This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts. Over the recent years, a revolutionary new paradigm has been developed for training models for NLP. These models are first pre-trained on large collections of text documents to acquire general syntactic knowledge and semantic information. Then, they are fine-tuned for specific tasks, which they can often solve with superhuman accuracy. When the models are large enough, they can be instructed by prompts to solve new tasks without any fine-tuning. Moreover, they can be applied to a wide range of different media and problem domains, ranging from image and video processing to robot control learning. Because they provide a blueprint for solving many tasks in artificial intelligence, they have been called Foundation Models. After a brief introduction to basic NLP models the main pre-trained language models BERT, GPT and sequence-to-sequence transformer are described, as well as the concepts of self-attention and context-sensitive embedding. Then, different approaches to improving these models are discussed, such as expanding the pre-training criteria, increasing the length of input texts, or including extra knowledge. An overview of the best-performing models for about twenty application areas is then presented, e.g., question answering, translation, story generation, dialog systems, generating images from text, etc. For each application area, the strengths and weaknesses of current models are discussed, and an outlook on further developments is given. In addition, links are provided to freely available program code. A concluding chapter summarizes the economic opportunities, mitigation of risks, and potential developments of AI.
This textbook provides an introduction to modern monetary economics for advanced undergraduates, highlighting the lessons learned from the recent financial crisis. The book presents both the core New Keynesian model and recent advances, taking into account financial frictions, and discusses recent research on an intuitive level based on simple static and two-period models, but also prepares readers for an extension to a truly dynamic analysis. Further, it offers a systematic perspective on monetary policy, covering a wide range of models to help readers gain a better understanding of controversial issues. Part I examines the long-run perspective, addressing classical monetary policy issues such as determination of the price level and interaction between monetary and fiscal policy. Part II introduces the core New Keynesian model, characterizing optimal monetary policy to stabilize short-term shocks. It discusses rules vs. discretion and the challenges arising from control errors, imperfect information and robustness issues. It also analyzes optimal control in the presence of an effective lower bound. Part III focuses on modelling financial frictions. It identifies the transmission mechanisms of monetary policy via banking and introduces models with incomplete markets, principal-agent problems, maturity mismatch and leverage cycles, to show why investors’ and intermediaries’ own stakes play a key role in lending with pro-cyclical features. In addition, it presents a tractable model for handling liquidity management and demonstrates that the need to sell assets in crisis amplifies the volatility of the real economy. Lastly, the book discusses the relation between monetary policy and financial stability, addressing systemic risk and the role of macro-prudential regulation.
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