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How Synamedia uses Amazon Rekognition Video to build advanced video search capabilities for long-form video

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 …

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Increase ML model performance and reduce training time using Amazon SageMaker built-in algorithms with pre-trained models

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 …

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InformedIQ automates verifications for Origence’s auto lending using machine learning

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 …

How our commitment to open source unlocks AI and ML innovation

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 …

Generative Multiplane Images: Making a 2D GAN 3D-Aware

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 …

Texturify: Generating Textures on 3D Shape Surfaces

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 …

How IBM Planning Analytics can help fix your supply chain

IBM Planning Analytics, or TM1 as it used to be known, has always been a powerful upgrade from spreadsheets for all kinds of planning and reporting use cases, including financial planning and analysis (FP&A), sales & operations planning (S&OP), and many aspects of supply chain planning (SCP). As far back as the 1990s and early …

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Prevent account takeover at login with the new Account Takeover Insights model in Amazon Fraud Detector

Digital is the new normal, and there’s no going back. Every year, consumers visit, on average, 191 websites or services requiring a user name and password, and the digital footprint is expected to grow exponentially. So much exposure naturally brings added risks like account takeover (ATO). Each year, bad actors compromise billions of accounts through …

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Metrics for evaluating content moderation in Amazon Rekognition and other content moderation services

Content moderation is the process of screening and monitoring user-generated content online. To provide a safe environment for both users and brands, platforms must moderate content to ensure that it falls within preestablished guidelines of acceptable behavior that are specific to the platform and its audience. When a platform moderates content, acceptable user-generated content (UGC) …

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Face-off Probability, part of NHL Edge IQ: Predicting face-off winners in real time during televised games

Face-off Probability is the National Hockey League’s (NHL) first advanced statistic using machine learning (ML) and artificial intelligence. It uses real-time Player and Puck Tracking (PPT) data to show viewers which player is likely to win a face-off before the puck is dropped, and provides broadcasters and viewers the opportunity to dive deeper into the …