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MLOps for Generative AI

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Deploying Generative AI in the Enterprise

The influx of new tools like ChatGPT spark the imagination and highlight the importance of Generative AI and foundation models as the basis for modern AI applications. However, the rise of generative AI also brings a new set of MLOps challenges. Challenges like handling massive amounts of data, large scale computation and memory, complex pipelines, transfer learning, extensive testing, monitoring, and so on.

In this 9 minute demo video, Iguazio CTO Yaron Haviv shares MLOps orchestration best practices and explores open source technologies available to help tackle these challenges. Haviv shows ways to enable your team to automate the continuous integration and deployment (CI/CD) of foundation models and transformers, along with the application logic, in production, and how to use GPUs to maximize application performance while protecting your investment in AI infrastructure. He also shares tips on what to look out for and how to make the whole process efficient, effective and collaborative.

Simplify your Gen AI Implementation

Interested in how you can scale, automate and accelerate your Gen AI project? Book a time to discuss your use case with our AI experts.