Electric vehicles (EVs) have gained significant momentum in the automotive industry, with their long-anticipated shift to electric power. This shift has a direct impact on various stakeholders. Similarly, advancements in artificial intelligence (AI) are revolutionizing the control and functionality of drones. Researchers have recently developed a machine-learning approach that enhances the control of robots, including drones and autonomous vehicles, especially in rapidly changing environments. This wave of AI innovations has the potential to transform drone utilization across multiple sectors, including hobbyists, military applications, and industrial purposes. According to Carlo Pinciroli, a professor of robotics engineering at Worcester Polytechnic Institute, AI reduces the need for constant human intervention, enabling drone operators to view them as collaborative teammates rather than mere puppets. This collaborative approach allows for the execution of complex and perilous missions while minimizing the risk to human safety. A groundbreaking technique developed by scientists from MIT and Stanford University enables a drone to closely track a downhill skier even in adverse weather conditions. By integrating control theory into their learning process, the researchers leverage valuable hints to guide the system's control strategy. Remarkably, their approach only requires 100 data points, making it highly efficient for rapid learning in dynamic environments. AI-powered drones possess remarkable autonomy, allowing them to perform tasks such as large-scale mapping and search-and-rescue operations. These drones can adapt to changing surroundings and effectively manage unexpected situations. Real-time data analysis from various sensors further enhances their capacity for data collection and analysis. The film and photography industry has widely embraced the potential of AI-powered drones to capture breathtaking shots during live events, movie scenes, and natural landscapes.

Additionally, drones are being utilized for last-mile delivery services and can autonomously navigate and identify suitable landing spots for package delivery. Remote visual monitoring and inspection of aging infrastructure, such as bridges, can be efficiently conducted using drones. The captured aerial imagery can be transformed into 3D bridge models, enabling accurate analysis and assessment of cracks and defects. AI's impact on drone technology extends to warfare applications as well. The conflict in Ukraine has accelerated developments in AI-controlled drones. Automation facilitated by AI, such as image recognition, replaces the need for human vigilance in identifying potential threats. Fortem Technologies, for instance, employs AI in its DroneHunter system, which autonomously pursues and neutralizes enemy drones. High automation levels not only enhance mission speed and success rates but also reduce human error and operator workload. Looking ahead, there is the potential to use large AI language models like ChatGPT for voice-controlled drones. Verbal commands from authorized officers could enable specific instructions such as continuous drone threat detection. Once authorized, AI takes over the implementation and execution of the given command. In conclusion, the integration of AI and electric power in the automotive and drone industries respectively is driving significant transformations. These advancements improve efficiency, safety, and capabilities, revolutionizing various sectors ranging from transportation and delivery to filmmaking and military operations.