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Elon Musk Had 'Hair-Raising' Idea of Passing OpenAI Onto His Kids, Sam Altman Says

WIRED

Elon Musk Had'Hair-Raising' Idea of Passing OpenAI Onto His Kids, Sam Altman Says Musk's lawyers questioned Altman over allegations of deception and his network of financial investments, but the OpenAI CEO painted a picture of Musk as obsessed with controlling the company. Sam Altman took to the witness stand to defend his reputation in the trial on Tuesday, as Elon Musk's lawyers peppered the OpenAI CEO with hours of questions regarding his alleged history of deceptive behavior . The cross examination was a much needed win for Musk, who has so far struggled to make a convincing case. Tuesday's testimony included several heated exchanges in which the OpenAI CEO had to respond to allegations from former colleagues suggesting he's untrustworthy . Highlighting this evidence is not only important for Musk winning over a jury, but also for beating OpenAI in the court of public opinion.


Sam Altman says Elon Musk wanted 90 percent of OpenAI in high-stakes trial

Al Jazeera

In a United States court, OpenAI chief executive Sam Altman has rejected claims from fellow tech mogul Elon Musk that he betrayed the artificial intelligence company's original vision. Tuesday marked the start of Altman's testimony in a contentious trial unfolding in Oakland, California, between some of tech's richest and most powerful titans. He alleged that OpenAI's leader persuaded him to invest $38bn, based on a goal of improving humanity, only to see the company pivot to a for-profit venture in 2019. On the witness stand on Tuesday, Altman instead framed Musk as a competitor obsessed with exercising control over OpenAI. "It does not fit with my conception of the words'stealing a charity' to look at what has actually happened here," Altman told the court.


Ilya Sutskever Stands by His Role in Sam Altman's OpenAI Ouster: 'I Didn't Want It to Be Destroyed'

WIRED

Ilya Sutskever Stands by His Role in Sam Altman's OpenAI Ouster: 'I Didn't Want It to Be Destroyed' The former OpenAI chief scientist may be estranged from the company, but he still came to its defense as he testified on Monday. Elon Musk's trial against OpenAI and Microsoft entered its final stretch on Monday, with testimony from Microsoft CEO Satya Nadella, former OpenAI chief scientist Ilya Sutskever, and current OpenAI chairman Bret Taylor. Sutskever drew the spotlight, revealing an ownership stake in OpenAI's $850-billion for-profit arm that is currently worth about $7 billion. That makes him one of the largest known individual shareholders of OpenAI. Earlier in the trial, OpenAI president Greg Brockman acknowledged for the first time that he has around $30 billion worth of OpenAI shares .


What I saw at the Musk-OpenAI trial: petty billionaires, protests and a stern judge

The Guardian

Showdown between Musk and Altman has rendered the world's most wealthy comical under egalitarian eye of court For the past couple of weeks, on the fourth floor of a courthouse on a quiet street in downtown Oakland, the world's richest man and one of the world's most valuable startups have been at war over the future of artificial intelligence. Being one of the reporters in the room has felt like watching an updated, opposite-coast version of Tom Wolfe's The Bonfire of the Vanities - ambition, ego, greed and the spectrum of social class on full display. The supporting cast has included Elon Musk fanboys, a stern judge and a who's-who of Silicon Valley's most influential people. All courtroom battles are theatre, but this one has proved to be a unique spectacle, with the judge chastising the lawyers for leading the witness, raising meritless objections and even too much coughing. With Musk on the stand, he griped that an opposing attorney had asked a leading question, to which the judge told him to "tell the jury you're not a lawyer".


ICE Agent Who Reportedly Shot Renee Good Was a Firearms Trainer, Per Testimony

WIRED

Jonathan Ross told a federal court in December about his professional background, including "hundreds" of encounters with drivers during enforcement actions, according to testimony obtained by WIRED. Jonathan Ross, the Immigration and Customs Enforcement officer identified by multiple news outlets as the federal agent who shot 37-year-old Renee Good in Minneapolis on Wednesday, is a veteran deportation officer in ICE's Enforcement and Removal Operations division, according to sworn testimony from the federal district court in Minnesota obtained by WIRED. A member of a Special Response Team, ICE's version of a SWAT team, he's had duties as a firearms trainer and led teams drawn from multiple federal agencies including the FBI, Ross testified. The testimony stems from a December 2025 trial related to a June incident with parallels to the interaction that led to Good's killing. In June according to Ross's testimony, he led a team seeking to apprehend a man named Roberto Carlos Muñoz-Guatemala, who was on an administrative warrant for being in the United States without authorization.


