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Native Frame Rate Playback

by Akshay Garg, Roger Quero Introduction Maximizing immersion for our members is an important goal for the Netflix product and engineering teams to keep our members entertained and fully engaged in our content. Leveraging a good mix of mature and cutting-edge client device technologies to deliver a smooth playback experience with glitch-free in-app transitions is an …

7 steps for managing the work order process

Work orders are the driving force behind any organization’s asset management apparatus. Whenever a person or entity submits a service request, the maintenance team that receives it must create a formal paper and/or digital document that includes all the details of maintenance tasks and outlines a process for completing the tasks. That document is called …

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Use Amazon SageMaker Canvas to build machine learning models using Parquet data from Amazon Athena and AWS Lake Formation

Data is the foundation for machine learning (ML) algorithms. One of the most common formats for storing large amounts of data is Apache Parquet due to its compact and highly efficient format. This means that business analysts who want to extract insights from the large volumes of data in their data warehouse must frequently use …

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From Receipts to Riches: Save Money w/ Google Cloud & Supermarket Bills – Part 2

Manual document classification and extraction is still a time-consuming and difficult task for many organizations. This blog series aims to demonstrate how Google Cloud products like Document AI and BigQuery can be used together to help organizations eliminate manual document processing. In the first part of this blog series, we discussed how to digitize grocery …

Microsoft Bing Speeds Ad Delivery With NVIDIA Triton

Jiusheng Chen’s team just got accelerated. They’re delivering personalized ads to users of Microsoft Bing with 7x throughput at reduced cost, thanks to NVIDIA Triton Inference Server running on NVIDIA A100 Tensor Core GPUs. It’s an amazing achievement for the principal software engineering manager and his crew. Tuning a Complex System Bing’s ad service uses …

Robustness in Multimodal Learning under Train-Test Modality Mismatch

Multimodal learning is defined as learning over multiple heterogeneous input modalities such as video, audio, and text. In this work, we are concerned with understanding how models behave as the type of modalities differ between training and deployment, a situation that naturally arises in many applications of multimodal learning to hardware platforms. We present a …

Accelerating AI & Innovation: the future of banking depends on core modernization

In the rapidly evolving landscape of financial services, embracing AI and digital innovation at scale has become imperative for banks to stay competitive. With the power of AI and machine learning, financial institutions can leverage predictive analytics, anomaly detection and shared learning models to enhance system stability, detect fraud and drive superior customer-centric experiences. As …

AVFormer

AVFormer: Injecting vision into frozen speech models for zero-shot AV-ASR

Posted by Arsha Nagrani and Paul Hongsuck Seo, Research Scientists, Google Research Automatic speech recognition (ASR) is a well-established technology that is widely adopted for various applications such as conference calls, streamed video transcription and voice commands. While the challenges for this technology are centered around noisy audio inputs, the visual stream in multimodal videos …

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Last Chance! 48-Hour Flash Sale on AI & Chatbot Certified Workshops

I hope this email finds you well. I wanted to reach out with an exciting update: we are having a 48-Hour Flash Sale on our highly anticipated AI & Chatbot Certified Workshops, and I didn’t want you to miss out on this amazing opportunity! For the next 48 hours only, you can take advantage of …

Learning Language-Specific Layers for Multilingual Machine Translation

Multilingual Machine Translation promises to improve translation quality between non-English languages. This is advantageous for several reasons, namely lower latency (no need to translate twice), and reduced error cascades (e.g. , avoiding losing gender and formality information when translating through English). On the downside, adding more languages reduces model capacity per language, which is usually …