Session Outline
Generative AI is revolutionizing data interaction, unleashing new use cases. Yet, there remains uncertainty about leveraging this technology with production data. Let’s explore the evolution of traditional architectures to accommodate generative AI and the associated risks in this integration.
Key Takeaways
- Evolution of data warehouses and data lakes to leverage generative content capabilities
- Challenges when using LLMs with data
- Sustainability, beyond mere financial considerations
In a Hyperight Data Talks interview, we speak with Sina Nek Akhtar, Tech Lead, Data Analytics and ML at Google Cloud! During our discussion, we cover new AI developments that enable deeper experimentation. How multimodality lets AI process information like images, videos, and code, giving it superhuman perception. How Google Gemini‘s expanded context windows enhance AI’s ability to summarize thousands of pages of documents and analyze tens of thousands of lines of code. How to choose the right tool for the job and why we should think platform-first rather than model-first.