TurnaboutLLM: A Deductive Reasoning Benchmark from Detective Games

Yuan, Yuan, He, Muyu, Shahid, Muhammad Adil, Huang, Jiani, Li, Ziyang, Zhang, Li

arXiv.org Artificial Intelligence

This paper introduces TurnaboutLLM, a novel framework and dataset for evaluating the deductive reasoning abilities of Large Language Models (LLMs) by leveraging the interactive gameplay of detective games Ace Attorney and Danganronpa. The framework tasks LLMs with identifying contradictions between testimonies and evidences within long narrative contexts, a challenging task due to the large answer space and diverse reasoning types presented by its questions. We evaluate twelve state-of-the-art LLMs on the dataset, hinting at limitations of popular strategies for enhancing deductive reasoning such as extensive thinking and Chain-of-Thought prompting. The results also suggest varying effects of context size, the number of reasoning step and answer space size on model performance. Overall, TurnaboutLLM presents a substantial challenge for LLMs' deductive reasoning abilities in complex, narrative-rich environments.


Your eyes can reveal the accuracy of your memories

Popular Science

Breakthroughs, discoveries, and DIY tips sent every weekday. We like to think our brains are reliable recorders--but reality says otherwise. From misremembered childhood moments to mistakenly "recalling" that you took your pills when you didn't, false memories are surprisingly common. And in high-stakes situations like courtroom testimony, these errors can have devastating consequences. Wouldn't it be amazing if there were an objective way to measure just how accurate someone's memory really is? New research suggests we might be able to do just that--by watching the eyes.


Parameterized Argumentation-based Reasoning Tasks for Benchmarking Generative Language Models

Steging, Cor, Renooij, Silja, Verheij, Bart

arXiv.org Artificial Intelligence

Generative large language models as tools in the legal domain have the potential to improve the justice system. However, the reasoning behavior of current generative models is brittle and poorly understood, hence cannot be responsibly applied in the domains of law and evidence. In this paper, we introduce an approach for creating benchmarks that can be used to evaluate the reasoning capabilities of generative language models. These benchmarks are dynamically varied, scalable in their complexity, and have formally unambiguous interpretations. In this study, we illustrate the approach on the basis of witness testimony, focusing on the underlying argument attack structure. We dynamically generate both linear and non-linear argument attack graphs of varying complexity and translate these into reasoning puzzles about witness testimony expressed in natural language. We show that state-of-the-art large language models often fail in these reasoning puzzles, already at low complexity. Obvious mistakes are made by the models, and their inconsistent performance indicates that their reasoning capabilities are brittle. Furthermore, at higher complexity, even state-of-the-art models specifically presented for reasoning capabilities make mistakes. We show the viability of using a parametrized benchmark with varying complexity to evaluate the reasoning capabilities of generative language models. As such, the findings contribute to a better understanding of the limitations of the reasoning capabilities of generative models, which is essential when designing responsible AI systems in the legal domain.


Google pays Samsung an 'enormous' amount of money to pre-install Gemini on phones

Engadget

Google has been paying Samsung tons of cash every month to pre-install the AI app Gemini on its smartphones, according to a report by Bloomberg . This information comes to us as part of a pre-existing antitrust case against Google. Peter Fitzgerald, Google's VP of platforms and device partnerships, testified in federal court that it began paying Samsung for this service back in January. The pair of companies have a contract that's set to run at least two years. Fitzgerald told Judge Amit Metha, who is overseeing the case, that Google provides Samsung with both fixed monthly payments and a percentage of revenue earned from advertisers within the Gemini app.


Titanic's Scottish scapegoat is CLEARED after 113 years: 3D scans confirm First Officer William Murdoch did NOT abandon his post as the ship sank

Daily Mail - Science & tech

It has been 113 years since the Titanic sank beneath the waves, claiming the lives of more than 1,500 passengers and crew. But new evidence has finally cleared the tragedy's Scottish scapegoat: First Officer William Murdoch. For years, Officer Murdoch has been accused of taking bribes, abandoning his post, and was even depicted shooting a passenger in the James Cameron movie. Now, more than a century later, 3D scans show that Officer Murdoch did not flee his position, but died while helping passengers escape until the very end. Deep sea scanning company Magellan has snapped 715,000 photos of the Titanic wreck 12,500 feet beneath the Atlantic.