Things to Do in L.A. Tap to enable a layout that focuses on the article. A pedestrian walks past Los Angeles Police Department headquarters along 1st Street downtown. This is read by an automated voice. Please report any issues or inconsistencies here . An LAPD official said an investigation is underway after video footage showed an officer from Transit Services Division enter a Tesla while responding to a call for service.

Online detectives are inaccurately claiming to have identified the federal agent who shot and killed a 37-year-old woman in Minnesota based on AI-manipulated images. Federal agents push through a crowd of bystanders as they leave the scene where a woman was fatally shot by an agent in Minneapolis, Minn., on January 7, 2026. In the hours after a masked federal agent shot and killed Renee Nicole Good, a 37-year-old woman in Minneapolis, social media users have been sharing AI-altered images they falsely claim "unmask" the officer, revealing their real identity. The agent was later identified by Department of Homeland Security spokesperson Tricia McLaughlin as an Immigrations and Customs Enforcement officer. The shooting occurred on Wednesday morning, and social media footage of the scene shows two masked federal agents approaching an SUV parked in the middle of the road in a suburb south of downtown Minneapolis.

Organizations have a wealth of unstructured data that most AI models can't yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results. Enterprises are sitting on vast quantities of unstructured data, from call records and video footage to customer complaint histories and supply chain signals. Yet this invaluable business intelligence, estimated to make up as much as 90% of the data generated by organizations, historically remained dormant because its unstructured nature makes analysis extremely difficult. But if managed and centralized effectively, this messy and often voluminous data is not only a precious asset for training and optimizing next-generation AI systems, enhancing their accuracy, context, and adaptability, it can also deliver profound insights that drive real business outcomes. A compelling example of this can be seen in the US NBA basketball team the Charlotte Hornets who successfully leveraged untapped video footage of gameplay--previously too copious to watch and too unstructured to analyze--to identify a new competition-winning recruit.

Indoor navigation is a difficult task, as it generally comes with poor GPS access, forcing solutions to rely on other sources of information. While significant progress continues to be made in this area, deployment to production applications is still lacking, given the complexity and additional requirements of current solutions. Here, we introduce an efficient, real-time and easily deployable deep learning approach, based on visual input only, that can predict the direction towards a target from images captured by a mobile device. Our technical approach, based on a novel graph-based path generation method, combined with explainable data augmentation and curriculum learning, includes contributions that make the process of data collection, annotation and training, as automatic as possible, efficient and robust. On the practical side, we introduce a novel large-scale dataset, with video footage inside a relatively large shopping mall, in which each frame is annotated with the correct next direction towards different specific target destinations. Different from current methods, ours relies solely on vision, avoiding the need of special sensors, additional markers placed along the path, knowledge of the scene map or internet access. W e also created an easy to use application for Android, which we plan to make publicly available.

Identifying risky driving behavior in real-world situations is essential for the safety of both drivers and pedestrians. However, integrating natural language models in this field remains relatively untapped. To address this, we created a novel multi-modal instruction tuning dataset and driver coaching inference system. Our primary use case is dashcam-based coaching for commercial drivers. The North American Dashcam Market is expected to register a CAGR of 15.4 percent from 2022 to 2027. Our dataset enables language models to learn visual instructions across various risky driving scenarios, emphasizing detailed reasoning crucial for effective driver coaching and managerial comprehension. Our model is trained on roadfacing and driver-facing RGB camera footage, capturing the comprehensive scope of driving Figure 1: Overview of our targeting coaching task.

Researchers from the University of Waterloo got a valuable assist from artificial intelligence (AI) tools to help capture and analyze data from professional hockey games more quickly and more accurately, something which could have implications for the business of sports. The growing field of hockey analytics currently relies on the manual analysis of video footage from games. Professional hockey teams across the sport, notably in the National Hockey League (NHL), make important decisions regarding players' careers based on that information. "The goal of our research is to interpret a hockey game through video more effectively and efficiently than a human," said Dr David Clausi, a professor in Waterloo's Department of Systems Design Engineering. Bounding boxes are used to identify players as they move on the ice in broadcast game video.

Genie often adds this effect to the games it generates. While Genie is an in-house research project and won't be released, Guzdial notes that the Google DeepMind team says it could one day be turned into a game-making tool--something he's working on too. "I'm definitely interested to see what they build," he says.

The U.S. Department of Defense released video footage of a U.S. air strike on a training and weapons facility in Abul Kamal, Syria. The USS Thomas Hudner, an Arleigh Burke-class destroyer, shot down a drone from Yemen in the Red Sea on Wednesday, two U.S. defense officials confirmed to Fox News. A defense official said the drone was shot down in self-defense. "The drone was heading towards the Hudner," the official said. The drone attack is the latest in a series of attacks on American troops stationed in the Middle East amid the ongoing Israel-Hamas war.

Computer vision and machine learning have brought revolutionary shifts in perception for researchers, scientists, and the general populace. Once thought to be unattainable, these technologies have achieved the seemingly impossible. Their exceptional applications in diverse fields like security, agriculture, and education are a testament to their impact. However, the full potential of computer vision remains untapped. This paper explores computer vision's potential in security and surveillance, presenting a novel approach to track motion in videos. By categorizing motion into Arcs, Lanes, Converging/Diverging, and Random/Block motions using Motion Information Images and Blockwise dominant motion data, the paper examines different optical flow techniques, CNN models, and machine learning models. Successfully achieving its objectives with promising accuracy, the results can train anomaly-detection models, provide behavioral insights based on motion, and enhance scene comprehension.

Porcha Woodruff was eight months pregnant when police in Detroit, Michigan came to arrest her on charges of carjacking and robbery. She was getting her two children ready for school when six police officers knocked on her door and presented her with an arrest warrant. She thought it was a prank. Do you see that I am eight months pregnant?" the lawsuit Woodruff filed against Detroit police reads. She sent her children upstairs to tell her fiance that "Mommy's going to jail". She was detained and questioned for 11 hours and released on a $100,000 bond. She immediately went to the hospital, where she was treated for dehydration. Woodruff later found out that she was the latest victim of false identification by facial recognition. After her image was incorrectly matched to video footage of a woman at the gas station where the carjacking took place, her picture was shown to the victim in a photo lineup. According to the lawsuit, the victim allegedly chose Woodruff's picture as the woman ...