Posts in tag

BigQuery ML


AI is at a tipping point. We are seeing the impact of AI across more and more industries and use cases. Organizations with varying levels of ML expertise are solving business-critical problems with AI — from creating compelling customer experiences, to optimizing operations, to automating routine tasks, these organizations learn to innovate faster and ultimately, …

Over one third of organizations believe that data analytics and machine learning have the most potential to significantly alter the way they run business over the next 3 to 5 years. However, only 26% of organizations are data driven. One of the biggest reasons for this gap is that a major portion of the data generated today is …

“Cloud Wisdom Weekly: for tech companies and startups” is a new blog series we’re running this fall to answer common questions our tech and startup customers ask us about how to build apps faster, smarter, and cheaper. In this installment, we explore how to leverage artificial intelligence (AI) and machine learning (ML) for faster innovation …

Alphabet CEO Sundar Pichai has compared the potential impact of artificial intelligence (AI) to the impact of electricity—so it may be no surprise that at Google Cloud, we expect to see increased AI and machine learning (ML) momentum across the spectrum of users and use cases. Some of the momentum is more foundational, such as the hundreds …

Gartner® named Google as a Leader in the 2022 Magic Quadrant™ for Cloud AI Developer Services report. This evaluation covered Google’s language, vision and structured data products including AutoML, all of which we deliver through Google Cloud. We believe this recognition is a reflection of the confidence and satisfaction that customers have in our language, …

Bringing AI models to a production environment is one of the biggest challenges of AI practitioners. Much of the discussions in the AI/ML space revolve around model development. As shown in this diagram from the canonical Google paper “Hidden Technical Debt in Machine Learning Systems”, the bulk of activities, time and expense in building and …

Editor’s note: This post features third party projects built with AI Platform. At Google I/O on May 18, 2021 Google Cloud announced Vertex AI, a unified UI for the entire ML workflow, which includes equivalent functionality from the AI Platform and new MLOps services. Most of the sample code and materials introduced in this post …

Google Cloud is offering no-cost training opportunities to help you gain the latest AI and machine learning skills. You’ll have a chance to learn more about the new Document AI along with Explainable AI, Looker, BigQuery ML, and Dialogflow CX. Document AI The new Document AI (DocAI) platform, a unified console for document processing, became …

We launched BigQuery ML, an integrated part of Google Cloud’s BigQuery data warehouse, in 2018 as a SQL interface for training and using linear models. Many customers with a large amount of data in BigQuery started using BigQuery ML to remove the need for data ETL, since it brought ML directly to their stored data. Due …

An organization’s ability to quickly detect and respond to anomalies is critical to success in a digitally transforming culture. Google Cloud customers can strengthen this ability by using rich artificial intelligence and machine learning (AI/ML) capabilities in conjunction with an enterprise-class streaming analytics platform. We refer to this combination of fast data and advanced analytics as real-time AI. There are …