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Autonomous vehicles (AVs) represent a transformative advancement in transportation technology, promising to enhance travel efficiency, reduce traffic accidents, and revolutionize our road systems. Central to the operation of AVs is the integration of artificial intelligence (AI), which enables these vehicles to navigate complex environments with minimal human intervention. This review critically examines the potential dangers associated with the increasing reliance on AI in AV navigation. It explores the current state of AI technologies, highlighting key techniques such as machine learning and neural networks, and identifies significant challenges including technical limitations, safety risks, and ethical and legal concerns. Real-world incidents, such as Uber's fatal accident and Tesla's crash, underscore the potential risks and the need for robust safety measures. Future threats, such as sophisticated cyber-attacks, are also considered. The review emphasizes the importance of improving AI systems, implementing comprehensive regulatory frameworks, and enhancing public awareness to mitigate these risks. By addressing these challenges, we can pave the way for the safe and reliable deployment of autonomous vehicles, ensuring their benefits can be fully realized. [ABSTRACT FROM AUTHOR]

The rapid development and deployment of autonomous vehicles (AVs) present unprecedented opportunities and challenges in the transportation sector. While AVs promise enhanced safety, efficiency, and convenience, they also introduce significant cybersecurity vulnerabilities due to their reliance on advanced electronics, connectivity, and artificial intelligence (AI). This review examines the current state of cybersecurity in autonomous vehicles, identifying major threats such as remote hacking, sensor manipulation, data breaches, and denial of service (DoS) attacks. It also explores existing countermeasures including intrusion detection systems (IDSs), encryption, over-the-air (OTA) updates, and authentication protocols. Despite these efforts, numerous challenges remain, including the complexity of AV systems, lack of standardization, latency issues, and resource constraints. This review concludes by highlighting future directions in cybersecurity research and development, emphasizing the potential of AI and machine learning, blockchain technology, industry collaboration, and legislative measures to enhance the security of autonomous vehicles. [ABSTRACT FROM AUTHOR]

In the rapidly evolving landscape of electronics, Artificial Intelligence Circuits and Systems (AICAS) stand out as a groundbreaking frontier. This review provides an exhaustive examination of the advancements in AICAS, tracing its development from inception to its modern-day applications. Beginning with the foundational principles that underpin AICAS, we delve into the state-of-the-art architectures and design paradigms that are propelling the field forward. This review also sheds light on the multifaceted applications of AICAS, from optimizing energy efficiency in electronic devices to empowering next-generation cognitive computing systems. Key challenges, such as scalability and robustness, are discussed in depth, along with potential solutions and emerging trends that promise to shape the future of AICAS. By offering a comprehensive overview of the current state and potential trajectory of AICAS, this review serves as a valuable resource for researchers, engineers, and industry professionals looking to harness the power of AI in electronics. [ABSTRACT FROM AUTHOR]