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Google is named a Leader in the 2023 Gartner® Magic Quadrant™ for Cloud AI Developer Services report

Gartner has named Google a Leader in the2023 Gartner® Magic Quadrant™ for Cloud AI Developer Services (CAIDS). This is the fourth year in a row that Google has been named a Leader and we believe this is because of Google Cloud’s portfolio being one of the most comprehensive and innovative in the market for developers.

From the legion of Vertex AI services, to our pre-trained AI APIs and new generative AI products, Google Cloud’s leadership in the market is a testament to Google’s commitment to innovation and focus on helping developers build AI-powered applications. Not only do we build cool stuff, we are committed to developing and deploying AI in a way that is in accordance with our Responsible AI principles. 

Strength in Large Models

Google Cloud’s AI tools are built and trained on Google’s industry-leading breakthroughs in large language models, including our work in Transformer and diffusion models. Trained on immensely large datasets, the billion-parameter large models that power many of our developer tools cover a wide range of AI capabilities including natural language processing, translation, automatic speech recognition, image recognition, and more. Our current tools including Vertex AI, AutoML, and our pre-trained AI APIs help developers with limited AI/ML backgrounds build high-quality AI applications in little to no time leveraging the latest AI technology coming out of Google. 

We are excited to continue bringing the best of Google’s research and advancements in large models to our developers and data scientists through new services including our PaLM API, generative AI support in Vertex AI and Gen App Builder. Building on our investments and innovations in AI, our recently announced generative AI offerings are designed to help developers and data scientists unlock the power of generative AI leveraging the strength of large models and Google’s leadership in AI. 

Unified approach to data and AI 

We’ve learned from Google’s years of experience in AI development on how to make the data-to-AI journey as seamless as possible and we’ve poured this experience into our products and services. Vertex AI is tightly integrated across Google’s data cloud enabling data practitioners to accelerate data science workflows and deliver more value from data. Vertex AI’s singular notebook experience simplifies work across data and AI workloads. Powerful AI/ML capabilities are easily accessible from the notebook making it possible to extract features from unstructured data and deepen insights across data types. When you want to use your data to build custom models, Vertex AI provides a range of tools to build, deploy and manage ML models, minimizing data movement. BigQuery ML for SQL practitioners, AutoML for low code development, and Vertex AI’s managed training service to operationalize large scale model training provide choice and meet users where they are with their current skills. Built-in MLOps tools work across training capabilities, removing the complexity of deploying, managing and maintaining models. 

Enterprise-grade MLOps

Google Cloud’s enterprise-grade MLOps platform helps practitioners build, deploy, and manage machine learning models at scale for enhanced stability, reliability, and team productivity. With MLOps, customers can build a unified data to AI platform; train and serve models with little to no AI expertise; build advanced models with custom tooling; and use fully managed services to manage and govern the entire model lifecycle. From data to deployment, Vertex AI’s MLOps services ensure that users are well-equipped to manage, monitor, govern, and explain the entire ML development lifecycle. 

For example, AI accounting startup, Digits, is leveraging Google Cloud AI to make the full accounting pipeline faster and more efficient. “[Vertex AI] Pipelines let us move faster from ML prototypes to production models, and give us confidence that our ML infrastructure will keep pace with our transaction volume as we scale.” By embracing Vertex AI, Digits was able to free up resources and talent so they could focus on building innovative ML models and products, instead of managing infrastructure, workflows, and other MLOps tasks. 

Through its end-to-end set of tools and services for model management, Vertex AI helps practitioners easily utilize their data to produce enterprise-grade models while also reducing the time to business value for the organization. 

Read the full report and get started with Google Cloud AI 

Google Cloud is committed to democratizing AI and helping organizations build and deploy the AI-powered applications that are changing the world today. We are investing heavily in bringing new generative AI offerings for developers and are focused on continuing to innovate with developers in mind to help them leverage the latest AI technology. To download the full report, click here, and for more information on our new generative AI offerings see here.

Gartner, Magic Quadrant for Cloud AI Developer Services, Jim Scheibmeir, Arun Batchu, Van L Baker, Frank O’Connor, Mike Fang, Svetlana Sicular. May 2023. GARTNER is a registered trademark and service mark of Gartner and Magic Quadrant is a registered trademark of Gartner Inc, and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Google. 

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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