Partially Redacted: Data, AI, Security, and Privacy Skyflow

In this episode, Sean is joined by Eric Dodds, Head of Product Marketing at RudderStack, to dive into the world of data management, data pipelines, and common data mistakes. Eric shares his insights on when organizations should transition from basic tools like spreadsheets to a more sophisticated data stack, including data warehouses and modern tooling.
They discuss the challenges businesses face in data management, specifically about coming up with a common set of definitions that an organization is aligned around. They also discuss how to address these issues, and the importance of secure handling of customer data.
Eric also provides an overview of RudderStack, its open-source approach, and the value it brings to managing customer data. Eric shares a ton of practical advice on building and optimizing your data infrastructure.

In this episode, Kirk Marple, CEO and Co-founder of Graphlit, joins the show. Sean and Kirk dive into the world of unstructured data management, discussing the evolution and current challenges in the field.
While structured data has been well-handled since the 1970s, 80-90% of the world’s data remains unstructured, with predictions of 175 billion terabytes by 2025. Despite this vast amount, companies struggle to utilize it effectively due to immature tools and processes. Graphlit was founded to address this gap, providing scalable, maintainable systems with enhanced observability to handle unstructured data efficiently.
Kirk discusses the challenges in data security and privacy when building RAG-based applications. He discusses some of their exploration into PII scrubbing and also controlled access to the vector embeddings based on the roles of a user.
Finally, looking forward, Kirk shares insights into the future of Graphlit and their continued focus on enhancing the accessibility and utility of unstructured data for businesses across various industries.

In this episode, Jake Moshenko, CEO and co-founder of AuthZed, joins the show to explore the world of user permissions at scale. Inspired by Google's Zanzibar, AuthZed aims to tackle the challenges of authorization - a less common focus compared to authentication in the tech industry.
Jake discusses the initial simplicity and subsequent complications in role-based permission models, where businesses often struggle as they scale and need more nuanced access controls. He explains the Zanzibar paper from Google and the technical challenges with implementing the approach successfully. He explains how AuthZed facilitates a flexible and maintainable permission system and how companies get started.

In this episode host Sean Falconer is joined by Aaron Painter, CEO of Nametag, to explore the evolving threat and potential of AI deepfakes. They discuss the increasing sophistication of deepfake technology, highlighted by the significant rise in incidents such as the Retool hack, and how these technologies can manipulate public perception and security. Aaron discusses the development of technologies to both create and detect deepfakes, discussing the arms race that pits innovation against security.
Aaron shares insights into how his company, Nametag, is at the forefront of combating deepfake fraud by protecting identity data and providing solutions for both companies and individuals to safeguard themselves. They conclude with thoughts on the future, discussing the ongoing technological advancements that are expected to play a crucial role in the fight against deepfakes, aiming to balance innovation with security in the digital landscape.

In this episode we’re joined by Shubh Sinha, CEO and Co-founder of Integral, to discuss the protection and utilization of sensitive health data. Shubh shares insights from his varied career in sales, engineering, and product management, and dives into the challenges of maintaining privacy and security in healthcare. The conversation covers HIPAA regulations, the balance of securing data while keeping it accessible, and the role of generative AI in healthcare innovations. Tune in for a detailed look at how technology is shaping the future of patient treatment and data privacy.

In this episode, we dive into the world of MLOps, the engine behind secure and reliable AI/ML deployments. MLOps focuses on the lifecycle of machine learning models, ensuring they are developed and deployed efficiently and responsibly.
With the explosion of ML applications, the demand for specialized tools has skyrocketed, highlighting the need for improved observability, auditing, and reproducibility. This shift necessitates an evolution in ML toolchains to address gaps in security, governance, and reliability.
Jozu is a platform founded to tackle these very challenges by enhancing the collaboration between AI/ML and application development teams. Jozu aims to provide a comprehensive suite of tools focusing on efficiency throughout the model development and deployment process.
This conversation discusses the importance of MLOps, the limitations of current tools, and how Jozu is paving the way for the future of secure and reliable ML deployments.
Resources:
Jozu
KitOps