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One of the great attractions of large language models (LLMs) is that they encode information about the real world. But the world is constantly changing, and...
Federated learning is a process in which distributed devices, each with its own store of locally collected data, can contribute to a global machine learning model...
In March of 2022, Amazon and Carnegie Mellon University announced the second class of Amazon graduate research fellows, marking an expansion of the company’s efforts to...
In recent years, automatic speech recognition (ASR) has moved to all-neural models. Connectionist-temporal-classification loss functions are an attractive option for ASR (and specifically end-to-end ASR) because...
Three years ago, Alexa began using an industry-leading self-learning model that learns to correct improperly phrased or misheard customer queries without human involvement. The model detects...
Machine learning (ML) models need regular updates to improve performance, but retraining a model poses risks, such as the loss of backward compatibility or behavioral regression,...
Watching items move down a conveyor belt toward a Robin robot arm at an Amazon fulfillment center is a great place to learn about the role...
Kathleen McKeown, the Henry and Gertrude Rothschild Professor of Computer Science at Columbia University and an Amazon Scholar, has a storied history with the Association for...