The Amazon Prime prank series amplifies the hijinks of workplace dynamics, while showing how people find purpose--and community--in their jobs despite impossible situations. Anthony Norman is your typical Gen Z worker: 25, a little wayward, and struggling to find a full time job. Unemployment rates are high . AI is creating a crisis for young people trying to enter the workforce. And several companies--including Amazon, Block, and Meta --have embraced tech's latest era of layoffmaxxing, with some cutting their staff by 20 percent.

Fact-checking is extensively studied in the context of misinformation and disinformation, addressing objective inaccuracies. However, a softer form of misinformation involves responses that are factually correct but lack certain features such as clarity and relevance. This challenge is prevalent in formal Question-Answer (QA) settings such as press conferences in finance, politics, sports, and other domains, where subjective answers can obscure transparency. Despite this, there is a lack of manually annotated datasets for subjective features across multiple dimensions. To address this gap, we introduce SubjECTive-QA, a human annotated dataset on Earnings Call Transcripts' (ECTs) QA sessions as the answers given by company representatives are often open to subjective interpretations and scrutiny. The dataset includes 49,446 annotations for long-form QA pairs across six features: Assertive, Cautious, Optimistic, Specific, Clear, and Relevant. These features are carefully selected to encompass the key attributes that reflect the tone of the answers provided during QA sessions across different domains. Our findings are that the best-performing Pre-trained Language Model (PLM), RoBERTa-base, has similar weighted F1 scores to Llama-3-70b-Chat on features with lower subjectivity, such as Relevant and Clear, with a mean difference of 2.17% in their weighted F1 scores. The models perform significantly better on features with higher subjectivity, such as Specific and Assertive, with a mean difference of 10.01% in their weighted F1 scores.

A famous detail in the Battle of Hastings is based on a major misunderstanding. The Battle of Hastings is famously recounted across the Bayeux Tapestry. Breakthroughs, discoveries, and DIY tips sent six days a week. One of history's most famous military marches has been misunderstood for centuries. According to the prevailing English accounts, King Harold made a momentous, 200-mile march over land to the Battle of Hastings in 1066 CE after dismissing his naval fleet.

Unmanned Aerial Vehicles (UAVs), equipped with cameras, are employed in numerous applications, including aerial photography, surveillance, and agriculture. In these applications, robust object detection and tracking are essential for the effective deployment of UAVs. However, existing benchmarks for UAV applications are mainly designed for traditional 2D perception tasks, restricting thedevelopment of real-world applications that require a 3D understanding of the environment. Furthermore, despite recent advancements in single-UAV perception, limited views of a single UAV platform significantly constrain its perception capabilities over long distances or in occluded areas. To address these challenges, we introduce UAV3D - a benchmark designed to advance research in both 3D andcollaborative 3D perception tasks with UAVs. UAV3D comprises 1,000 scenes, each of which has 20 frames with fully annotated 3D bounding boxes on vehicles. We provide the benchmark for four 3D perception tasks: single-UAV 3D object detection, single-UAV object tracking, collaborative-UAV 3D object detection, and collaborative-UAV object tracking.

Barksdale Air Force Base, home to nuclear-capable B-52 bombers, confirmed "multiple unauthorized drones" in its airspace during the week of March 9.

Cinematographers adeptly capture the essence of the world, crafting compelling visual narratives through intricate camera movements. Witnessing the strides made by large language models in perceiving and interacting with the 3D world, this study explores their capability to control cameras with human language guidance. We introduce ChatCam, a system that navigates camera movements through conversations with users, mimicking a professional cinematographer's workflow. To achieve this, we propose CineGPT, a GPT-based autoregressive model for text-conditioned camera trajectory generation. We also develop an Anchor Determinator to ensure precise camera trajectory placement. ChatCam understands user requests and employs our proposed tools to generate trajectories, which can be used to render high-quality video footage on radiance field representations. Our experiments, including comparisons to state-of-the-art approaches and user studies, demonstrate our approach's ability to interpret and execute complex instructions for camera operation, showing promising applications in real-world production settings.

Science Ask Us Anything What'Jurassic Park' got wrong about venomous dinosaurs And what did'Spinosaurus' really do with that sail? Dilophosaurus didn't have a frill or spit venom. Breakthroughs, discoveries, and DIY tips sent six days a week. We all know dinosaurs were scary. While not strictly a dinosaur, the ancient shark was four times longer than the biggest great white. Now, imagine one of those big bad dinos had venom. That'd be the last thing we need, but it very well could've been a reality. In a new episode of's Ask Us Anything podcast, we dig into the fossil record to see just how likely a venomous dinosaur would've been.

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Hospital cyberattacks like the University of Mississippi Medical Center ransomware incident disrupt patient care. Ricardo Amper explains why healthcare systems are targets.

Smart glasses with AI photo editing capabilities raise questions about image authenticity as the technology can generate realistic backgrounds and alter photos instantly.