In this podcast, the hosts discuss the future of AI in the data platform space, exploring the definition of AI and its current features. They also examine the integration of AI with SQL Server, the differences between using and feeding AI models, experiences and concerns with using chat GPT, the current state of AI and its implications, and changing careers and bucket list dreams.
AI can be used to automate tasks like generating code or writing recommendation letters, but validation and expertise are crucial to ensure accuracy.
Different levels of utilizing AI exist, ranging from cautious usage for individuals with limited knowledge to more advanced tasks requiring validation and expertise.
Deep dives
The potential of AI and its integration with SQL Server
The podcast episode explores the potential of AI and its integration with SQL Server. It is mentioned that companies are using AI as a tool to enhance productivity and efficiency. One specific example is the use of generative AI models to automate tasks such as writing recommendation letters or generating SQL code. The discussion emphasizes that these models are not perfect and require validation, especially in complex domains like mathematics or law. The episode also highlights the importance of being cautious with proprietary information and complying with legal requirements. The upcoming developments in AI tools and their integration into Microsoft services are mentioned, opening possibilities for data-driven prompts and integration with Office 365. Overall, the episode provides insights into the current state and future prospects of AI integration with SQL Server.
Different levels of AI utilization for various skill sets
The speaker discusses different levels of utilizing AI based on individual skill sets and familiarity with specific domains. Level one refers to situations where individuals have limited knowledge and should be cautious when using AI. Level two involves using AI for specific tasks or generating terse statements in areas where individuals already have some familiarity, such as CSS coding or generating HTML templates. Level three is about utilizing AI for more advanced or specialized tasks, such as statistical modeling or transforming code between programming languages. The speaker highlights the importance of validation and expertise while using AI to ensure accuracy and prevent reliance on incorrect or incomplete information.
Benefits and limitations of using AI in various domains
The podcast explores the benefits and limitations of using AI in different domains. It is mentioned that AI tools can provide time-saving benefits, such as generating code or automating specific tasks like writing contracts or creating business slogans. The discussion emphasizes the need for domain-specific knowledge and validation, as AI models have limitations and can generate incorrect or unrealistic suggestions. Specific examples are given, showcasing how AI can be useful in generating DAX queries from Tableau syntax or assisting in tabletop RPG rule creation. The speaker highlights the importance of understanding the strengths and weaknesses of AI models and making informed decisions about their utilization based on specific needs and domains.
Future prospects and considerations with AI integration
The podcast episode touches on future prospects and considerations associated with AI integration. It mentions the $10 billion investment by Microsoft in OpenAI and the potential future integration of AI models into various Microsoft services. The speaker also discusses the challenges and legal aspects related to using AI prompts and the potential risks of proprietary information leakage. The episode highlights the need to regularly review terms and conditions for AI services and ongoing litigation related to licensing and intellectual property issues. The discussion ends with the possibility of future AI tools being developed specifically for SQL Server and the potential benefits and considerations associated with such developments.
We love hearing from our listeners!!! In this episode, a long-time listener asked about the future of AI in the data platform space. We thought this was a very interesting topic as Microsoft has been including Artificial Intelligence or AI in more and more of its marketing material. In this episode we'll dive into the definition of AI, what features are currently available, how we can leverage those technologies, and where we think this might go in the future. One of the challenges we currently face is all the buzz and excitement around AI. From a data platform vantage point, we started with analytics and training models to analyze the data. Microsoft has suddenly slapped Artificial Intelligence on some of the feature sets and confuses the issue a bit.
We are excited to have Mike Chrestensen from Duke Health as our episode guest to help us sort it all out. Mike has begun leveraging AI in his work and I think he gives some interesting thoughts on how he has used it to help his team go faster. We hope you enjoy the episode. As always, we welcome your feedback and thoughts.
