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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 …
Read more “How our commitment to open source unlocks AI and ML innovation”
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 …
Read more “Generative Multiplane Images: Making a 2D GAN 3D-Aware”
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”
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 …
Read more “How IBM Planning Analytics can help fix your supply chain”
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 …
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) …
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 …
Thanks to earbuds, people can take calls anywhere, while doing anything. The problem: those on the other end of the call can hear all the background noise, too, whether it’s the roommate’s vacuum cleaner or neighboring conversations at a café. Now, work by a trio of graduate students at the University of Washington, who spent …
Read more “Researchers Use AI to Help Earbud Users Mute Background Noise”