Hundreds of people had gathered to hear right-wing activist Charlie Kirk speak at the Utah Valley University on Wednesday. The conservative activist and influential Trump ally was shot and killed while speaking. BBC Verify has been piecing together a timeline of how the incident unfolded. 'I would feel more worried' - Chicagoans on Trump's plan to deploy troops President Donald Trump says he will send the National Guard to Chicago to help fight crime but has not specified when that could occur. Officers in Michigan were responding to reports of a stolen vehicle, when they deployed a grappler device around one of the car's tires.

A concert is raging underneath the sea ice. But will we drown it out? Breakthroughs, discoveries, and DIY tips sent every weekday. Earth's oceans have always been a wild world of sound . A symphony of chatter between creatures, rain hitting the surface, the boom of calving ice, the thunders of waves and fizz of bubbles, the rumble of undersea earthquakes, and even mysterious quacking sounds .

AI models are trained on vast swathes of data from every corner of the internet, by humans. AI models are trained on vast swathes of data from every corner of the internet, by humans. How thousands of'overworked, underpaid' humans train Google's AI to seem smart In the spring of 2024, when Rachael Sawyer, a technical writer from Texas, received a LinkedIn message from a recruiter hiring for a vague title of writing analyst, she assumed it would be similar to her previous gigs of content creation. On her first day a week later, however, her expectations went bust. Instead of writing words herself, Sawyer's job was to rate and moderate the content created by artificial intelligence. The job initially involved a mix of parsing through meeting notes and chats summarized by Google's Gemini, and, in some cases, reviewing short films made by the AI.

Larry Ellison, the co-founder of software company Oracle, is having a good year. His friend Donald Trump is in the White House, his son David Ellison has taken over the storied media company CBS, and on Wednesday he surpassed his buddy Elon Musk to win the title of the "world's richest man". Oracle's stock went wild with the news, pushing his fortune even higher. Ellison's net worth shot up to $393bn, surpassing Musk's $384bn - although, by the time markets closed on Wednesday, Musk was back ahead. Ellison is not as much of a household name as Musk, but he's largely influential in Silicon Valley and more recently, politics.

FBI under pressure over open airport five miles from Charlie Kirk assassination hit as private jet'vanishes' after shooting MSNBC analyst Matthew Dowd fired over'disgusting' on-air comments about Charlie Kirk shortly after conservative star was assassinated Elite sniper breaks down Charlie Kirk assassin's sick plot... and reveals tiny detail everyone's missed: The gun. MAUREEN CALLAHAN: Charlie Kirk's body wasn't even cold... before the fighting started again. Do these ghouls not see where this is headed? Charlie Kirk's powerful tribute to murdered Ukrainian refugee hours before his own assassination: 'America will never be the same' Musk dethroned as richest person by forgotten Wall Street darling's founder as stock soars 42% Charlie Kirk dead at 31: What we know so far about MAGA star's death at Utah campus that sent shockwaves around the world as FBI botches arrest and Trump promises ultimate punishment TMZ forced to apologize after staff heard erupting in laughter as Charlie Kirk's death was announced Sweater weather starts here - the cozy, chic pieces from Soft Surroundings you'll actually wear all season Trump issues Oval Office address over Charlie Kirk's assassination: 'This is a dark moment for America' Fierce debate erupts over'non-human' technology in space after video captures UFO surviving Hellfire strike Is this Charlie Kirk's killer? This Oscar-nominated actress, 68, will soon reunite with her ex in Spain for their daughter's wedding, can you guess who?

A legal battle is brewing, as two companies are suing to overturn the two-year ban. Last week, a legal battle over lab-grown meat kicked off in Texas. On September 1, a two-year ban on the technology went into effect across the state; the following day, two companies filed a lawsuit against state officials. The two companies, Wildtype Foods and Upside Foods, are part of a growing industry that aims to bring new types of food to people's plates. These products, often called cultivated meat by the industry, take live animal cells and grow them in the lab to make food products without the need to slaughter animals. Here's what we know about lab-grown meat and climate change Cultivated meat is coming to the US.

'Traumatising for everyone': Witnesses describe Charlie Kirk shooting scene Conservative activist Charlie Kirk has died after being shot while speaking to a crowd of hundreds on the campus of Utah Valley University on Wednesday. Witnesses describe what happened on the scene before and after a single shot rang out. 'I would feel more worried' - Chicagoans on Trump's plan to deploy troops President Donald Trump says he will send the National Guard to Chicago to help fight crime but has not specified when that could occur. Officers in Michigan were responding to reports of a stolen vehicle, when they deployed a grappler device around one of the car's tires. In response to a reporter's question, the president said he was'very active' over the Labor Day weekend.

Ensuring equitable treatment (fairness) across protected attributes (such as gender or ethnicity) is a critical issue in machine learning. Most existing literature focuses on binary classification, but achieving fairness in regression tasks-such as insurance pricing or hiring score assessments-is equally important. Moreover, anti-discrimination laws also apply to continuous attributes, such as age, for which many existing methods are not applicable. In practice, multiple protected attributes can exist simultaneously; however, methods targeting fairness across several attributes often overlook so-called "fairness gerrymandering", thereby ignoring disparities among intersectional subgroups (e.g., African-American women or Hispanic men). In this paper, we propose a distance covariance regularisation framework that mitigates the association between model predictions and protected attributes, in line with the fairness definition of demographic parity, and that captures both linear and nonlinear dependencies. To enhance applicability in the presence of multiple protected attributes, we extend our framework by incorporating two multivariate dependence measures based on distance covariance: the previously proposed joint distance covariance (JdCov) and our novel concatenated distance covariance (CCdCov), which effectively address fairness gerrymandering in both regression and classification tasks involving protected attributes of various types. We discuss and illustrate how to calibrate regularisation strength, including a method based on Jensen-Shannon divergence, which quantifies dissimilarities in prediction distributions across groups. We apply our framework to the COMPAS recidivism dataset and a large motor insurance claims dataset.

Human Activity Recognition (HAR) has seen significant advancements with the adoption of deep learning techniques, yet challenges remain in terms of data requirements, reliability and robustness. This paper explores a novel application of Ensemble Distribution Distillation (EDD) within a self-supervised learning framework for HAR aimed at overcoming these challenges. By leveraging unlabeled data and a partially supervised training strategy, our approach yields an increase in predictive accuracy, robust estimates of uncertainty, and substantial increases in robustness against adversarial perturbation; thereby significantly improving reliability in real-world scenarios without increasing computational complexity at inference. We demonstrate this with an evaluation on several publicly available datasets. The contributions of this work include the development of a self-supervised EDD framework, an innovative data augmentation technique designed for HAR, and empirical validation of the proposed method's effectiveness in increasing robustness and reliability.

Bio-inspired design is often used in autonomous UAV navigation due to the capacity of biological systems for flight and obstacle avoidance despite limited sensory and computational capabilities. In particular, honeybees mainly use the sensory input of optic flow, the apparent motion of objects in their visual field, to navigate cluttered environments. In our work, we train a Reinforcement Learning agent to navigate a tunnel with obstacles using only optic flow as sensory input. We inspect the attention patterns of trained agents to determine the regions of optic flow on which they primarily base their motor decisions. We find that agents trained in this way pay most attention to regions of discontinuity in optic flow, as well as regions with large optic flow magnitude. The trained agents appear to navigate a cluttered tunnel by avoiding the obstacles that produce large optic flow, while maintaining a centered position in their environment, which resembles the behavior seen in flying insects. This pattern persists across independently trained agents, which suggests that this could be a good strategy for developing a simple explicit control law for physical UAVs.