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.

Today, Frank and Andy are joined by David Hirschfeld, CEO and founder of Tekyz Corporation, a firm specializing in helping startups and saving troubled projects with his unique "Launch First" methodology.

David brings us into his world of startups, where, believe it or not, he advocates for getting customers before you even build the product! He explains how Launch First combines high-fidelity prototypes, niche targeting, and a lean, marketing-first approach to de-risk software launches and prove real demand.

Whether you’re an engineer turned entrepreneur, or just curious about the art and science of startups, buckle up for an enlightening episode with insights on maximizing impact and proving product-market fit with speed and precision. Let’s dive in!

00:00 Launch First: Get customers before building product.

06:00 Market first, then build software; analyze niche.

07:04 Create marketing stack, offer lifetime license, guarantee refund.

10:30 Offer lifetime licenses for upfront subscription payments.

16:39 Identify top niche problems and assess impact.

19:29 Paying customers prove genuine interest and commitment.

23:34 Accidentally created first Windows software for industry.

25:52 Failed to monetize social media product, Klooj.

30:28 Red Hat's AI boosts chatbot data efficiency.

33:05 Exceptional teams produce highly detailed, compliant documentation.

34:52 Responsibility depends on knowledge and access.

40:29 Track time daily, categorize by client, invoice monthly.

42:37 Handoff documentation to Google; received positive feedback.

45:59 Impressed, thought price was reasonable, despite expectations.

48:11 Combining disciplines multiplies value exponentially.

51:56 David Hirschfeld discusses startup success strategies.

Today, we have a special treat for you as we welcome Candice Gillhooley, a dynamic force known for blending technical prowess with marketing brilliance. In this episode, we'll explore Candice's groundbreaking approach to "sentient marketing," dive into the interplay between AI and targeted audience communication, and discuss the importance of understanding behavioral data to craft unforgettable marketing experiences. So, sit back, relax, and get ready for an episode that's sure to spark new ideas and inspire innovation.

• Buy the book on Amazon: https://qrcodes.at/SentientMarketingBook
• https://sentientmarketingbook.com/
• Candace's LinkedIn Profile https://www.linkedin.com/in/candacegillhoolley/

00:00 Podcast explores data science, AI, engineering trends.

05:05 Ancient harvest tradition, winter preparation, birthdays coinciding.

06:46 Target audience insights through effective data utilization.

13:17 Enjoys startup vibes, marketing tech innovations.

15:36 Data-driven marketing is essential for organizational success.

20:27 Martha Stewart's over-the-top American Express commercial.

22:22 Impressed by her reinvention despite past challenges.

26:31 Glimmers evoke deep, happy memories and connections.

29:37 Advertising targets varied generations differently nowadays.

32:32 Tech changes: fascinating generational shifts, CD nostalgia.

36:11 SQL Server generations discussed at SQL Saturday.

39:47 Marketing tech evolves rapidly; cloud frenzy over.

41:52 Hybrid cloud trend emerged after market saturation.

44:33 Enjoying feedback from Andy about my work.

49:28 Personality divergence; traditionalism conflicts with change.

50:48 Neurodiverse individuals face job dissatisfaction challenges.

54:55 Discussed AI-driven marketing with Candice Gillhooley.

Andy Leonard and Frank La Vigne are joined by experts Baruch Lev and Feng Gu to uncover the complexities and pitfalls of mergers and acquisitions. We'll discuss the controversial "killer acquisitions" in the pharmaceutical industry, which regulators fear stifle innovation and harm public health.

Our guests will share insights from their upcoming book, "The M&A Failure Trap," which critiques current acquisition strategies and introduces a unique 10-factor scorecard for assessing potential success. From data analysis on 40,000 mergers over 40 years to the challenges and market trends affecting merger outcomes, we’ll explore why up to 75% of mergers fail and how decision-makers often benefit at the expense of employees and shareholders.

Whether you're an entrepreneur looking to navigate M&As or a data enthusiast curious about the numbers behind these strategic moves, this episode offers a data-driven look at the forces shaping mergers and their real-world impacts.

The M&A Trap Book Link (no affiliate) https://www.amazon.com/Failure-Trap-Mergers-Acquisitions-Succeed/dp/1394204760

00:00 Exploring data science, AI, mergers with experts.

04:43 Extensive data-driven analysis of mergers' failures.

09:22 Investment bankers pressure companies to finalize acquisitions.

11:15 Managers get bonuses for concluding acquisition deals.

14:26 Global economy affected; star performers leave.

17:32 Mergers often lead to employee departures, layoffs.

20:24 Managed data engineering team during Unisys acquisition.

26:28 Analogies highlight misapplication of causal thinking.

28:58 Complex model reveals hidden variable impact.

31:01 Correlation can mislead; avoid single-focus traps.

37:14 Comprehensive analysis of acquisitions and their impacts.

38:39 Analyzed LinkedIn data on employee turnover trends.

41:50 Creative metric developed for private acquisition premium.

46:01 Acquisitions are widespread, impacting various industries significantly.

52:11 Unique 10-factor acquisition scorecard predicts success.

55:45 Deep dive into mergers and acquisitions data.

Baruch Lev is a professor emeritus at NYU Stern School of Business, where he has taught and conducted research on mergers and acquisitions for decades. He worked formerly at UC Berkeley and the University of Chicago. His work has been widely cited in academic and professional circles (over 63,000 Google Scholar citations), and he is a leading authority on corporate finance and valuation.

Feng Gu is a professor of accounting at the University at Buffalo and has extensive experience in analyzing the financial aspects of corporate acquisitions. His research focuses on the economic consequences of corporate decisions and has been published in top-tier academic journals.