-Page Document Attempts to Rewrite the Ending

比推Опубликовано 2026-02-11Обновлено 2026-02-11

Введение

Sam Bankman-Fried (SBF), the imprisoned founder of FTX, has filed a 35-page pro se motion seeking to overturn his 2023 fraud conviction and 25-year sentence. Submitted through his mother, Stanford law professor Barbara H. Fried, the motion cites newly discovered evidence and alleges multiple judicial and prosecutorial misconducts. Key claims include: the prosecution allegedly threatened witnesses like Ryan Salame to prevent exculpatory testimony and coerced former FTX engineering head Nishad Singh into changing his statements. SBF also presents a sworn declaration from former FTX data head Daniel Chapsky, arguing that prosecutors misrepresented Alameda Research’s account balances to fabricate a shortfall. Additionally, SBF accuses Sullivan & Cromwell, the law firm handling FTX’s bankruptcy, of undervaluing assets to support the narrative of insolvency—contrary to the eventual 119-143% customer recovery rate. He further suggests political targeting by the Biden administration and requests Judge Lewis A. Kaplan to recuse himself due to perceived bias. Legal experts view the motion as a long shot, as most claims rely on evidence that may not meet the “newly discovered” standard, and challenging judicial bias is rarely successful.

Written by: Sanqing, Foresight News

Original title: Former Titan Refuses to Accept Fate, SBF Files 35-Page Motion from Prison Alleging "Conspiracy" in Trial


On February 10, according to a report by Inner City Press, FTX founder Sam Bankman-Fried (SBF), currently serving his sentence at Terminal Island prison in California, is actively seeking to overturn his conviction. A pro se (self-represented) motion for a new trial, submitted on his behalf by his mother, Stanford Law School Professor Barbara H. Fried, has been formally filed with the court. This 35-page document cites Federal Rule of Criminal Procedure Rule 33 and newly discovered evidence, strongly demanding the reversal of his 2023 fraud conviction and the 25-year prison sentence imposed in 2024.

The motion's key arguments include: the absence of crucial witnesses (such as former Alameda Research co-CEO Ryan Salame and former FTX.US executive Daniel Chapsky) led to serious flaws in the trial; prosecutors allegedly concealed evidence; and the entire process was influenced by political factors, with SBF subtly suggesting he was a victim of "targeted prosecution" by the Biden administration.

The evidence and arguments submitted by SBF this time are not aimed at directly proving his "innocence" but rather adopt a legal strategy questioning the procedural loopholes in the judicial process.

Core Allegation One: "Customized" Witnesses and Judicial Coercion

The motion alleges that the prosecution, through threats and inducements, turned his inner circle against him and "silenced" witnesses favorable to his defense.

For example, the absence of former Alameda Research co-CEO Ryan Salame. The motion cites Salame's public statements after August 2024 (including an interview with Tucker Carlson) as newly discovered evidence, revealing that prosecutors threatened to prosecute Salame's partner, Michelle Bond, to prevent Salame from testifying to SBF's innocence.

Regarding former engineering director Nishad Singh, who testified against SBF, the motion discloses that during pre-trial interviews, when Singh's initial statements did not meet the prosecution's expectations, a prosecutor angrily "slammed the table," reprimanding Singh for his "unreliable" memory.

SBF believes that this high-pressure intimidation forced Singh to subsequently change his testimony. The motion formally requests the court to order the prosecution to hand over the relevant interview notes to prove this coercion was concealed.

Core Allegation Two: The Vanishing "Liabilities" and the Mystery of [email protected]

SBF submitted a sworn declaration from former FTX Head of Data Science Daniel Chapsky, countering the misappropriation allegations from a data perspective.

The motion points out that the prosecution had presented the huge negative balance in the [email protected] account as ironclad evidence of SBF's misappropriation of customer funds. However, Chapsky refutes this in his declaration, calling the prosecution's interpretation a "fundamental misrepresentation."

He stated that the negative balance in this account corresponded to cash and assets held offline by Alameda. The prosecution only showed the "debit" negative numbers to the jury but deliberately omitted the corresponding "credit" assets, thus fabricating a false impression of a multi-billion dollar shortfall.

Chapsky's data analysis further shows that if correctly accounted for during most of 2022, Alameda's account on FTX actually maintained a positive balance of approximately $2 billion. The prosecution and expert witness Peter Easton deliberately only displayed certain specific sub-accounts with negative balances, misleading the jury.

Core Allegation Three: Bankruptcy Law Firm S&C's "Asset Erasure Technique"

SBF also targeted the law firm Sullivan & Cromwell (S&C), responsible for FTX's bankruptcy restructuring. He accuses S&C of artificially creating "insolvency" to align with the prosecution's conviction narrative and to earn exorbitant legal fees.

