Jenny Tsai

In this podcast, Google Cloud's Oliver Parker vice president, global generative AI GTM, and Miku Jha, director, AI/ML and generative AI partner engineering, sit down with Bob Evans to talk about how businesses can safely and efficiently scale their generative AI efforts, focusing on high-value opportunities while leveraging Google Cloud’s open platform, extensive ecosystem, and advanced AI/ML capabilities to deliver meaningful results for clients. Scaling Generative AI The Big Themes: Prioritizing cost and impact: Businesses are focused on the dual priorities of cost efficiency and impactful results when implementing generative AI. With numerous potential applications for generative AI, organizations need to evaluate which projects will deliver the highest value. This approach involves collaborating with partners to identify the opportunities that offer the most substantial benefits. Open ecosystem advantage: Google Cloud’s emphasis on openness and flexibility is a key differentiator in the AI landscape. Its commitment to open systems and platforms allows for various models and technologies, including first-party and open-source offerings. This open ecosystem approach enables businesses to leverage various AI models and infrastructure options, enhancing scalability and adaptability. End-to-end offerings: Google Cloud offers a comprehensive AI stack that supports a wide range of applications, from foundational models to advanced infrastructure. This end-to-end tool facilitates the development and scaling of sophisticated AI applications. The integration of various layers, including model capabilities, hardware options, and platform services, enables partners to deliver efficient and effective AI offerings. The Big Quote: “Having great models is one thing, but having differentiated infrastructure and a platform — all those three things come together, and I think we are unique in that sense.” More from Google Cloud: Learn more about Google Cloud and AI.

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