197: Deep Dive: How to Build AI Features and Why it is So Dang Hard with Barry McCardle of Hex
Jul 10, 2024
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AI expert Barry McCardle discusses challenges in building AI features, benchmarking AI models, and AI integration in products. Topics include AI development struggles, determinstic template selection, and open source database success. The podcast also covers market dynamics, enterprise adoption, and the fun side of product launch videos.
Hex focuses on AI-driven features for collaborative data analysis.
Hex confronts challenges in AI model benchmarking and uncertainty handling.
The data space sees consolidation and competition, impacting industry dynamics.
Deep dives
Hex: A Collaborative Data Science Platform
Hex is a collaborative platform for data science and analytics designed to unite teams and workflows in a more flexible and integrated way than traditional tools. The platform aims to solve the gap observed in data work at organizations where most of the data analysis occurs outside of dashboard-centric BI tools. By offering a multimodal product, Hex enables users to mix Python and SQL seamlessly, enhancing workflows and promoting collaboration within data teams.
AI Integration and Product Updates in Hex
Within the past year and a half, Hex introduced AI assist features known as 'magic features,' enabling users to leverage a suite of no-code tools like charts, pivots, and filters in data analysis. The platform expanded to include spreadsheet functions in table cells, facilitating end-to-end no-code workflows. Hex's focus on governance tools aims to broaden access to data workflows while empowering core data teams in making critical business decisions.
Challenges in AI Implementation and AI-Driven Workflows
Hex's AI-driven editing feature faced challenges in generating coherent chains of cells, leading to the need for predefined templates and manual selection based on user instructions. The platform's evaluation of AI models revealed the complexities in benchmarking different models and the importance of contextual prompts for generating accurate responses. Despite advancements in AI models, navigating uncertainties and expressing model uncertainty remain critical aspects in AI implementation to enhance user experience and productivity.
Incorporating AI into Product Development
The podcast delves into the significance of incorporating AI into product development for data practitioners. By targeting users who typically work with SQL and Python, the product allows for imperfections as long as it remains useful and facilitates insights. The iterative process enables the incorporation of AI while maintaining usability for practitioners even if the AI tools may not be flawless, thereby enhancing user experience and product enhancement.
Consolidation and Competition in Data Space
The discussion extends to the evolving landscape within the data space, emphasizing the trend towards consolidation and competition among industry players. Observations point towards a potential era of consolidation where winners and losers emerge across different layers of the data stack. Key players like Snowflake, Databricks, and other independent vendors are scrutinized within the context of market dynamics, highlighting the strategic partnerships, competition, and the imminent shifts expected in the data industry.
Deterministic template selection and AI model uncertainty (36:21)
Infrastructure for AI experimentation and evaluation (40:11)
Consolidation and competition in the data stack industry (42:27)
Data gravity, integration, and market dynamics (47:12)
Enterprise adoption and the bundling and unbundling of platforms (51:03)
The open source databases and the middle ground (53:18)
Building successful open source businesses (57:00)
The fun approach to product launch video (1:01:14)
Final thoughts and takeaways (01:03:15)
The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.
RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.
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