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Aible is the leader in generating business impact from AI in less than 30 days by helping teams go from raw data to business value with solutions for customer acquisition, churn prevention, demand prediction, preventative maintenance, and more. These solutions help IT and data teams identify valuable data through automated data validation, enabling collaborative open-world …
Surfers, swimmers and beachgoers face a hidden danger in the ocean: rip currents. These narrow channels of water can flow away from the shore at speeds up to 2.5 meters per second, making them one of the biggest safety risks for those enjoying the ocean. To help keep beachgoers safe, Christo Rautenbach, a coastal and …
Read more “Making a Splash: AI Can Help Protect Ocean Goers From Deadly Rips”
Posted by Kendra Byrne, Senior Product Manager, and Jie Tan, Staff Research Scientist, Robotics at Google (This is Part 6 in our series of posts covering different topical areas of research at Google. You can find other posts in the series here.) Within our lifetimes, we will see robotic technologies that can help with everyday …
Amazon Kendra is an intelligent search service powered by machine learning (ML). It indexes the documents stored in a wide range of repositories and finds the most relevant document based on the keywords or natural language questions the user has searched for. In some scenarios, you need the search results to be filtered based on …
Could an app tell if a first date is just not that into you? Engineers say the technology might not be far off. They trained a computer to identify the type of conversation two people were having based on their physiological responses alone.
Lack of diversity in data collection has caused significant failures in machine learning (ML) applications. While ML developers perform post-collection interventions, these are time intensive and rarely comprehensive. Thus, new methods to track and manage data collection, iteration, and model training are necessary for evaluating whether datasets reflect real world variability. We present designing data, …
Read more “Designing Data: Proactive Data Collection and Iteration for Machine Learning”
By Gustavo Carmo, Elliot Chow, Nagendra Kamath, Akshay Modi, Jason Ge, Wenbing Bai, Jackson de Campos, Lingyi Liu, Pablo Delgado, Meenakshi Jindal, Boris Chen, Vi Iyengar, Kelli Griggs, Amir Ziai, Prasanna Padmanabhan, and Hossein Taghavi Figure 1 – Media Machine Learning Infrastructure Introduction In 2007, Netflix started offering streaming alongside its DVD shipping services. As the …
This post is co-written by Zdenko Estok, Cloud Architect at Accenture and Sakar Selimcan, DeepRacer SME at Accenture. With the increasing use of artificial intelligence (AI) and machine learning (ML) for a vast majority of industries (ranging from healthcare to insurance, from manufacturing to marketing), the primary focus shifts to efficiency when building and training …
Read more “Configure an AWS DeepRacer environment for training and log analysis using the AWS CDK”
Posted by Vahab Mirrokni, VP and Google Fellow, Google Research (This is Part 5 in our series of posts covering different topical areas of research at Google. You can find other posts in the series here.) Robust algorithm design is the backbone of systems across Google, particularly for our ML and AI models. Hence, developing …
Read more “Google Research, 2022 & beyond: Algorithmic advances”
This post is co-written with Jonathan Jung, Mike Band, Michael Chi, and Thompson Bliss at the National Football League. A coverage scheme refers to the rules and responsibilities of each football defender tasked with stopping an offensive pass. It is at the core of understanding and analyzing any football defensive strategy. Classifying the coverage scheme …
Read more “Identifying defense coverage schemes in NFL’s Next Gen Stats”