The motion states that FTX held a venture portfolio valued at up to $8.4 billion at the time of bankruptcy (including investments in Claude AI developer Anthropic). However, in the early stages of bankruptcy, S&C and the prosecution, to solidify the funding gap, artificially recorded these less liquid but highly valuable assets at zero or extremely low values.

SBF emphasizes that the bankruptcy team's eventual confirmation that customers will receive 119% to 143% cash recovery itself proves that his assertion during the trial—"FTX was solvent, the money wasn't lost"—was true.

Core Allegation Four: Political Targeting and Judicial Bias

Finally, SBF played the political and procedural cards. He implied he was a victim of a "political war" by the Biden administration. As a former major Democratic donor, he was quickly distanced from and harshly sentenced after his downfall to quell public anger.

Furthermore, given that presiding Judge Lewis A. Kaplan repeatedly rejected defense evidence regarding "FTX's solvency" during the previous trial, SBF's motion not only demands a new trial but also explicitly requests Judge Kaplan to recuse himself, citing the judge's demonstrated extreme bias and inability to adjudicate the case fairly.

Is This Breakout Attempt Doomed to Be a Last Stand?

A Rule 33 motion requires the evidence to be "newly discovered" after the trial, which the defense could not have obtained through "due diligence" during the trial. The judge will likely rule that Salame and Chapsky were known potential witnesses during the trial, and the defense's failure to call them was a strategic choice or an objective difficulty, not "new evidence."

Moreover, FTX's high recovery rate (even exceeding 100%) does not conversely prove that SBF did not misappropriate customer funds at the time. The crime is established upon the unauthorized use of customer funds (regardless of intent), and subsequent asset appreciation is typically considered irrelevant to legal guilt, potentially affecting only sentencing.

Regarding the coercion allegations, unless there is conclusive audio or written evidence proving direct prosecutorial coercion (such as a specific recording of "table slamming"), judges generally tend to accept the prosecution's explanations of procedural compliance.

Additionally, successfully requesting a senior federal judge to recuse themselves for "bias" is extremely rare in judicial practice, unless there is very clear evidence of a conflict of interest. Otherwise, such accusations might further anger the judicial system and be seen as contempt of court.


Twitter:https://twitter.com/BitpushNewsCN

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

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

Original article link:https://www.bitpush.news/articles/7611087

Связанные с этим вопросы

QWhat is the main legal strategy Sam Bankman-Fried (SBF) is using in his motion for a new trial?

ASBF is not directly attempting to prove his innocence but is instead challenging the legal process by alleging procedural flaws in his trial, including the absence of key witnesses, prosecutorial misconduct in withholding evidence, and political influence.

QAccording to the motion, why was key witness Ryan Salame absent from SBF's trial?

AThe motion alleges that prosecutors threatened to indict Ryan Salame's partner, Michelle Bond, to prevent Salame from testifying in SBF's defense, which they claim would have supported SBF's innocence.

QHow does the motion challenge the prosecution's evidence regarding the [email protected] account's negative balance?

AThe motion includes a sworn statement from former FTX data science head Daniel Chapsky, who argues the prosecution's portrayal was a 'fundamental misrepresentation.' He claims the negative balance corresponded to cash and assets Alameda held off-chain and that Alameda's account actually maintained a positive balance of approximately $2 billion when correctly accounted for.

QWhat role does SBF's motion allege the law firm Sullivan & Cromwell (S&C) played in his conviction?

ASBF alleges that the bankruptcy law firm S&C, to support the prosecution's case and earn massive legal fees, artificially created the appearance of insolvency by initially valuing FTX's vast venture portfolio (worth billions) at zero or a very low value, despite the assets later proving sufficient for over 100% customer repayment.

QWhat two significant requests does SBF make regarding the judge who presided over his trial, Lewis A. Kaplan?

ASBF's motion requests a new trial and also formally asks for Judge Lewis A. Kaplan to recuse himself from the case, citing the judge's alleged extreme bias and inability to rule fairly due to his previous rejections of defense evidence concerning FTX's solvency.

