Andy Leonard and Frank La Vigne delve into the exciting world of AI and growth marketing with the renowned Lillian Pierson. Lillian, a globally recognized AI growth strategist and author. She shares her unique journey from engineering to data science and her role as a fractional CMO. She provides deep insights into leveraging AI to revolutionize marketing and growth strategies, discusses breaking down the barriers in early data science, and explores the rise of agentic AI.

This conversation is filled with valuable knowledge, humor, and a reality check on the evolving tech landscape. Tune in to explore how AI and data-driven approaches are transforming industries and why Data Driven is a top pick for AI enthusiasts.

00:00 "Interview with AI Expert Lillian Pearson"

04:18 Earning a Professional Engineering License

09:21 Evolution of Data Science Disciplines

11:08 Career Pivot to Success

14:01 Data Strategy and AI Insights

19:19 Marketing's Role in Product Growth

21:58 Customer Advocacy in Product Development

26:16 Exploring AI for Content Automation

28:28 OpenAI Trained on My Style

30:51 Frank's Podcast Automation Expansion

33:22 "Delegation vs. Self-Management Discussion"

37:45 Decoupled, Resilient System Communication

41:57 Clay-Powered Decision Tech Critique

45:41 AI Is Essential in Business

49:09 Debating with ChatGPT's Perspectives

50:23 Google AI: Generative Podcast Tool

56:11 Big Data Fallacies Explored

Today, we've got an exciting episode lined up for you. Hosts Frank La Vigne and Bailey dive deep into the tech universe with Dean Guida, the CEO and founder of Infragistics. Dean brings his 35-year journey and expansive experience in technology to the table, reminiscing about the early days of software development and his transition into the data-driven world.

In this conversation, you'll hear about the evolution of Infragistics from building UI components for Windows to creating sophisticated data analytics and AI tools. Dean also shares insights from his new book, "When Grit is Not Enough," focusing on how entrepreneurs can foster agile, data-driven learning organizations. Whether you're a seasoned developer, a budding entrepreneur, or someone fascinated by the intersection of AI and data, this episode promises a wealth of knowledge and inspiration.

Join us as we explore technology old and new, from the bygone era of Windows 3.0 to the cutting-edge capabilities of AI today. Plus, hear Dean's personal journey of navigating through various technological and economic shifts over the decades. Make sure to tune in for a discussion that bridges the past, present, and future of tech innovation!

00:00 35 Years of UI/UX Innovation

06:35 "Simplicity, Beauty, and Conversational AI"

15:29 Enhancing User Trust Through Transparency

19:52 AI-Driven Learning and OKR Management

26:20 Kids Reflecting Tech Evolution

27:12 "AI in Future Work Environments"

33:14 "Data-Driven Leadership and Team Alignment"

38:44 Entrepreneurship Beyond Grinding

48:19 Contextual Understanding in AI Assistants

51:57 Overprotected Generation's Communication Challenges

54:55 Generational Impact of Pandemics

01:00:47 "Data-Driven Podcast: Ranked 38"

Today, we delve into the intriguing world of vector databases, retrieval augmented generation, and a surprising twist—origami.

Our special guest, Arjun Patel, a developer advocate at Pinecone, will be walking us through his mission to make vector databases and semantic search more accessible. Alongside his impressive technical expertise, Arjun is also a self-taught origami artist with a background in statistics from the University of Chicago. Together with co-host Frank La Vigne, we explore Arjun’s unique journey from making speech coaching accessible with AI at Speeko to detecting AI-generated content at Appen.

In this episode, get ready to unravel the mysteries of natural language processing, understand the impact of the attention mechanism in transformers, and discover how AI can even assist in the art of paper folding. From discussing the nuances of RAG systems to sharing personal insights on learning and technology, we promise a session that’s both enlightening and entertaining. So sit back, relax, and get ready to fold your way into the fascinating layers of AI with Arjun Patel on Data Driven.

