End-to-end learning directly maps sensory inputs to actions, creating highly integrated and efficient policies for complex robotics tasks. However, such models are tricky to efficiently train and often struggle to generalize beyond their training scenarios, limiting adaptability to new environments, tasks, and concepts. In this work, we investigate the minimal data requirements and architectural adaptations necessary to achieve robust closed-loop performance with vision-based control policies under unseen text instructions and visual distribution shifts. To this end, we design datasets with various levels of data representation richness, refine feature extraction protocols by leveraging multi-modal foundation model encoders, and assess the suitability of different policy network heads. Our findings are synthesized in Flex (Fly-lexically), a framework that uses pre-trained Vision Language Models (VLMs) as frozen patch-wise feature extractors, generating spatially aware embeddings that integrate semantic and visual information. These rich features form the basis for training highly robust downstream policies capable of generalizing across platforms, environments, and text-specified tasks. We demonstrate the effectiveness of this approach on quadrotor fly-to-target tasks, where agents trained via behavior cloning on a small simulated dataset successfully generalize to real-world scenes, handling diverse novel goals and command formulations.

On 11 October, North Korea's foreign ministry accused the South of sending drones to Pyongyang at night over the course of two weeks. It said that leaflets dispersed by the drones contained "inflammatory rumours and rubbish". Kim's influential sister, Kim Yo Jong, warned Seoul of "horrible consequences" if the alleged drone flights happened again. She later said there was "clear evidence" that "military gangsters" from the South were behind the alleged provocations. North Korea has released blurry images of what it said were the drones flying in the sky, as well as pictures allegedly showing the leaflets, but there is no way of independently verifying their claims.

Somewhere on the horizon is a beam of light from another group, scouring the skies for danger over their own patrol zone. There's no public data on the total number of volunteer units – or how many women are involved. But as Russia sends drones packed with explosives almost every night, they help form an extra shield around big towns and cities. From the Witches' position in a field, Yulia tracks two drones on her tablet. They're over the neighbouring region, so there's no imminent danger for Bucha, but the machine guns will stay in place until the alert ends.

In the past utilities relied on in-field inspections to identify asset defects. Recently, utilities have started using drone-based inspections to enhance the field-inspection process. We consider a vast repository of drone images, providing a wealth of information about asset health and potential issues. However, making the collected imagery data useful for automated defect detection requires significant manual labeling effort. We propose a novel solution that combines synthetic asset defect images with manually labeled drone images. This solution has several benefits: improves performance of defect detection, reduces the number of hours spent on manual labeling, and enables the capability to generate realistic images of rare defects where not enough real-world data is available. We employ a workflow that combines 3D modeling tools such as Maya and Unreal Engine to create photorealistic 3D models and 2D renderings of defective assets and their surroundings. These synthetic images are then integrated into our training pipeline augmenting the real data. This study implements an end-to-end Artificial Intelligence solution to detect assets and asset defects from the combined imagery repository. The unique contribution of this research lies in the application of advanced computer vision models and the generation of photorealistic 3D renderings of defective assets, aiming to transform the asset inspection process. Our asset detection model has achieved an accuracy of 92 percent, we achieved a performance lift of 67 percent when introducing approximately 2,000 synthetic images of 2k resolution. In our tests, the defect detection model achieved an accuracy of 73 percent across two batches of images. Our analysis demonstrated that synthetic data can be successfully used in place of real-world manually labeled data to train defect detection model.

A retired, senior Pentagon official has confirmed that UFO'mother ships' were spotted'releasing swarms of smaller craft' -- adding further mystery to the still-unexplained intrusions over multiple US military bases. His statements come amid the release of 50 pages of Air Force records related to provocative'drone' incursions, that one general calls'Close Encounters at Langley.' For at least 17 nights last December, swarms of noisy, small UFOs were seen at dusk'moving at rapid speeds' and displaying'flashing red, green, and white lights' penetrating the highly restricted airspace above Langley Air Force Base in Virginia. Senior ex-Pentagon security official Chris Mellon told DailyMail.com'Two of the notable aspects,' he said, 'are the fact our drone signal-jamming devices have proven ineffective and these craft are making no effort to remain concealed.'

Here in northern Israel we hear booms at regular intervals as Iron Dome intercept rockets that Hezbollah fires from southern Lebanon. Israel says it hits more than 90% of its targets. But Iron Dome works because Hezbollah's rockets are crude – and it's possible to calculate where it's rockets will go at take-off and then intercept them. Stopping drones is more complicated. And has in this war become a recurring problem.

One of the civilians who spotted the drone, Viki Kadosh, said she was "so frustrated, because 10 minutes before the hit, we had called in to warn about it." Speaking on Monday to Galei Tzahal, a radio station run by the Israeli military, Ms. Kadosh said: "We spotted it flying very low, right above our home. We heard the sound it was making and immediately noticed there was something strange about it." The Israeli military declined to comment. The sequence of drone attacks has caused alarm in Israel as it prepares for a potential escalation with Iran.

Hezbollah has carried out its deadliest attack against Israel since the latest escalation in fighting began, sending a'swarm' of drones to a military base and killing at least four soldiers. Here's what we know about the attack.

South Korea's military has announced it is "fully ready" to respond amid reports that North Korean troops have been deployed to the border and are getting ready to blow up roads connecting the two nations along the heavily militarised dividing line. Tensions have escalated in recent days as the nuclear-armed North accused Seoul of flying drones over its capital to drop propaganda leaflets filled with "inflammatory rumours and rubbish", and warned that if another drone was detected, it would consider it "a declaration of war". South Korean military spokesman Lee Sung-jun told reporters in Seoul on Monday they are in "full readiness" against the possibility of "a provocation" after Pyongyang ordered artillery units along the border to open fire in case of an escalation. South Korean state news agency Yonhap also quoted Lee as saying the military found that the North is installing screens along the roads "to make preparations for the explosions". "It is possible for [North Korea's explosions] to take place as early as today [Monday]," he said.

South Korea's military said Monday it was "fully ready" to respond after North Korea ordered troops on the border to prepare to fire, in an escalating dispute over drone flights to Pyongyang. The nuclear-armed North has accused Seoul of flying drones over its capital to drop propaganda leaflets filled with "inflammatory rumors and rubbish," and warned Sunday that if another drone was detected, it would consider it "a declaration of war." Seoul's military previously denied it was behind the flights, with local speculation centered on activist groups in the South, which have long sent propaganda and U.S. currency northward, typically by balloon.