While previous chapters discussed deep learning recommender systems from a theoretical and algorithmic perspective, this chapter shifts focus to the engineering platform that supports their implementation. Recommender systems are divided into two key components: data and model. The data aspect involves the engineering of the data pipeline, while the model aspect is split between offline training and online serving. This chapter is structured into three parts: (1) the data pipeline framework and big data platform technologies; (2) popular platforms for offline training of recommendation models like Spark MLlib, TensorFlow, and PyTorch; and (3) online deployment and serving of deep learning recommendation models. Additionally, the chapter covers the trade-offs between engineering execution and theoretical considerations, offering insights into how algorithm engineers can balance these aspects in practice.

This chapter explores the widespread issue of addiction, focusing on sugar addiction as a prevalent yet often overlooked example. It compares the addictive potential of sugar to cocaine, highlighting the detrimental health consequences of excessive sugar consumption. The chapter also examines the neural mechanisms underlying addiction, explaining how the brain’s pleasure system adapts to frequent drug use, leading to cravings and withdrawal symptoms. Music is presented as a potential antidote to addiction, offering distraction, mood regulation, and alternative sources of pleasure. Research suggests that music therapy can be a promising intervention for individuals struggling with addiction, as it activates the brain’s pleasure pathways and fosters social connection. The chapter also discusses the importance of personalized playlists in addiction management, emphasizing the need to avoid music associated with past addictive behaviours. It concludes by offering practical recommendations for utilizing music to overcome cravings, regulate emotions, and build resilience in the face of addiction. The potential of music therapy to address the underlying emotional and social factors contributing to addiction is also highlighted.

What is the nature of discovery? As a human being and a physicist, I can only observe one mind at work first-hand. This mind accepts every new scrap as a discovery, whether it originates in the external world of knowledge or springs from an internal process. To explore the nature of discovery from the point of view of the inner observer, I chose to turn over past experiences, fitting together days on which years of determined and dogged plodding resulted in a finished equation, or finally, a coherent assembly of disparate ideas gave the clue to why storm damage in breakwaters is like a phase change in liquid crystals. Old, unfashionable methods are suddenly useful with new computer architectures. Theory, experiment, observation, and simulation fit together as aids to thinking. The properties of complex systems can provide intuitive insight into the social science of science. We will need every ability to assemble the puzzle pieces in the coming years to discover how to extricate the planet from the difficulties in which we have placed it: as an observer and actor, I suggest that the evolution of human thinking, and of aids to thinking, are critical.