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Vertex AI Vision: Easily Build And Deploy Computer Vision Applications At Scale

  • aster.cloud
  • November 25, 2022
  • 3 minute read
If organizations can easily analyze unstructured data streams, like live video and images, they can more effectively leverage information from the physical world to create intelligent business applications. Retailers can improve shelf management by instantly spotting what products are out of stock, manufacturers can reduce product defects by detecting production errors in real time, and in our communities, administrators could improve traffic management by analyzing vehicle patterns. The possibilities to create new experiences, efficiencies, and insights are endless.However, enterprises struggle to ingest, process, and analyze real-time video feeds at scale due to high infrastructure costs, development effort, longer lead times, and technology complexities.That’s why last week, at Google Cloud Next’ 22, we launched the preview of Vertex AI Vision, a fully managed end-to-end application development environment that lets enterprises easily build, deploy, and manage computer vision applications for their unique needs. Our internal research shows that Vertex AI Vision can help developers reduce time to build computer vision applications from weeks to hours, at a fraction of the cost of current offerings. As always, our new AI products also adhere to our AI Principles.

One-stop environment for computer vision applications development

Vertex AI Vision radically simplifies the process of cost-effectively creating and managing computer vision apps, from ingestion and analysis to deployment and storage. It does so by providing an integrated environment that includes all the tools needed to develop computer vision applications; developers can easily ingest live video streams (all they need is the IP address), add pre-trained models for common tasks such as “Occupancy Analytics,” “PPE Detection,” “Visual Inspection,” add custom models from Vertex AI for specialized tasks, and define a target location for output/ analytics. The application is ready to go.

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Vertex AI Vision comprises the following services:


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  • Vertex AI Vision Streams: a geo-distributed managed endpoint service for ingesting video streams & images. Easily connect cameras or devices from anywhere in the world and let Google handle ingestion and scaling
  • Vertex AI Vision Applications: a serverless orchestration platform for video models & services enabling developers to stitch together large, auto-scaled media processing and analytics pipelines
  • Vertex AI Vision Models: a new portfolio of specialized pre-built vision models for common analytics tasks including occupancy counting, PPE detection, face-blurring, retail product recognition and more. Additionally, users can build and deploy their own custom models
  • Vertex AI Vision Warehouse: a serverless rich-media storage that provides the best of Google search combined with managed video storage. Perfect for ingesting, storing, and searching PBs of video data.

Customers are already seeing the future with Vertex AI Vision

Customers are thrilled with the possibilities Vertex AI Vision opens. According to Elizabeth Spears, Co-Founder & CPO, Plainsight, a leading developer of computer vision applications, “Vertex AI Vision is changing the game for use cases that for us have previously been economically non-viable at scale. The ability to run computer vision models on streaming video with up to a 100X cost reduction for Plainsight is creating entirely new business opportunities for our customers.”

Similarly, Brain Corp Vice President Botond Szatmáry said, “Vertex AI Vision is the backend solution that enables Brain Corp’s Shelf Analytics on all BrainOS powered robots, including a new commercial ready reference platform that’s purpose built for end to end inventory analytics. The Vertex AI Product Recognizer and Shelf Recognizer, combined with BigQuery, enable us to efficiently detect products, out of stock events, and low stock events while capturing products, prices, and location within stores and warehouses. Our retail customers can be more competitive in e-commerce, better manage their inventory, improve operational efficiencies, and improve the customer shopping experience with our highly accurate, actionable, and localized inventory shelf insights.”

Read More  Google Cloud’s Security And Resiliency Measures For Customers And Partners

You can hear more from Plainsight and Brain Corp in our Next ’22 session. If you are a developer and want to get started on Vertex AI Vision I invite you to experience the magic for yourself here.

 

By: Vishy Tirumalashetty (Head of Product, Vertex AI Vision)
Source: Google Cloud Blog


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Related Topics
  • Application Deployment
  • Artificial Intelligence
  • Google Cloud
  • Machine Learning
  • Vertex AI
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