Welcome to another episode of "Data Driven," where we dive into the ever-evolving world of data science, AI, and data engineering. Today's special guest is Inna Tokarev Sela, CEO and founder of Illumix. Join hosts Frank La Vigne, BAILeY, and Andy Leonard as they unpack Inna's groundbreaking insights into generative AI, the future of data management, and the intricacies of AI cost effectiveness.

Inna reveals the origin of her company's name, "Illumix," and discusses the pressing risks of 2025, particularly the total cost of ownership for managing generative AI. She highlights the inefficiencies of data customization and proposes a shift towards moving AI closer to the data to reduce costs. Through the unique lens of Illumix’s approach, Inna explains how they aim to illuminate organizational data by using a virtual semantic knowledge graph based on industry ontologies and business logic.

00:00 Ina Tokarav Sala: CEO of Illumix, AI readiness pioneer.

05:57 ROI and data are crucial for decisions.

08:56 Intermediate stage: copilots, insights, static dashboards persist.

11:12 Illumax targets structured data market, unlike others.

14:29 Bad data skews predictive analytics, causing errors.

19:48 Data modeling efficiency increases with virtual assistants.

22:33 E-commerce evolution: convenient online shopping preferred.

25:27 2025's biggest risk: High generative AI costs.

27:07 Focus on domain knowledge and metadata utilization.

31:44 Predicting patterns is profound, not crazy.

36:09 Industry trends are cyclical, like fashion trends.

37:49 Repatriating data due to AI cost efficiency.

40:47 Data processing everywhere raises security concerns.

45:00 Founder freedom: Experimentation unlike SAP's structure.

49:11 I'm considered controversial for being very visionary.

52:29 Truth's evolution parallels past technological shifts.

54:39 Frank's World: Kids show on recycling, BBC.

57:09 Thank you, Ina Tokarev Saleh, for insights.

Joining hosts Frank La Vigne and Andy Leonard, Geoff shares insights on the intersection of AI and creativity, the evolving landscape of careers in the age of artificial intelligence, and the crucial balance between innovation and traditional storytelling. We'll delve into AI's role in enhancing emotional connections with audiences, its potential to disrupt traditional media and consultancy services, and the caution needed to maintain authenticity and human touch amidst technological advances.

From amusing anecdotes about AI challenges in creative tasks to profound reflections on storytelling, this episode is a treasure trove for anyone intrigued by how emerging technologies are reshaping the arts and beyond. Stay tuned for inspiring discussions, engaging stories, and actionable insights—right here on "Data Driven".

Let's get started!

• Geoff's LinkedIn https://www.linkedin.com/in/geoffthatcher/

00:00 Jeff Thatcher revolutionizes experiences with AI innovations.

08:56 Storytelling is more important than technology investment.

13:38 Football field experience mimicking recruitment video reveal.

18:45 AI summaries risk losing creative inspiration.

22:21 AI enhances storytelling and client engagement passion.

31:49 Collaboration with LLMs enhances content drafting.

34:53 We integrated AI and illustrator for Christmas card.

43:03 AI empowers creativity, challenges traditional gatekeepers.

44:44 Simplicity aids decision-making; avoid complicating stories.

51:19 Slow drive through town renewed my soul.

56:26 Created AI color library to match teams.

01:01:30 Creativity requires discipline, connections, and stimulus.

Frank La Vigne sits down with Alex Gold, Head of Solutions Engineering at POSIT and author of "DevOps for Data Science."

Together, they explore the fascinating intersections of DevOps, MLOps, and generative AI, shedding light on the importance of social norms, innovation, and practical impact in open-source development.

• DevOps for Data Science (Online Version) https://do4ds.com
• DevOps for Data Science (Amazon)

02:14 Marylander love their state flag

06:09 PBC prioritizes diverse responsibilities beyond shareholder value.

08:17 Chose Python for its versatility across fields.

12:15 Choose the right language for each pipeline stage.

16:14 Deploying software for enterprise use requires oversight.

19:26 Most data scientists rarely focus on machine learning.

23:18 Machine learning misunderstood; majority use simple models.

26:46 Generative AI in big companies, production challenges.

28:30 DevOps for data science needs unique practices.

31:28 Focus on quick wins for business value.

34:05 Focus on relationships; people problems require empathy.

37:17 Technical people focus on solving technical problems.

42:53 Companies exploring gen AI strategies, co-pilot model prioritized.

45:01 Exploring gen AI for effective customer data use.

49:32 Progress continues despite leveling off in horsepower.

52:40 AI needs deeper integration for life-changing impact.

55:39 Upload content; create NPR-style podcast summary.

58:38 Thanks for tuning in! Stay data driven.