In this course, we review use cases and challenges of three interrelated areas in computer science: artificial intelligence (AI), the internet of things (IoT), and cybersecurity. Students gain an overview of the possibilities and challenges of building complex information systems that take advantage of recent advances in these fields. The course is divided into three parts, each focused on the instructor presenting the research conducted by leading Massachusetts Institute of Technology (MIT) experts in their fields. Students gain an understanding of what is possible and what not today, as well as what MIT researchers are trying to make possible in the near future. The course provides a framework to analyze the frontiers in computer science. The first part surveys state-of-the-art topics in designing AI products and services. The focus of this part of the course is to understand where the rapidly evolving frontier in AI areas is. It covers machine learning (including neural networks), speech processing, robotics computer vision, and natural language processing. Topics in this first section also include existing hurdles for successful AI design such as explainability, visualization, adversarial attacks, and institutional review board (IRB) approval. The AI segment has two weeks entirely devoted to healthcare, covering neural implants, ingestible robotics, multi-modal longitudinal diagnosis with deep neural networks, mechanical limbs including grasping, and wi-fi surveillance. The second part of the course looks at the IoT. While the promise of the IoT brings many new business prospects, it also presents significant challenges ranging from technology architectural choices to security concerns. This part of the course offers important insights into how to overcome these challenges and thrive in this exciting space. The concept of IoT has begun to make an impact in industries ranging from industrial systems to home automation to healthcare. MIT researchers continue to conduct ground-breaking research on topics that are presented ranging from radio frequency identification (RFID) to cloud technologies, and from sensors to the world wide web. The third and final part of the course covers cybersecurity issues related to hardware, software, cryptography, blockchain, and policy to make better, safer decisions. Topics include systems (secure architectures, network security, secure programming languages, and system verification); algorithmic solutions (public key cryptography, multi-party computation, secret sharing, distributing trust, and computing on encrypted data); public policy issues in cybersecurity; and case studies (BitLocker, web security, and mobile phone security).
