This material may not be published, broadcast, rewritten, or redistributed. Quotes displayed in real-time or delayed by at least 15 minutes. Market data provided by Factset . Powered and implemented by FactSet Digital Solutions . Mutual Fund and ETF data provided by LSEG . Timeline: NBC host Savannah Guthrie's mother disappears as sheriff says'everybody's still a suspect' Arizona family sues hospital, says staff'Ubered' sick son to sidewalk where he died Medical examiner determines Texas A&M student's manner of death as family attorney disputes finding: 'Flawed' Dramatic bodycam video captures deputy pulling woman from fiery car wreck: 'I got to her just in time' NJ tech boss convicted of quadruple murder in 2018 killing of brother's family Genealogy company exec slams Pima sheriff's'devastating' move to ship Nancy Guthrie evidence to Florida lab Walmart sales records become critical evidence as FBI investigates Nancy Guthrie's disappearance Feds double Nancy Guthrie reward as former FBI agents suggest they're seeking an insider tip Savannah Guthrie's mother abducted from upscale neighborhood as Tucson crime'spins out of control' SWAT was prepared for possibly'very dangerous' situation in Guthrie case, expert says A man is detained near Nancy Guthrie's house Second Pima County SWAT vehicle seen leaving scene of law enforcement operation in Tucson, Ariz.

For all the ways that AI might have transformed the world, I doubt many people expected flirty serial killer chatbots to be part of it. Yet on the seedier corners of the internet, there are scores of AIs built specifically to give some most vicious killers in history a romantic twist. To see just how dark these bots could be, I decided to step up for a spot of serial killer speed dating. I went on six'dates' with some of history's most notorious murderers and, perhaps unsurprisingly, it didn't go great. Character.ai is the subject of a lawsuit alleging that its bots drove a 14-year-old boy to take his life and has been used to host ghoulish replicas of murder victims such as Brianna Ghey. Across my six dates on the site, I found myself threatened with violence, stalked, invited to remote locations, and generally met with some extraordinarily uncomfortable flirting.

Finetuning language agents with reasoning-action trajectories is effective, but obtaining these trajectories from human annotations or stronger models is costly and sometimes impractical. In this paper, we investigate the use of self-training in language agents, which can generate supervision from the agent itself, offering a promising alternative without relying on human or stronger model demonstrations. Self-training, however, requires high-quality model-generated samples, which are hard to obtain for challenging language agent tasks. To address this, we present Reflection-Reinforced Self-Training (Re-ReST), which uses a \textit{reflector} to refine low-quality generated samples during self-training. The reflector takes the agent's output and feedback from an external environment (e.g., unit test results in code generation) to produce improved samples. This technique enhances the quality of inferior samples and efficiently enriches the self-training dataset with higher-quality samples. We conduct extensive experiments on open-source language agents across tasks, including multi-hop question answering, sequential decision-making, code generation, visual question answering, and text-to-image generation. The results demonstrate the effectiveness of self-training and Re-ReST in language agent tasks, with self-training improving baselines by 7.6\% on HotpotQA and 28.4\% on AlfWorld, and Re-ReST further boosting performance by 2.0\% and 14.1\%, respectively. Our studies also confirm the efficiency of using a reflector to generate high-quality samples for self-training. Moreover, we demonstrate a method to employ reflection during inference without ground-truth feedback, addressing the limitation of previous reflection work. Our code is released at https://github.com/PlusLabNLP/Re-ReST.

Scientists have identified the five key personality traits that are common among famous psychopaths, including serial killer Ted Bundy, disgraced fraudster Bernie Madoff and robber Clyde Barrow. The US academics looked for shared traits in six men - Ted Bundy, Bernie Madoff, Clyde Barrow, James Bond, Sherlock Holmes and Chuck Yeager - who have previously been identified as psychopathic. They found that Bundy, Madoff and Barrow are all psychopaths guilty of callousness, manipulativeness, dishonesty, arrogance and cruelty. However, Bond, Holmes and Yeager likely are not psychopaths, and may have been misidentifed in the past due to their fearlessness and boldness, the experts say. Clyde Barrow (1910-1934): Along with Bonnie Parker, Clyde Barrow went on almost two-year crime spree that spanned several US states.