Machine learning (ML) is iterative in nature — model improvement is a necessity to drive the best business outcomes. Yet, with the proliferation of model artifacts, it can be difficult to ensure that only the best models make it into production. Data science teams may get access to new training data, expand the scope of …
Read more “Streamline your models to production with the Vertex AI Model Registry”
Introduction Personalized recommender systems are used widely for offering the right products or content to the right users. Some examples of such systems are video recommendations (“What to Watch Next”) on YouTube, Google Play Store app recommendations and similar services offered by other app stores and content services. In essence, recommendation systems filter products or …
Read more “Building Large Scale Recommenders using Cloud TPUs”
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Posted by Zalán Borsos, Research Software Engineer, and Neil Zeghidour, Research Scientist, Google Research Generating realistic audio requires modeling information represented at different scales. For example, just as music builds complex musical phrases from individual notes, speech combines temporally local structures, such as phonemes or syllables, into words and sentences. Creating well-structured and coherent audio …
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Synamedia is a leading video technology provider addressing the needs for premium video service providers and direct-to-consumer (D2C) with a comprehensive solution portfolio. Synamedia solutions spread across several pillars such as video networks, TV platforms, advertisement and monetization, and content protection and piracy disruption. Synamedia partnered with AWS to use artificial intelligence (AI) to develop …
Model training forms the core of any machine learning (ML) project, and having a trained ML model is essential to adding intelligence to a modern application. A performant model is the output of a rigorous and diligent data science methodology. Not implementing a proper model training process can lead to high infrastructure and personnel costs …
This post was co-written with Robert Berger and Adine Deford from InformedIQ. InformedIQ is the leader in AI-based software used by the nation’s largest financial institutions to automate loan processing verifications and consumer credit applications in real time per the lenders’ policies. They improve regulatory compliance, reduce cost, and increase accuracy by decreasing human error …
Read more “InformedIQ automates verifications for Origence’s auto lending using machine learning”
At Google, we believe anyone should be able to quickly and easily turn their artificial intelligence (AI) idea into reality. Open source software (OSS) has become increasingly important to this goal, heavily influencing the pace of innovation in AI and machine learning (ML) ecosystems. Over the last two decades, ML has transformed Google services including …
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What is really needed to make an existing 2D GAN 3D-aware? To answer this question, we modify a classical GAN, i.e., StyleGANv2, as little as possible. We find that only two modifications are absolutely necessary: 1) a multiplane image style generator branch which produces a set of alpha maps conditioned on their depth; 2) a …
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Texture cues on 3D objects are key to compelling visual representations, with the possibility to create high visual fidelity with inherent spatial consistency across different views. Since the availability of textured 3D shapes remains very limited, learning a 3D-supervised data-driven method that predicts a texture based on the 3D input is very challenging. We thus …
Read more “Texturify: Generating Textures on 3D Shape Surfaces”