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.