Optimizing shipping logistics in a time of change

Within logistics, shipping is a vast and delicate ecosystem. Over the last couple of years many people were directly impacted by complete production shutdowns, huge and unexpected swings in consumer demand, lack of labor at ports, a shortage of shipping containers… just to name a few! Addressing challenges with business analytics To help with some …

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A Multi-Axis Approach for Vision Transformer and MLP Models

Posted by Zhengzhong Tu and Yinxiao Li, Software Engineers, Google Research Convolutional neural networks have been the dominant machine learning architecture for computer vision since the introduction of AlexNet in 2012. Recently, inspired by the evolution of Transformers in natural language processing, attention mechanisms have been prominently incorporated into vision models. These attention methods boost …

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NVIDIA Hopper Sweeps AI Inference Benchmarks in MLPerf Debut

In their debut on the MLPerf industry-standard AI benchmarks, NVIDIA H100 Tensor Core GPUs set world records in inference on all workloads, delivering up to 4.5x more performance than previous-generation GPUs. The results demonstrate that Hopper is the premium choice for users who demand utmost performance on advanced AI models. Additionally, NVIDIA A100 Tensor Core …

A steadfast community in an ever-changing data landscape

There are still not enough data experts out there, even as the world of data evolves rapidly. We started the Summer School for Data Leaders five years ago to create a community for data experts to share ideas and relate to people facing similar challenges. Today, the Summer School has grown to include over 400 …

Ashish Khetan

Transfer learning for TensorFlow image classification models in Amazon SageMaker

Amazon SageMaker provides a suite of built-in algorithms, pre-trained models, and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. You can use these algorithms and models for both supervised and unsupervised learning. They can process various types of input data, including tabular, …

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Improve transcription accuracy of customer-agent calls with custom vocabulary in Amazon Transcribe

Many AWS customers have been successfully using Amazon Transcribe to accurately, efficiently, and automatically convert their customer audio conversations to text, and extract actionable insights from them. These insights can help you continuously enhance the processes and products that directly improve the quality and experience for your customers. In many countries, such as India, English …

Mel Spectrogram Inversion with Stable Pitch

Vocoders are models capable of transforming a low-dimensional spectral representation of an audio signal, typically the mel spectrogram, to a waveform. Modern speech generation pipelines use a vocoder as their final component. Recent vocoder models developed for speech achieve a high degree of realism, such that it is natural to wonder how they would perform …

GAUDI: A Neural Architect for Immersive 3D Scene Generation

We introduce GAUDI, a generative model capable of capturing the distribution of complex and realistic 3D scenes that can be rendered immersively from a moving camera. We tackle this challenging problem with a scalable yet powerful approach, where we first optimize a latent representation that disentangles radiance fields and camera poses. This latent representation is …

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Digitizing Smell: Using Molecular Maps to Understand Odor

Posted by Richard C. Gerkin, Google Research, and Alexander B. Wiltschko, Google Did you ever try to measure a smell? …Until you can measure their likenesses and differences you can have no science of odor. If you are ambitious to found a new science, measure a smell. — Alexander Graham Bell, 1914. How can we …