Implementing Gen AI in Practice

Across the industry, organizations are attempting to find ways to implement generative AI in their business and operations. But doing so requires significant engineering, quality data and overcoming risks. In this blog post, we show all the elements and practices you need to to take to productize LLMs and generative AI. You can watch the full talk this blog post is based on, which took place at ODSC West 2023, here.

Harness the Power of Outcomes: Solve Problems, Drive Success

You will see how Qlik works where and how you work, whether you are on a computer or mobile device You will see how I use AI and conversational analytics to collaborate in real-time with my colleagues to get context to help me explore my business problem further and how I can take action on my findings immediately by notifying and integrating with my valued partners, all from one platform. I even use a little generative AI with Amazon Bedrock as a fun example to show you the art of the possible.

Setting up and Getting Started with Cloudera's New SQL AI Assistant

As described in our recent blog post, an SQL AI Assistant has been integrated into Hue with the capability to leverage the power of large language models (LLMs) for a number of SQL tasks. It can help you to create, edit, optimize, fix, and succinctly summarize queries using natural language. This is a real game-changer for data analysts on all levels and will make SQL development faster, easier, and less error-prone.