Accelerating ML development with optimized performance and cost | C2C Community

Accelerating ML development with optimized performance and cost

  • 19 October 2022
  • 1 reply

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Successful machine learning deployments can depend on the ability of infrastructure to support the performance and budget requirements of a workload. Google’s open, flexible, and scalable AI infrastructure supports a wide variety of AI workloads, enabling customers to increase velocity to production, reduce costs, and to meet changing requirements over time. In this session, we discuss how to optimize across the AI stack with the latest GPUs and TPUs, fully-managed purpose-built AI infrastructure capabilities with Vertex AI, and state of the art solutions for demanding workloads. You'll also hear about how Uber, Cohere, Credit Karma, Arbor Biotechnologies and other enterprises are leveraging Google Cloud's AI Infrastructure to innovate, accelerate deployment, and drive business value.


Click on video below to watch it in detail:



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1 reply

Userlevel 7
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It’s always great to here the stories of other people.

It’s always great to hear their case studies and how they are using GC.

In this video we have 4 different companies, co:here, credit karma, arbor & Uber. 

Thanks for sharing it with us @malamin