![]() The impact of AI on economic growth and international trade This means that access to the tails of data-less usual and irregular data-matters. Here, quantity matters because machine learning needs to be able to incorporate into future predictions as many possible past outcomes as possible. 5Īpplying these developments in a real-world context requires large data sets to initialize AI systems. Narrow AI also includes specific tools such as out-of-sample validation to validate models, stochastic gradient descent for training models on streams of data, and graphical processing units (GPUs)-originally developed for video games but which have proven well-suited to support the types of massive parallel computations needed to train DNNs. 4 Deep Neural Networks combine multiple machine learning tasks-creating what is referred to as general purpose machine learning (GPML)-which allows AI to effectively live on top of the types of chaotic data that humans are able to digest, such as video, audio, and text. Each layer is highly modular, making it possible to take a layer optimized for one type of data (say, images) and to combine it with other layers for other types of data (e.g., text). DNNs are comprised of layers of nonlinear transformation node functions, where the output of each layer becomes an input to the next layer in the network. John Villasenor Wednesday, November 14, 2018Īnother key development underpinning narrow AI is the Deep Neural Network (DNN). 3 This includes reinforcement learning-where machine-learning algorithms actively choose and even generate their own training data. 2 The data used for machine learning can be either supervised-data with associated facts, such as labels-or unsupervised-raw data that requires the identification of patterns without prior prompting. In particular, narrow AI is based on machine learning, which uses large amounts of data and powerful algorithms to develop increasingly robust predictions about the future. To understand the potential significance of narrow AI for trade, it is also important to briefly consider its core parts. More specifically, that there is a key difference between narrow AI such as translation services, chatbots, and autonomous vehicles and general AI-“self-learning systems that can learn from experience with humanlike breadth and surpass human performance on all tasks.” General AI raises broader existential concerns, such as how to align the goals of such a system with our own to prevent catastrophic outcomes, 1 but general AI remains a technology still to be developed in the distant future. What do we mean by artificial intelligence?īefore proceeding to the impact of AI on trade, it is important to clarify what is meant by AI. The following provides an overview of some of the key AI opportunities for trade as well as those areas where trade rules can help support AI development. At the same time, there are challenges in the development of AI that international trade rules could address, such as improving global access to data to train AI systems. Already, specific applications in areas such as data analytics and translation services are reducing barriers to trade. Twitter intelligence (AI) stands to have a transformative impact on international trade.
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