00:00 Arjun Patel: Bridging AI & Education

04:39 Traditional NLP and Geometric Models

08:40 Co-occurrence and Meaning in Text

13:14 Masked Language Modeling Success

16:50 Understanding Tokenization in AI Models

18:12 "Understanding Large Language Models"

22:43 Instruction-Following vs Few-Shot Learning

26:43 "Rel AI: Open Source Data Tool"

31:14 "Retrieval-Augmented Generation Explained"

33:58 "Pinecone: Efficient Vector Database"

37:31 "AI Found Me: Intern to Innovator"

41:10 "Impact of Code Generation Models"

45:25 Personalized Learning Path Technology

46:57 Mathematical Complexity in Origami Design

50:32 "Data, AI, and Origami Insights"

In today's episode, we're thrilled to have Niv Braun, co-founder and CEO of Noma Security, join us as we tackle some pressing issues in AI security.

With the rapid adoption of generative AI technologies, the landscape of data security is evolving at breakneck speed. We'll explore the increasing need to secure systems that handle sensitive AI data and pipelines, the rise of AI security careers, and the looming threats of adversarial attacks, model "hallucinations," and more. Niv will share his insights on how companies like Noma Security are working tirelessly to mitigate these risks without hindering innovation.

We'll also dive into real-world incidents, such as compromised open-source models and the infamous PyTorch breach, to illustrate the critical need for improved security measures. From the importance of continuous monitoring to the development of safer formats and the adoption of a zero trust approach, this episode is packed with valuable advice for organizations navigating the complex world of AI security.

So, whether you're a data scientist, AI engineer, or simply an enthusiast eager to learn more about the intersection of AI and security, this episode promises to offer a wealth of information and practical tips to help you stay ahead in this rapidly changing field. Tune in and join the conversation as we uncover the state of AI security and what it means for the future of technology.

00:00 Security spotlight shifts to data and AI.

03:36 Protect against misconfigurations, adversarial attacks, new risks.

09:17 Compromised model with undetectable data leaks.

12:07 Manual parsing needed for valid, malicious code detection.

15:44 Concerns over Agiface models may affect jobs.

20:00 Combines self-developed and third-party AI models.

20:55 Ensure models don't use sensitive or unauthorized data.

25:55 Zero Trust: mindset, philosophy, implementation, security framework.

30:51 LLM attacks will have significantly higher impact.

34:23 Need better security awareness, exposed secrets risk.

35:50 Be organized with visibility and governance.

39:51 Red teaming for AI security and safety.

44:33 Gen AI primarily used by consumers, not businesses.

47:57 Providing model guardrails and runtime protection services.

50:53 Ensure flexible, configurable architecture for varied needs.

52:35 AI, security, innovation discussed by Niamh Braun.

In this livestream, Frank and Andy discuss the timeless nature of backend enterprise tech, that, much like a Christmas special from decades ago, is still very much celebrated.

00:00 Exploring SSIS future in a festive episode.

08:28 Data engineering evolved from business intelligence systems.

10:57 Social networks project before Facebook's popularity.

19:19 SSIS training informed data engineering concepts teaching.

24:56 Bill Gates moved project to immature Microsoft tooling.

29:10 Data engineering possible in 2024 using T-SQL.

35:23 Huge cloud companies surpass previous brick-and-mortar giants.

40:10 Old technologies endure; misconceptions about their age.

46:03 Evaluate change benefits: technical ease, business growth.

52:30 Cloud departure interests rise, SSIS assistance sought.

55:47 Big government agency utilizing diverse cloud platforms.

01:00:59 Security is crucial; clients' preferences vary.

01:08:56 Certification issues hinder software updates and compliance.

01:10:02 People stick with older systems for reasons.

01:15:15 Proper GPU driver drastically improved loading time.

01:22:16 Repost increased engagement and communication with author.

01:25:45 Data scientists should learn SQL for simplicity.

01:31:06 Obsolete systems cause issues without quotes.

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.