Похожее

To C, To B, and the Next Big Thing Called To A

After To C and To B, the Next Wave is To A: Serving AI Agents In a recent quarterly earnings call, Meituan's Wang Xing introduced a new concept: To A (To Agent), signifying that future business services will increasingly target AI Agents as primary clients, not just consumers or merchants. This shift implies that internet giants must now consider how to make their services more appealing for AI Agents to recommend, fundamentally altering traditional distribution logic. This "To A era" is prompting an unusual trend of alliances among major tech companies. Unlike previous competitive battles, firms like Meituan, Tencent, JD.com, Huawei, OPPO, and OpenAI are rapidly forming partnerships. The reason is strategic: as AI Agents become the primary user interface, handling tasks from a single command (e.g., "Book a Japanese restaurant for tomorrow"), the risk for platforms is being bypassed entirely. Companies are positioning themselves within this new value chain. Three primary strategies are emerging: 1. **Super-Entry Points + Service Providers:** Platforms like Tencent's Yuanbao, WeChat, and ChatGPT aim to be the first-stop Agent, integrating various services (food delivery, shopping, travel) from partners like Meituan and JD.com. 2. **Apps as Callable Services:** Companies like Meituan, JD.com, and Uber are ensuring their core services remain accessible and callable by external Agents, shifting from front-end apps to back-end capabilities. 3. **System-Level Agent Entry Points:** Smartphone makers (Huawei, Honor, OPPO) are leveraging their OS-level AI assistants to control the initial user command, redistributing it to relevant service apps. While alliances offer mutual benefit—entry points gain service capabilities, and service providers gain traffic—inherent conflicts of interest exist. A dominant Agent platform could eventually attempt to connect directly with suppliers (restaurants, hotels), bypassing current aggregators like Meituan or Ctrip. Other unresolved challenges include the potential for Agent recommendations to become a new form of paid ranking and unclear accountability for faulty recommendations. The current rush to form alliances is a defensive move by service providers to secure their position before the landscape solidifies. In this To A-driven restructuring, the greatest risk is not losing the race but failing to hear the starting gun.

marsbit5 мин. назад

To C, To B, and the Next Big Thing Called To A

marsbit5 мин. назад

The More Lifelike the Robot, the More Terrifying? Unveiling the 'Uncanny Valley Effect' in the Era of Humanoid Robots

As humanoid robots become increasingly lifelike, they confront a significant psychological barrier known as the "Uncanny Valley Effect," a concept proposed by Japanese roboticist Masahiro Mori in 1970. This phenomenon describes a dip in human comfort and acceptance when robots appear almost, but not perfectly, human. Minor imperfections in facial expressions, eye movements, or skin texture trigger a subconscious sense of unease, as the brain detects something trying, yet failing, to mimic a person. Examples range from the controversial human-like robot Sophia to animated characters in films like *The Polar Express*. The effect poses a key design challenge for robotics companies. Some, like Boston Dynamics, avoid it entirely by creating highly capable but visibly mechanical robots. Others, like Hanson Robotics, push for greater human likeness despite the risk. For consumer robots, especially in homes, most manufacturers opt for stylized or clearly mechanical designs to ensure broader acceptance. While the Uncanny Valley remains a powerful force, its impact may diminish over time through technological advancements that achieve near-perfect realism or through generational familiarity as people grow accustomed to interacting with humanoid machines. Ultimately, navigating this psychological frontier requires as much understanding of human perception as of robotics technology itself.

marsbit6 мин. назад

The More Lifelike the Robot, the More Terrifying? Unveiling the 'Uncanny Valley Effect' in the Era of Humanoid Robots

marsbit6 мин. назад

WeChat Agent Issues a 'Heroic Summons,' Half of the Internet Responds

WeChat AI Agent is on the horizon. The WeChat Open Platform has issued a guide for developers, offering them ways to integrate into the WeChat AI ecosystem. This will enable mini-programs to be discovered and invoked by the AI. Meituan has already announced its integration, allowing users to access services like food delivery through WeChat AI. Other platforms like Ctrip and Tongcheng have followed suit. Furthermore, WeChat is collaborating with major smartphone manufacturers to enable their native AI assistants to perform actions within WeChat, such as initiating calls or sending messages, through a controlled protocol called Agent-to-Agent (A2A). Reports indicate the WeChat AI Agent will be accessible by swiping right on the main interface. It aims to understand user intent within the rich context of chats, groups, and past interactions, then automatically call upon relevant mini-programs to complete tasks like ordering coffee or booking restaurants. This positions it as a potential "super app" with direct access to WeChat's vast ecosystem of services, social connections, and payment systems. Technically, this is a complex endeavor. It requires advanced natural language understanding, a "world model" to predict interactions within mini-programs (UI-Oceanus), multi-model orchestration for cost efficiency, and careful coordination with millions of third-party service providers. Tencent's development follows a "Co-Design" approach, where product teams and the Hunyuan model team collaborate closely, allowing capabilities honed in other AI products (like Yuanbao for chat, ima for search, WorkBuddy for office tasks) to be transferred to the WeChat Agent. Tencent is strategically opting for the A2A protocol over GUI-based automation (which it has blocked in the past), maintaining control over its ecosystem. To manage the immense scale and cost of serving 1.4 billion monthly active users, Tencent is deepening its ties with DeepSeek, known for its cost-effective training, to secure a low-cost inference backbone. The ultimate goal is to solve practical, everyday problems for users within the WeChat ecosystem, moving beyond technical benchmarks to deliver real utility, which Tencent sees as the key to winning in the long-term AI game.

marsbit1 ч. назад

WeChat Agent Issues a 'Heroic Summons,' Half of the Internet Responds

marsbit1 ч. назад

Торговля

Спот
Фьючерсы
活动图片