From edge computing and causal reasoning to differential privacy and visual-field mapping, the top blog posts of the year display the range of scientific ...

We explored everything from the science behind the new F1 car to a look back at how the operations science team addressed a challenge of almost unimaginable ...

As a Principal Scientist within Alexa, you are a trusted part of the technical leadership. You bring ...

Most state-of-the-art computer vision models depend on supervised learning, in which labeled data is used for training. But labeling is costly, and the cost ...

Zongyi (Joe) Liu is a principal scientist in the Amazon Customer Experience and Business Trends (CXBT) organization, which evaluates the customer experience ...

In June 2022, Amazon re:MARS, the company’s in-person event that explores advancements and practical applications within machine learning, automation, ...

A quick guide to Amazon’s innovative work at the IEEE Spoken Language Technology Workshop (SLT), which begins next week:Accelerator-aware training for ...

A. While I was studying industrial design at Lund University, I had the opportunity to go to Johnson Space Center and take part in a project with NASA. The ...

Modern AI models, such as those that recognize images and speech, are highly data dependent. While some public-domain data sets are available to train such ...

In an effort to create enduring pipelines of diverse science talent and differentiated research, Amazon today announced a collaboration with Tennessee State ...

In recent years, automatic speech recognition (ASR) has moved to all-neural models. Connectionist-temporal-classification loss functions are an attractive ...

Knowledge distillation is a popular technique for compressing large machine learning models into manageable sizes, to make them suitable for low-latency ...